US20050037367A9 - Scanned image alignment systems and methods - Google Patents
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- US20050037367A9 US20050037367A9 US10/648,819 US64881903A US2005037367A9 US 20050037367 A9 US20050037367 A9 US 20050037367A9 US 64881903 A US64881903 A US 64881903A US 2005037367 A9 US2005037367 A9 US 2005037367A9
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformation in the plane of the image
- G06T3/60—Rotation of a whole image or part thereof
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/20—Image enhancement or restoration by the use of local operators
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/24—Aligning, centring, orientation detection or correction of the image
- G06V10/245—Aligning, centring, orientation detection or correction of the image by locating a pattern; Special marks for positioning
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G16B25/00—ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20068—Projection on vertical or horizontal image axis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30072—Microarray; Biochip, DNA array; Well plate
Definitions
- a Software Appendix of source code for an embodiment of the invention including two (2) sheets is included herewith.
- the present invention relates to the field of image processing. More specifically, the present invention relates to computer systems for aligning grids on a scanned image of a chip including hybridized nucleic acid sequences.
- an array of nucleic acid probes is fabricated at known locations on a chip.
- a labeled nucleic acid is then brought into contact with the chip and a scanner generates an image file (also called a cell file) indicating the locations where the labeled nucleic acids are bound to the chip.
- an image file also called a cell file
- Such systems have been used to form, for example, arrays of DNA that may be used to study and detect mutations relevant to genetic diseases, cancers, infectious diseases, HIV, and other genetic characteristics.
- the VLSIPSTM technology provides methods of making very large arrays of oligonucleotide probes on very small chips. See U.S. Pat. No. 5,143,854 and PCT patent publication Nos. WO 90/15070 and 92/10092, each of which is incorporated by reference for all purposes.
- the oligonucleotide probes on the DNA probe array are used to detect complementary nucleic acid sequences in a sample nucleic acid of interest (the “target” nucleic acid).
- the chip may be tiled for a specific target nucleic acid sequence.
- the chip may contain probes that are perfectly complementary to the target sequence and probes that differ from the target sequence by a single base mismatch.
- the chip may include all the possible probes of a specific length.
- the probes are tiled on a chip in rows and columns of cells, where each cell includes multiple copies of a particular probe.
- “blank” cells may be present on the chip which do not include any probes. As the blank cells contain no probes, labeled targets should not bind specifically to the chip in this area. Thus, a blank cell provides a measure of the background intensity.
- a cell In the scanned image file, a cell is typically represented by multiple pixels. Although a visual inspection of the scanned image file may be performed to identify the individual cells in the scanned image file. It would be desirable to utilize computer-implemented image processing techniques to align the scanned image file.
- Embodiments of the present invention provide innovative techniques for aligning scanned images.
- a pattern is included in the scanned image so that when the image is convolved with a filter, a recognizable pattern is generated in the convolved image.
- the scanned image may then be aligned according to the position of the recognizable pattern in the convolved image.
- the filter may also act to remove or “filter out” the portions of the scanned image that do not correspond to the pattern in the scanned image.
- the invention provides a computer-implemented method of aligning scanned images.
- the scanned image is convolved with a filter.
- the scanned image includes a first pattern that the filter will convolve into a second pattern in the convolved image.
- the scanned image is then aligned according to the position of the second pattern in the convolved image.
- the first pattern may be a checkerboard pattern that is convolved into a grid pattern in the convolved image.
- the invention provides a method of aligning scanned images of chips with hybridized nucleic sequences.
- a chip having attached nucleic acid sequences (probes) is synthesized, with the chip including a first pattern of nucleic acid sequences.
- Labeled nucleic acid sequences are hybridized to nucleic acid sequences on the chip and the hybridized chip is scanned to produce a scanned image.
- the scanned image is convolved with a filter that will convolve the first pattern into a second pattern in the convolved image.
- the scanned image is then aligned according to the position of the second pattern in the convolved image.
- the first pattern may be a checkerboard pattern that is generated by control nucleic acid sequences that hybridize to alternating squares in the checkerboard pattern.
- FIG. 1 illustrates an example of a computer system that may be utilized to execute the software of an embodiment of the invention.
- FIG. 2 illustrates a system block diagram of the computer system of FIG. 1 .
- FIG. 3 illustrates an overall system for forming and analyzing arrays of biological materials such as DNA or RNA.
- FIG. 4 is a high level flowchart of a process of synthesizing a chip.
- FIG. 5 illustrates conceptually the binding of probes on chips.
- FIG. 6 illustrates a flowchart of how a chip is hybridized and analyzed to produce experimental results.
- FIG. 7A shows a checkerboard pattern in a scanned image and FIG. 7B shows a grid that has been aligned over the scanned image to show the individual cells on the chip.
- FIG. 8 illustrates a flowchart of a process of image alignment.
- FIG. 9A shows a checkerboard pattern in a scanned image
- FIG. 9B shows a convolved image of FIG. 9A with a grid pattern that was generated by the checkerboard pattern.
- FIG. 10 illustrates a flowchart of a process of convolving the scanned image.
- FIG. 11 shows neighbor pixels that may be analyzed to produce a convolved pixel in the convolved image.
- FIGS. 12A-12D show how the filter may be moved over the scanned image to produce the convolved image.
- FIG. 13 illustrates a flowchart of a process of refining the grid alignment over the scanned image.
- FIG. 14 shows the grid lines in the scanned image that may be analyzed to refine the grid alignment.
- FIG. 1 illustrates an example of a computer system that may be used to execute the software of an embodiment of the invention.
- FIG. 1 shows a computer system 1 that includes a display 3 , screen 5 , cabinet 7 , keyboard 9 , and mouse 11 .
- Mouse 11 may have one or more buttons for interacting with a graphical user interface.
- Cabinet 7 houses a CD-ROM drive 13 , system memory and a hard drive (see FIG. 2 ) which may be utilized to store and retrieve software programs incorporating computer code that implements the invention, data for use with the invention, and the like.
- a CD-ROM 15 is shown as an exemplary computer readable storage medium, other computer readable storage media including floppy disk, tape, flash memory, system memory, and hard drive may be utilized.
- a data signal embodied in a carrier wave (e.g., in a network including the Internet) may be the computer readable storage medium.
- FIG. 2 shows a system block diagram of computer system 1 used to execute the software of an embodiment of the invention.
- computer system 1 includes monitor 3 and keyboard 9 , and mouse 11 .
- Computer system 1 further includes subsystems such as a central processor 51 , system memory 53 , fixed storage 55 (e.g., hard drive), removable storage 57 (e.g., CD-ROM drive), display adapter 59 , sound card 61 , speakers 63 , and network interface 65 .
- Other computer systems suitable for use with the invention may include additional or fewer subsystems.
- another computer system could include more than one processor 51 (i.e., a multi-processor system) or a cache memory.
- the system bus architecture of computer system 1 is represented by arrows 67 .
- arrows 67 are illustrative of any interconnection scheme serving to link the subsystems.
- a local bus could be utilized to connect the central processor to the system memory and display adapter.
- Computer system 1 shown in FIG. 2 is but an example of a computer system suitable for use with the invention. Other computer architectures having different configurations of subsystems may also be utilized.
- the present invention provides methods of aligning scanned images or image files of hybridized chips including nucleic acid probes.
- the scanned image files include fluorescence data from a biological array, but the files may also represent other data such as radioactive intensity, light scattering, refractive index, conductivity, electroluminescence, or large molecule detection data. Therefore, the present invention is not limited to analyzing fluorescence measurements of hybridization but may be readily utilized to analyze other measurements of hybridization.
- the present invention is described as being part of a computer system that designs a chip mask, synthesizes the probes on the chip, labels the nucleic acids, and scans the hybridized nucleic acid probes.
- a computer system that designs a chip mask, synthesizes the probes on the chip, labels the nucleic acids, and scans the hybridized nucleic acid probes.
- Such a system is fully described in U.S. Pat. No. 5,571,639 that has been incorporated by reference for all purposes.
- the present invention may be used separately from the overall system for analyzing data generated by such systems.
- FIG. 3 illustrates a computerized system for forming and analyzing arrays of biological materials such as RNA or DNA.
- a computer 100 is used to design arrays of biological polymers such as RNA and DNA.
- the computer 100 may be, for example, an appropriately programmed Sun Workstation or personal computer or workstation, such as an IBM PC equivalent, including appropriate memory and a CPU as shown in FIGS. 1 and 2 .
- the computer system 100 obtains inputs from a user regarding characteristics of a gene of interest, and other inputs regarding the desired features of the array.
- the computer system may obtain information regarding a specific genetic sequence of interest from an external or internal database 102 such as GenBank.
- the output of the computer system 100 is a set of chip design computer files 104 in the form of, for example, a switch matrix, as described in PCT application WO 92/10092, and other associated computer files.
- the chip design files are provided to a system 106 that designs the lithographic masks used in the fabrication of arrays of molecules such as DNA.
- the system or process 106 may include the hardware necessary to manufacture masks 110 and also the necessary computer hardware and software 108 necessary to lay the mask patterns out on the mask in an efficient manner. As with the other features in FIG. 3 , such equipment may or may not be located at the same physical site but is shown together for ease of illustration in FIG. 3 .
- the system 106 generates masks 110 or other synthesis patterns such as chrome-on-glass masks for use in the fabrication of polymer arrays.
- Synthesis system 112 includes the necessary hardware and software used to fabricate arrays of polymers on a substrate or chip 114 .
- synthesizer 112 includes a light source 116 and a chemical flow cell 118 on which the substrate or chip 114 is placed.
- Mask 110 is placed between the light source and the substrate/chip, and the two are translated relative to each other at appropriate times for deprotection of selected regions of the chip.
- Selected chemical regents are directed through flow cell 118 for coupling to deprotected regions, as well as for washing and other operations. All operations are preferably directed by an appropriately programmed computer 119 , which may or may not be the same computer as the computer(s) used in mask design and mask making.
- the substrates fabricated by synthesis system 112 are optionally diced into smaller chips and exposed to marked targets.
- the targets may or may not be complementary to one or more of the molecules on the substrate.
- the targets are marked with a label such as a fluorescein label (indicated by an asterisk in FIG. 3 ) and placed in scanning system 120 .
- Scanning system 120 again operates under the direction of an appropriately programmed digital computer 122 , which also may or may not be the same computer as the computers used in synthesis, mask making, and mask design.
- the scanner 120 includes a detection device 124 such as a confocal microscope or CCD (charge-coupled device) that is used to detect the location where labeled target (*) has bound to the substrate.
- a detection device 124 such as a confocal microscope or CCD (charge-coupled device) that is used to detect the location where labeled target (*) has bound to the substrate.
- the output of scanner 120 is an image file(s) 124 indicating, in the case of fluorescein labeled target, the fluorescence intensity (photon counts or other related measurements, such as voltage) as a function of position on the substrate. Since higher photon counts will be observed where the labeled target has bound more strongly to the array of polymers (e.g., DNA probes on the substrate), and since the monomer sequence of the polymers on the substrate is known as a function of position, it becomes possible to determine the sequence(s) of polymer(s) on the substrate that are complementary to the target.
- image file(s) 124 indicating, in the case of fluorescein labeled target, the fluorescence intensity (photon counts or other related measurements, such as voltage) as a function of position on the substrate. Since higher photon counts will be observed where the labeled target has bound more strongly to the array of polymers (e.g., DNA probes on the substrate), and since the monomer sequence of the polymers on the substrate is known as a function of position
- the image file 124 is provided as input to an analysis system 126 that incorporates the scanned image alignment techniques of the present invention.
- the analysis system may be any one of a wide variety of computer system(s), but in a preferred embodiment the analysis system is based on a WINDOWS NT workstation or equivalent.
- the analysis system may analyze the image file(s) to generate appropriate output 128 , such as the identity of specific mutations in a target such as DNA or RNA.
- FIG. 4 is a high level flowchart of a process of synthesizing a chip.
- the desired chip characteristics are input to the chip synthesis system.
- the chip characteristics may include (such as sequence checking systems) the genetic sequence(s) or targets that would be of interest.
- the sequences of interest may, for example, identify a virus, microorganism or individual. Additionally, the sequence of interest may provide information about genetic diseases, cancers or infectious diseases. Sequence selection may be provided via manual input of text files or may be from external sources such as GenBank. In a preferred embodiment that performs de novo sequencing of target nucleic acids, this steps is not necessary as the chip includes all the possible n-mer probes (where n represents the length of the nucleic acid probe).
- a chip may be synthesized to include cells containing all the possible probes of a specific length. For example, a chip may be synthesized that includes all the possible 8-mer DNA probes. Such a chip would have 65,536 cells (4*4*4*4*4*4*4*4*4), with each cell corresponding to a particular probe. A chip may also include other probes including all the probes of other lengths.
- the system determines which probes would be desirable on the chip, and provides an appropriate “layout” on the chip for the probes.
- the layout implements desired characteristics such as an arrangement on the chip that permits “reading” of genetic sequence and/or minimization of edge effects, ease of synthesis, and the like.
- the masks for the chip synthesis are designed at a step 205 .
- the masks are designed according to the desired chip characteristics and layout.
- the system synthesizes the DNA or other polymer chips. Software controls, among other things, the relative translation of the substrate and mask, the flow of the desired reagents through a flow cell, the synthesis temperature of the flow cell, and other parameters.
- FIG. 5 illustrates the binding of a particular target DNA to an array of DNA probes 114 .
- the following probes are formed in the array: 3′-AGAACGT AGACCGT AGAGCGT AGATCGT • • •
- fluorescein will be primarily found on the surface of the chip where 3′-AGAACGT is located.
- the chip contains cells that include multiple copies of a particular probe.
- the image file will contain fluorescence intensities, one for each probe (or cell).
- FIG. 6 illustrates a flowchart of a process of how a chip is hybridized and analyzed to produce experimental results.
- a chip 251 having attached nucleic acid sequences (or probes) is combined with a sample nucleic acid sequence (e.g., labeled fragments of the sample) and reagents in a hybridization step 255 .
- the hybridization step produces a hybridized chip 257 .
- the hybridized chip is scanned at a step 259 .
- the hybridized chip may be laser scanned to detect where fluorescein-labeled sample fragments have hybridized to the chip. Numerous techniques may be utilized to label the sample fragments and the scanning process will typically be performed according to the type of label utilized.
- the scanning step produces a digital image of the chip.
- the scanned image of the chip includes varying fluorescent intensities that correspond to the hybridization intensity or affinity of the sample to the probes in a cell. In order to achieve more accurate results, it is beneficial to identify the pixels that belong to each cell on the chip.
- the scanned image is aligned so that the pixels that correspond to each cell can be identified.
- the image alignment step includes the alignment of a grid over the scanned image (see FIG. 7B ).
- the analysis system analyzes the scanned image to calculate the relative hybridization intensities for each cell of interest on the chip.
- the hybridization intensity for a cell and therefore the relative hybridization affinity between the probe of the cell and the sample sequence, may be calculated as the mean of the pixel values within the cell.
- the pixel values may correspond to photon counts from the labeled hybridized sample fragments.
- the cell intensities may be stored as a cell intensity file 269 .
- the cell intensity file includes a list of cell intensities for the cells.
- the analysis system may analyze the cell intensity file and chip characteristics to generate results 273 .
- the chip characteristics may be utilized to identify the probes that have been synthesized at each cell on the chip.
- sequence information such as the location of mutations, deletions or insertions, or the sequence of the sample nucleic acid.
- the results may include sequence information, graphs of the hybridization intensities of probe(s), graphs of the differences between sequences, and the like. See U.S. patent application Ser. No. 08/327,525, which is hereby incorporated by reference for all purposes.
- the invention provides a pattern in the scanned image that will be convolved into a recognizable pattern.
- the pattern in the scanned image is a checkerboard pattern that is generated by synthesizing alternating cells that include probes that are complementary to a control nucleic acid sequence.
- the control nucleic acid sequence may be a known sequence that is labeled and hybridized to the chip for the purpose of aligning the scanned image. Additionally, the brightness of the cells complementary to the control nucleic acid sequence may be utilized as a baseline or for comparison to other intensities.
- FIG. 7A shows a checkerboard pattern in a hybridized chip.
- a scanned image 301 of a hybridized chip includes an active area 303 where the probes were synthesized. At the corner of the active area is a pattern 305 that is a checkerboard pattern. Typically, the pattern appears at each corner of the active area of the scanned image.
- the pattern is shown as being a checkerboard pattern, in other embodiments the pattern is a circle, square, plus sign, or any other pattern.
- FIG. 6 it was stated that a grid may optionally be placed over the scanned image to show or delineate the individual cells of the chip.
- FIG. 7B shows a grid that has been aligned over the scanned image of FIG. 7A to show the individual cells of the chip.
- a grid 307 has been placed over active area 303 of hybridized chip 301 .
- FIG. 8 illustrates a flowchart of a process of image alignment.
- the flowchart shows detail for step 263 of FIG. 6 .
- the scanned image is convolved with a filter.
- the filter is typically a software filter that convolves the scanned image into a convolved image.
- a pattern in the scanned image is convolved into a recognizable pattern.
- the position of the recognizable pattern in the convolved image may be utilized to align the scanned image, such as by placing a grid over the image.
- the convolved image is searched for bright areas.
- the pattern(s) in the scanned image will be convolved into a recognizable pattern or patterns of bright areas. Accordingly, once bright areas are identified in the convolved image, the system confirms that the bright areas are in the expected recognizable pattern (e.g., a grid pattern) at a step 355 .
- FIG. 9A shows a checkerboard pattern 401 in a scanned image 403 .
- FIG. 9B shows a recognizable pattern 451 in convolved image 453 .
- the convolved image was generated from the scanned image of FIG. 9A .
- recognizable pattern 41 in this embodiment is a grid pattern that was generated by the checkerboard pattern when it was convolved with a filter. Additionally, it should be noted that the filter acted to remove the other pixel intensities so that the convolved image only includes the recognizable pattern. By removing pixel intensities pixel intensities that are not part of the pattern in the scanned image, it is easier to align the scanned image.
- FIG. 10 illustrates a flowchart of a process of convolving the scanned image.
- the flowchart illustrates a process that may be performed at step 351 of FIG. 8 .
- a pixel is selected.
- the process selects pixels of the scanned image from left to right and top to bottom.
- the order that the pixels are analyzed may be varied.
- neighbor pixels may then be selected at a step 503 .
- neighbor pixels it is meant pixels that the pixels are near, but not necessarily adjacent to a pixel.
- FIG. 11 shows neighbor pixels that may be analyzed to produce a convolved pixel in a convolved image. As shown in FIG. 11 , there are 9 pixels labeled 1-9.
- pixel 1 is the pixel retrieved at step 501 and the neighbor pixels retrieved at step 503 are pixels 2-9. Of course, any number or location of different neighbor pixels may be utilized.
- the average of the odd pixels and the average of the even pixels is determined.
- the intensities of pixels 1, 3, 5, 7, and 9 may be averaged to produce the average of the odd pixels (AVG O ).
- the intensities of pixels 2, 4, 6, and 8 may be averaged to produce the average of the odd pixels (AVG E ).
- the odd pixels may be pixels that have an odd number designation and the even pixels may be pixels that have an even number designation.
- Pixel 1 is convolved into a convolved pixel in a convolved image by determining if the average of the odd pixels is greater than the average of the even pixels at a step 507 . If the average of the odd pixels is greater, the convolved pixel is set equal to the intensity of the minimum of the odd pixels minus the intensity of the maximum of the even pixels at a step 509 . Otherwise, the convolved pixel is set equal to the intensity of the minimum of the even pixels minus the intensity of the maximum of the odd pixels at a step 511 .
- the neighbor pixels may be thought of as being filtered, such as by a software filter in preferred embodiments.
- the filter the system is searching for a checkerboard pattern where all the odd pixels are either darker or lighter than the even pixels. Accordingly, averages of the odd and even pixels are calculated at step 505 .
- Step 507 acts to determine if the pixels likely reflect a checkerboard pattern where the odd pixels, and therefore squares, are light (e.g., high intensity) or dark (e.g., low intensity).
- step 509 sets the convolved pixel to the difference between selected odd and even pixels, where the selected odd pixel is the minimum of the odd pixels and the selected even pixel is the maximum of the even pixels.
- Step 511 is similar but reversed.
- the convolved pixel will be relatively bright (e.g., high intensity).
- the convolved pixel will also be relatively bright if all the even pixels are much brighter than all the odd pixels at step 511 .
- the convolved pixel will be set to a relatively dark intensity. Convolved pixels with negative pixel values may be set to a zero in preferred embodiments.
- the convolved pixel will be bright and if the filter finds a relatively random pattern, the convolved pixel will be dark (thus, filtering out “noise” that is not the desired pattern).
- FIG. 9B which is a grid pattern
- FIGS. 12 A-D show how the filter may be moved over the checkerboard to produce a grid pattern in the convolved image.
- a bright square will be generated in the convolved image since a checkerboard pattern will be found.
- a bright square will be generated in the convolved image when the filter is over the pattern in square 530 of FIG. 12B .
- FIGS. 12A and 12B are reversed, but both will produce a bright square in the convolved image as described above in reference to FIG. 10 .
- FIGS. 12C and 12D will also produce two bright squares. Therefore, a 2 ⁇ 2 bright square grid pattern is generated as shown in FIG. 9B .
- the software filter of FIG. 10 acts to filter out signals that are not the desired pattern
- the recognizable pattern e.g., a grid pattern
- the recognizable patterns in the convolved image are utilized to align the scanned image.
- refined image alignment may be performed to further increase the accuracy of the scanned image alignment.
- FIG. 13 illustrates a flowchart of a process of refining grid alignment over a scanned image.
- the process in FIG. 13 may be utilized to refine the alignment.
- pixel intensities on grid lines in the grid are summed.
- the intensities of the grid in a vertical direction in the checkerboard pattern in the scanned image may be summed.
- FIG. 14 shows the grid lines in the scanned image that may be analyzed to refine the grid alignment. As shown, the pixel intensities of vertical lines 601 of a checkerboard pattern 603 may be summed and stored.
- the system may determine if there are more positions of the grid to analyze. If there are, the position of the grid may be adjusted at a step 555 . Therefore, the grid may be moved left and right by one or more pixels before the intensities are summed along grid lines at step 551 . Once all the positions of the grid have been analyzed, the system selects a grid position where pixel intensities (e.g., the sum calculated at step 551 ) are at a minimum. Therefore, if the pixel intensities for grid lines are lower at another position, the grid is adjusted accordingly. This refinement will work well if the cells are typically separated by a darker area or line.
- pixel intensities e.g., the sum calculated at step 551
- the process in FIG. 13 was described for grid lines in the vertical direction, preferred embodiments also perform the same grid alignment for the horizontal direction.
- the distance that the grid is able to be moved for refinement may be limited.
- the grid may be limited to movement of one-third a cell size.
Abstract
Systems and methods for aligning scanned images are provided. A pattern is included in the scanned image so that when the image is convolved with a filter, a recognizable pattern is generated in the convolved image. The scanned image may then be aligned according to the position of the recognizable pattern in the convolved image. The filter may also act to remove the portions of the scanned image that do not correspond to the pattern in the scanned image.
Description
- A portion of the disclosure of this patent document contains material that is subject to copyright protection. The copyright owner has no objection to the xerographic reproduction by anyone of the patent document or the patent disclosure in exactly the form it appears in the Patent and Trademark Office patent file or records, but otherwise reserves all copyright rights whatsoever.
- A Software Appendix of source code for an embodiment of the invention including two (2) sheets is included herewith.
- The present invention relates to the field of image processing. More specifically, the present invention relates to computer systems for aligning grids on a scanned image of a chip including hybridized nucleic acid sequences.
- Devices and computer systems for forming and using arrays of materials on a chip or substrate are known. For example, PCT applications WO92/10588 and 95/11995, both incorporated herein by reference for all purposes, describe techniques for sequencing or sequence checking nucleic acids and other materials. Arrays for performing these operations may be formed in arrays according to the methods of, for example, the pioneering techniques disclosed in U.S. Pat. Nos. 5,445,934, 5,384,261 and 5,571,639, each incorporated herein by reference for all purposes.
- According to one aspect of the techniques described therein, an array of nucleic acid probes is fabricated at known locations on a chip. A labeled nucleic acid is then brought into contact with the chip and a scanner generates an image file (also called a cell file) indicating the locations where the labeled nucleic acids are bound to the chip. Based upon the image file and identities of the probes at specific locations, it becomes possible to extract information such as the nucleotide or monomer sequence of DNA or RNA. Such systems have been used to form, for example, arrays of DNA that may be used to study and detect mutations relevant to genetic diseases, cancers, infectious diseases, HIV, and other genetic characteristics.
- The VLSIPS™ technology provides methods of making very large arrays of oligonucleotide probes on very small chips. See U.S. Pat. No. 5,143,854 and PCT patent publication Nos. WO 90/15070 and 92/10092, each of which is incorporated by reference for all purposes. The oligonucleotide probes on the DNA probe array are used to detect complementary nucleic acid sequences in a sample nucleic acid of interest (the “target” nucleic acid).
- For sequence checking applications, the chip may be tiled for a specific target nucleic acid sequence. As an example, the chip may contain probes that are perfectly complementary to the target sequence and probes that differ from the target sequence by a single base mismatch. For de novo sequencing applications, the chip may include all the possible probes of a specific length. The probes are tiled on a chip in rows and columns of cells, where each cell includes multiple copies of a particular probe. Additionally, “blank” cells may be present on the chip which do not include any probes. As the blank cells contain no probes, labeled targets should not bind specifically to the chip in this area. Thus, a blank cell provides a measure of the background intensity.
- In the scanned image file, a cell is typically represented by multiple pixels. Although a visual inspection of the scanned image file may be performed to identify the individual cells in the scanned image file. It would be desirable to utilize computer-implemented image processing techniques to align the scanned image file.
- Embodiments of the present invention provide innovative techniques for aligning scanned images. A pattern is included in the scanned image so that when the image is convolved with a filter, a recognizable pattern is generated in the convolved image. The scanned image may then be aligned according to the position of the recognizable pattern in the convolved image. The filter may also act to remove or “filter out” the portions of the scanned image that do not correspond to the pattern in the scanned image. Several embodiments of the invention are described below.
- In one embodiment, the invention provides a computer-implemented method of aligning scanned images. The scanned image is convolved with a filter. The scanned image includes a first pattern that the filter will convolve into a second pattern in the convolved image. The scanned image is then aligned according to the position of the second pattern in the convolved image. In a preferred embodiment, the first pattern may be a checkerboard pattern that is convolved into a grid pattern in the convolved image.
- In another embodiment, the invention provides a method of aligning scanned images of chips with hybridized nucleic sequences. A chip having attached nucleic acid sequences (probes) is synthesized, with the chip including a first pattern of nucleic acid sequences. Labeled nucleic acid sequences are hybridized to nucleic acid sequences on the chip and the hybridized chip is scanned to produce a scanned image. The scanned image is convolved with a filter that will convolve the first pattern into a second pattern in the convolved image. The scanned image is then aligned according to the position of the second pattern in the convolved image. In a preferred embodiment, the first pattern may be a checkerboard pattern that is generated by control nucleic acid sequences that hybridize to alternating squares in the checkerboard pattern.
- Other features and advantages of the invention will become readily apparent upon review of the following detailed description in association with the accompanying drawings.
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FIG. 1 illustrates an example of a computer system that may be utilized to execute the software of an embodiment of the invention. -
FIG. 2 illustrates a system block diagram of the computer system ofFIG. 1 . -
FIG. 3 illustrates an overall system for forming and analyzing arrays of biological materials such as DNA or RNA. -
FIG. 4 is a high level flowchart of a process of synthesizing a chip. -
FIG. 5 illustrates conceptually the binding of probes on chips. -
FIG. 6 illustrates a flowchart of how a chip is hybridized and analyzed to produce experimental results. -
FIG. 7A shows a checkerboard pattern in a scanned image andFIG. 7B shows a grid that has been aligned over the scanned image to show the individual cells on the chip. -
FIG. 8 illustrates a flowchart of a process of image alignment. -
FIG. 9A shows a checkerboard pattern in a scanned image andFIG. 9B shows a convolved image ofFIG. 9A with a grid pattern that was generated by the checkerboard pattern. -
FIG. 10 illustrates a flowchart of a process of convolving the scanned image. -
FIG. 11 shows neighbor pixels that may be analyzed to produce a convolved pixel in the convolved image. -
FIGS. 12A-12D show how the filter may be moved over the scanned image to produce the convolved image. -
FIG. 13 illustrates a flowchart of a process of refining the grid alignment over the scanned image. -
FIG. 14 shows the grid lines in the scanned image that may be analyzed to refine the grid alignment. - Overview
- In the description that follows, the present invention will be described in reference to preferred embodiments that utilize VLSIPS™ technology for making very large arrays of oligonucleotide probes on chips. However, the invention is not limited to images produced in this fashion and may be advantageously applied other hybridization technologies or images in other technology areas. Therefore, the description of the embodiments that follows for purposes of illustration and not limitation.
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FIG. 1 illustrates an example of a computer system that may be used to execute the software of an embodiment of the invention.FIG. 1 shows acomputer system 1 that includes adisplay 3,screen 5,cabinet 7,keyboard 9, andmouse 11.Mouse 11 may have one or more buttons for interacting with a graphical user interface.Cabinet 7 houses a CD-ROM drive 13, system memory and a hard drive (seeFIG. 2 ) which may be utilized to store and retrieve software programs incorporating computer code that implements the invention, data for use with the invention, and the like. Although a CD-ROM 15 is shown as an exemplary computer readable storage medium, other computer readable storage media including floppy disk, tape, flash memory, system memory, and hard drive may be utilized. Additionally, a data signal embodied in a carrier wave (e.g., in a network including the Internet) may be the computer readable storage medium. -
FIG. 2 shows a system block diagram ofcomputer system 1 used to execute the software of an embodiment of the invention. As inFIG. 1 ,computer system 1 includesmonitor 3 andkeyboard 9, andmouse 11.Computer system 1 further includes subsystems such as acentral processor 51,system memory 53, fixed storage 55 (e.g., hard drive), removable storage 57 (e.g., CD-ROM drive),display adapter 59,sound card 61,speakers 63, andnetwork interface 65. Other computer systems suitable for use with the invention may include additional or fewer subsystems. For example, another computer system could include more than one processor 51 (i.e., a multi-processor system) or a cache memory. - The system bus architecture of
computer system 1 is represented byarrows 67. However, these arrows are illustrative of any interconnection scheme serving to link the subsystems. For example, a local bus could be utilized to connect the central processor to the system memory and display adapter.Computer system 1 shown inFIG. 2 is but an example of a computer system suitable for use with the invention. Other computer architectures having different configurations of subsystems may also be utilized. - The present invention provides methods of aligning scanned images or image files of hybridized chips including nucleic acid probes. In a representative embodiment, the scanned image files include fluorescence data from a biological array, but the files may also represent other data such as radioactive intensity, light scattering, refractive index, conductivity, electroluminescence, or large molecule detection data. Therefore, the present invention is not limited to analyzing fluorescence measurements of hybridization but may be readily utilized to analyze other measurements of hybridization.
- For purposes of illustration, the present invention is described as being part of a computer system that designs a chip mask, synthesizes the probes on the chip, labels the nucleic acids, and scans the hybridized nucleic acid probes. Such a system is fully described in U.S. Pat. No. 5,571,639 that has been incorporated by reference for all purposes. However, the present invention may be used separately from the overall system for analyzing data generated by such systems.
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FIG. 3 illustrates a computerized system for forming and analyzing arrays of biological materials such as RNA or DNA. Acomputer 100 is used to design arrays of biological polymers such as RNA and DNA. Thecomputer 100 may be, for example, an appropriately programmed Sun Workstation or personal computer or workstation, such as an IBM PC equivalent, including appropriate memory and a CPU as shown inFIGS. 1 and 2 . Thecomputer system 100 obtains inputs from a user regarding characteristics of a gene of interest, and other inputs regarding the desired features of the array. Optionally, the computer system may obtain information regarding a specific genetic sequence of interest from an external orinternal database 102 such as GenBank. The output of thecomputer system 100 is a set of chip design computer files 104 in the form of, for example, a switch matrix, as described in PCT application WO 92/10092, and other associated computer files. - The chip design files are provided to a
system 106 that designs the lithographic masks used in the fabrication of arrays of molecules such as DNA. The system orprocess 106 may include the hardware necessary to manufacturemasks 110 and also the necessary computer hardware andsoftware 108 necessary to lay the mask patterns out on the mask in an efficient manner. As with the other features inFIG. 3 , such equipment may or may not be located at the same physical site but is shown together for ease of illustration inFIG. 3 . Thesystem 106 generatesmasks 110 or other synthesis patterns such as chrome-on-glass masks for use in the fabrication of polymer arrays. - The
masks 110, as well as selected information relating to the design of the chips fromsystem 100, are used in asynthesis system 112.Synthesis system 112 includes the necessary hardware and software used to fabricate arrays of polymers on a substrate orchip 114. For example,synthesizer 112 includes alight source 116 and achemical flow cell 118 on which the substrate orchip 114 is placed.Mask 110 is placed between the light source and the substrate/chip, and the two are translated relative to each other at appropriate times for deprotection of selected regions of the chip. Selected chemical regents are directed throughflow cell 118 for coupling to deprotected regions, as well as for washing and other operations. All operations are preferably directed by an appropriately programmedcomputer 119, which may or may not be the same computer as the computer(s) used in mask design and mask making. - The substrates fabricated by
synthesis system 112 are optionally diced into smaller chips and exposed to marked targets. The targets may or may not be complementary to one or more of the molecules on the substrate. The targets are marked with a label such as a fluorescein label (indicated by an asterisk inFIG. 3 ) and placed inscanning system 120.Scanning system 120 again operates under the direction of an appropriately programmeddigital computer 122, which also may or may not be the same computer as the computers used in synthesis, mask making, and mask design. Thescanner 120 includes adetection device 124 such as a confocal microscope or CCD (charge-coupled device) that is used to detect the location where labeled target (*) has bound to the substrate. The output ofscanner 120 is an image file(s) 124 indicating, in the case of fluorescein labeled target, the fluorescence intensity (photon counts or other related measurements, such as voltage) as a function of position on the substrate. Since higher photon counts will be observed where the labeled target has bound more strongly to the array of polymers (e.g., DNA probes on the substrate), and since the monomer sequence of the polymers on the substrate is known as a function of position, it becomes possible to determine the sequence(s) of polymer(s) on the substrate that are complementary to the target. - The
image file 124 is provided as input to ananalysis system 126 that incorporates the scanned image alignment techniques of the present invention. Again, the analysis system may be any one of a wide variety of computer system(s), but in a preferred embodiment the analysis system is based on a WINDOWS NT workstation or equivalent. The analysis system may analyze the image file(s) to generateappropriate output 128, such as the identity of specific mutations in a target such as DNA or RNA. -
FIG. 4 is a high level flowchart of a process of synthesizing a chip. At astep 201, the desired chip characteristics are input to the chip synthesis system. The chip characteristics may include (such as sequence checking systems) the genetic sequence(s) or targets that would be of interest. The sequences of interest may, for example, identify a virus, microorganism or individual. Additionally, the sequence of interest may provide information about genetic diseases, cancers or infectious diseases. Sequence selection may be provided via manual input of text files or may be from external sources such as GenBank. In a preferred embodiment that performs de novo sequencing of target nucleic acids, this steps is not necessary as the chip includes all the possible n-mer probes (where n represents the length of the nucleic acid probe). - For de novo sequencing, a chip may be synthesized to include cells containing all the possible probes of a specific length. For example, a chip may be synthesized that includes all the possible 8-mer DNA probes. Such a chip would have 65,536 cells (4*4*4*4*4*4*4*4), with each cell corresponding to a particular probe. A chip may also include other probes including all the probes of other lengths.
- At a
step 203 the system determines which probes would be desirable on the chip, and provides an appropriate “layout” on the chip for the probes. The layout implements desired characteristics such as an arrangement on the chip that permits “reading” of genetic sequence and/or minimization of edge effects, ease of synthesis, and the like. - The masks for the chip synthesis are designed at a
step 205. The masks are designed according to the desired chip characteristics and layout. At astep 207, the system synthesizes the DNA or other polymer chips. Software controls, among other things, the relative translation of the substrate and mask, the flow of the desired reagents through a flow cell, the synthesis temperature of the flow cell, and other parameters. -
FIG. 5 illustrates the binding of a particular target DNA to an array of DNA probes 114. As shown in this simple example, the following probes are formed in the array:3′-AGAACGT AGACCGT AGAGCGT AGATCGT • • •
As shown, when the fluorescein-labeled (or otherwise marked)target 5′-TCTTGCA is exposed to the array, it is complementary only to theprobe 3′-AGAACGT, and fluorescein will be primarily found on the surface of the chip where 3′-AGAACGT is located. The chip contains cells that include multiple copies of a particular probe. Thus, the image file will contain fluorescence intensities, one for each probe (or cell). By analyzing the fluorescence intensities associated with a specific probe, it becomes possible to extract sequence information from such arrays using the methods of the invention disclosed herein. - For ease of reference, one may call bases by assigning the bases the following codes:
Code Group Meaning A A Adenine C C Cytosine G G Guanine T T(U) Thymine (Uracil) M A or C aMino R A or G puRine W A or T(U) Weak interaction (2 H bonds) Y C or T(U) pYrimidine S C or G Strong interaction (3 H bonds) K G or T(U) Keto V A, C or G not T(U) H A, C or T(U) not G D A, G or T(U) not C B C, G or T(U) not A N A, C, G, or T(U) Insufficient intensity to call X A, C, G, or T(U) Insufficient discrimination to call
Most of the codes conform to the IUPAC standard. However, code N has been redefined and code X has been added.
Scanned Image Alignment - Before the scanned image alignment of the invention are discussed, it may be helpful to provide an overview of the overall process in one embodiment.
FIG. 6 illustrates a flowchart of a process of how a chip is hybridized and analyzed to produce experimental results. Achip 251 having attached nucleic acid sequences (or probes) is combined with a sample nucleic acid sequence (e.g., labeled fragments of the sample) and reagents in ahybridization step 255. The hybridization step produces a hybridizedchip 257. - The hybridized chip is scanned at a
step 259. For example, the hybridized chip may be laser scanned to detect where fluorescein-labeled sample fragments have hybridized to the chip. Numerous techniques may be utilized to label the sample fragments and the scanning process will typically be performed according to the type of label utilized. The scanning step produces a digital image of the chip. - In preferred embodiments, the scanned image of the chip includes varying fluorescent intensities that correspond to the hybridization intensity or affinity of the sample to the probes in a cell. In order to achieve more accurate results, it is beneficial to identify the pixels that belong to each cell on the chip. At an
image alignment step 263, the scanned image is aligned so that the pixels that correspond to each cell can be identified. Optionally, the image alignment step includes the alignment of a grid over the scanned image (seeFIG. 7B ). - At a
step 267, the analysis system analyzes the scanned image to calculate the relative hybridization intensities for each cell of interest on the chip. For example, the hybridization intensity for a cell, and therefore the relative hybridization affinity between the probe of the cell and the sample sequence, may be calculated as the mean of the pixel values within the cell. The pixel values may correspond to photon counts from the labeled hybridized sample fragments. - The cell intensities may be stored as a
cell intensity file 269. In preferred embodiments, the cell intensity file includes a list of cell intensities for the cells. At ananalysis step 271, the analysis system may analyze the cell intensity file and chip characteristics to generateresults 273. The chip characteristics may be utilized to identify the probes that have been synthesized at each cell on the chip. By analyzing both the sequence of the probes and their hybridization intensities from the cell intensity file, the system is able to extract sequence information such as the location of mutations, deletions or insertions, or the sequence of the sample nucleic acid. Accordingly, the results may include sequence information, graphs of the hybridization intensities of probe(s), graphs of the differences between sequences, and the like. See U.S. patent application Ser. No. 08/327,525, which is hereby incorporated by reference for all purposes. - In order to align the scanned image, the invention provides a pattern in the scanned image that will be convolved into a recognizable pattern. In preferred embodiments, the pattern in the scanned image is a checkerboard pattern that is generated by synthesizing alternating cells that include probes that are complementary to a control nucleic acid sequence. The control nucleic acid sequence may be a known sequence that is labeled and hybridized to the chip for the purpose of aligning the scanned image. Additionally, the brightness of the cells complementary to the control nucleic acid sequence may be utilized as a baseline or for comparison to other intensities.
- As an example,
FIG. 7A shows a checkerboard pattern in a hybridized chip. A scannedimage 301 of a hybridized chip includes anactive area 303 where the probes were synthesized. At the corner of the active area is apattern 305 that is a checkerboard pattern. Typically, the pattern appears at each corner of the active area of the scanned image. Although the pattern is shown as being a checkerboard pattern, in other embodiments the pattern is a circle, square, plus sign, or any other pattern. - With regard to
FIG. 6 , it was stated that a grid may optionally be placed over the scanned image to show or delineate the individual cells of the chip.FIG. 7B shows a grid that has been aligned over the scanned image ofFIG. 7A to show the individual cells of the chip. As shown, a grid 307 has been placed overactive area 303 of hybridizedchip 301. -
FIG. 8 illustrates a flowchart of a process of image alignment. The flowchart shows detail forstep 263 ofFIG. 6 . At astep 351, the scanned image is convolved with a filter. The filter is typically a software filter that convolves the scanned image into a convolved image. When the scanned image is convolved, a pattern in the scanned image is convolved into a recognizable pattern. The position of the recognizable pattern in the convolved image may be utilized to align the scanned image, such as by placing a grid over the image. - At a
step 353, the convolved image is searched for bright areas. When the scanned image is convolved, the pattern(s) in the scanned image will be convolved into a recognizable pattern or patterns of bright areas. Accordingly, once bright areas are identified in the convolved image, the system confirms that the bright areas are in the expected recognizable pattern (e.g., a grid pattern) at astep 355. - In order to better understand what is meant by the different patterns,
FIG. 9A shows acheckerboard pattern 401 in a scannedimage 403.FIG. 9B shows arecognizable pattern 451 inconvolved image 453. The convolved image was generated from the scanned image ofFIG. 9A . As shown, recognizable pattern 41 in this embodiment is a grid pattern that was generated by the checkerboard pattern when it was convolved with a filter. Additionally, it should be noted that the filter acted to remove the other pixel intensities so that the convolved image only includes the recognizable pattern. By removing pixel intensities pixel intensities that are not part of the pattern in the scanned image, it is easier to align the scanned image. -
FIG. 10 illustrates a flowchart of a process of convolving the scanned image. The flowchart illustrates a process that may be performed atstep 351 ofFIG. 8 . At astep 501, a pixel is selected. For simplicity, we will assume that the process selects pixels of the scanned image from left to right and top to bottom. Of course, the order that the pixels are analyzed may be varied. - Once a pixel selected, neighbor pixels may then be selected at a
step 503. By neighbor pixels, it is meant pixels that the pixels are near, but not necessarily adjacent to a pixel. For example,FIG. 11 shows neighbor pixels that may be analyzed to produce a convolved pixel in a convolved image. As shown inFIG. 11 , there are 9 pixels labeled 1-9. In a preferred embodiment,pixel 1 is the pixel retrieved atstep 501 and the neighbor pixels retrieved atstep 503 are pixels 2-9. Of course, any number or location of different neighbor pixels may be utilized. - At a
step 505, the average of the odd pixels and the average of the even pixels is determined. Referring again toFIG. 11 , the intensities ofpixels pixels -
Pixel 1 is convolved into a convolved pixel in a convolved image by determining if the average of the odd pixels is greater than the average of the even pixels at astep 507. If the average of the odd pixels is greater, the convolved pixel is set equal to the intensity of the minimum of the odd pixels minus the intensity of the maximum of the even pixels at astep 509. Otherwise, the convolved pixel is set equal to the intensity of the minimum of the even pixels minus the intensity of the maximum of the odd pixels at astep 511. - Conceptually, the neighbor pixels may be thought of as being filtered, such as by a software filter in preferred embodiments. With the filter, the system is searching for a checkerboard pattern where all the odd pixels are either darker or lighter than the even pixels. Accordingly, averages of the odd and even pixels are calculated at
step 505. Step 507 acts to determine if the pixels likely reflect a checkerboard pattern where the odd pixels, and therefore squares, are light (e.g., high intensity) or dark (e.g., low intensity). If the odd pixels likely reflect a checkerboard pattern where the odd pixels are light,step 509 sets the convolved pixel to the difference between selected odd and even pixels, where the selected odd pixel is the minimum of the odd pixels and the selected even pixel is the maximum of the even pixels. Step 511 is similar but reversed. - Therefore, at
step 509, if all the odd pixels are much brighter than all the even pixels, the difference will be a larger value. Hence, the convolved pixel will be relatively bright (e.g., high intensity). The convolved pixel will also be relatively bright if all the even pixels are much brighter than all the odd pixels atstep 511. However, if the difference atstep - The recognizable pattern in
FIG. 9B , which is a grid pattern, was generated by the software filter ofFIG. 10 . In order to better see how the recognizable pattern was generated, FIGS. 12A-D show how the filter may be moved over the checkerboard to produce a grid pattern in the convolved image. As the filter is convolved over the pattern in the scanned image shown in a square 530 inFIG. 12A , a bright square will be generated in the convolved image since a checkerboard pattern will be found. Similarly, a bright square will be generated in the convolved image when the filter is over the pattern insquare 530 ofFIG. 12B . Of course, the checkerboard patterns insquare 530 ofFIGS. 12A and 12B are reversed, but both will produce a bright square in the convolved image as described above in reference toFIG. 10 .FIGS. 12C and 12D will also produce two bright squares. Therefore, a 2×2 bright square grid pattern is generated as shown inFIG. 9B . - Additionally, as the software filter of
FIG. 10 acts to filter out signals that are not the desired pattern, the recognizable pattern (e.g., a grid pattern) is easier to identify. The recognizable patterns in the convolved image are utilized to align the scanned image. Returning now toFIG. 10 , after a selected pixel is convolved into a convolved pixel by the filter, it is determined if there is another pixel to process in the scanned image at astep 513. - The following shows how well an embodiment of the invention aligned scanned images of hybridized chips:
Previous method With filter convolution Perfect alignment 0% 4% 1 pixel off 8% 96% 2 or more pixels off 20% 0% 1 or more cells off 12% 0% unable to align 60% 0%
The previous method was to analyze the scanned image (unfiltered) to locate bright areas or spots in a checkerboard pattern. As shown, an embodiment of the invention was able to dramatically increase the accuracy of scanned image alignment.
Refined Grid Alignment - In preferred embodiments, refined image alignment may be performed to further increase the accuracy of the scanned image alignment.
FIG. 13 illustrates a flowchart of a process of refining grid alignment over a scanned image. Thus, for example, once the above-described process has been performed to align the scanned image, the process inFIG. 13 may be utilized to refine the alignment. - At a
step 551, pixel intensities on grid lines in the grid are summed. For example, the intensities of the grid in a vertical direction in the checkerboard pattern in the scanned image may be summed.FIG. 14 shows the grid lines in the scanned image that may be analyzed to refine the grid alignment. As shown, the pixel intensities ofvertical lines 601 of acheckerboard pattern 603 may be summed and stored. - Then, at a
step 553, the system may determine if there are more positions of the grid to analyze. If there are, the position of the grid may be adjusted at astep 555. Therefore, the grid may be moved left and right by one or more pixels before the intensities are summed along grid lines atstep 551. Once all the positions of the grid have been analyzed, the system selects a grid position where pixel intensities (e.g., the sum calculated at step 551) are at a minimum. Therefore, if the pixel intensities for grid lines are lower at another position, the grid is adjusted accordingly. This refinement will work well if the cells are typically separated by a darker area or line. - Although the process in
FIG. 13 was described for grid lines in the vertical direction, preferred embodiments also perform the same grid alignment for the horizontal direction. The distance that the grid is able to be moved for refinement may be limited. For example, the grid may be limited to movement of one-third a cell size. - The following shows how well an embodiment of the invention aligned scanned images of hybridized chips utilizing the refined grid alignment:
Previous method With refined grid alignment Perfect alignment 0% 64% 1 pixel off 8% 36% 2 or more pixels off 20% 0% 1 or more cells off 12% 0% unable to align 60% 0%
Once again, the previous method was to analyze the scanned image (unfiltered) to locate bright areas or spots in a checkerboard pattern. As shown, an embodiment of the invention was able to dramatically increase the accuracy of scanned image alignment. Furthermore, refining grid alignment increased the percentage of scanned images that were perfectly aligned with the invention from 4% to 64%. Therefore, performing a refinement of grid alignment can significantly increase the accuracy of the grid alignment.
Conclusion - While the above is a complete description of preferred embodiments of the invention, various alternatives, modifications, and equivalents may be used. It should be evident that the invention is equally applicable by making appropriate modifications to the embodiments described above. For example, the invention has been described in reference to a checkerboard pattern in the scanned image. However, the invention is not limited to any one pattern and may be advantageously applied to other patterns including those described herein. Therefore, the above description should not be taken as limiting the scope of the invention that is defined by the metes and bounds of the appended claims along with their full scope of equivalents.
Claims (23)
1. In a computer system, a method of aligning scanned images, comprising:
convolving a scanned image with a filter, the scanned image including a first pattern that the filter will convolve into a second pattern in a convolved image; and
aligning the scanned image according to a position of the second pattern in the convolved image.
2. The method of claim 1 , wherein convolving a scanned image with a filter comprises setting a convolved pixel to a difference between a selected odd pixel and a selected even pixel of the first pattern.
3. The method of claim 2 , wherein the selected odd pixel has the lowest intensity of the odd pixels and the selected even pixel has the highest intensity of the even pixels, if the average intensity of the odd pixels is greater than the average intensity of the even pixels.
4. The method of claim 2 , wherein the selected odd pixel has the highest intensity of the odd pixels and the selected even pixel has the lowest intensity of the even pixels, if the average intensity of the odd pixels is not greater than the average intensity of the even pixels.
5. The method of claim 1 , wherein the first pattern is a checkerboard pattern.
6. The method of claim 1 , wherein the second pattern is a grid pattern.
7. The method of claim 1 , wherein aligning the scanned image comprises aligning a grid over the scanned image.
8. The method of claim 7 , further comprising adjusting the position of the grid to minimize a sum of the intensities of pixels along a direction in the grid.
9. The method of claim 1 , wherein the scanned image includes multiple copies of the first pattern.
10. The method of claim 9 , wherein the scanned image is a rectangle with a copy of the first pattern near each corner.
11. A computer program product that aligns scanned images, comprising:
computer code that convolves a scanned image with a filter, the scanned image including a first pattern that the filter will convolve into a second pattern in a convolved image;
computer code that aligns the scanned image according to a position of the second pattern in the convolved image; and
a computer readable medium that stores the computer codes.
12. A method of aligning scanned images, comprising:
synthesizing a chip having attached nucleic acid sequences, the chip including a first pattern of nucleic acid sequences;
hybridizing labeled nucleic acid sequences to nucleic acid sequences on the chip;
scanning the hybridized chip to produce a scanned image;
convolving the scanned image with a filter, the filter convolving the first pattern into a second pattern in a convolved image; and
aligning the scanned image according to a position of the second pattern in the convolved image.
13. The method of claim 12 , wherein convolving the scanned image with a filter comprises setting a convolved pixel to a difference between a selected odd pixel and a selected even pixel of the first pattern.
14. The method of claim 13 , wherein the selected odd pixel has the lowest intensity of the odd pixels and the selected even pixel has the highest intensity of the even pixels, if the average intensity of the odd pixels is greater than the average intensity of the even pixels.
15. The method of claim 13 , wherein the selected odd pixel has the highest intensity of the odd pixels and the selected even pixel has the lowest intensity of the even pixels, if the average intensity of the odd pixels is not greater than the average intensity of the even pixels.
16. The method of claim 12 , wherein the first pattern is a checkerboard pattern.
17. The method of claim 16 , wherein the labeled nucleic acid sequences include control nucleic acid sequences that hybridize to alternating squares in the checkerboard pattern.
18. The method of claim 12 , wherein the second pattern is a grid pattern.
19. The method of claim 12 , wherein aligning the scanned image comprises aligning a grid over the scanned image.
20. The method of claim 19 , further comprising adjusting the position of the grid to minimize a sum of the intensities of pixels along a direction in the grid.
21. The method of claim 12 , wherein the scanned image includes multiple copies of the first pattern.
22. The method of claim 21 , wherein the scanned image is a rectangle with a copy of the first pattern near each corner.
23. A computer program product that aligns scanned images, comprising:
computer code that receives as input a scanned image of a chip having attached nucleic acid sequences to which labeled nucleic acid sequences are hybridized, the chip including a first pattern of nucleic acid sequences;
computer code that convolves the scanned image with a filter, the filter convolving the first pattern into a second pattern in a convolved image;
computer code that aligns the scanned image according to a position of the second pattern in the convolved image; and
a computer readable medium that stores the computer codes.
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Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20040076957A1 (en) * | 2001-02-01 | 2004-04-22 | Tetsuhiko Yoshida | Hybridized array analysis aiding method and analysis aiding service |
US20070192385A1 (en) * | 2005-11-28 | 2007-08-16 | Anand Prahlad | Systems and methods for using metadata to enhance storage operations |
US20070226535A1 (en) * | 2005-12-19 | 2007-09-27 | Parag Gokhale | Systems and methods of unified reconstruction in storage systems |
US20090193113A1 (en) * | 2008-01-30 | 2009-07-30 | Commvault Systems, Inc. | Systems and methods for grid-based data scanning |
US8296301B2 (en) | 2008-01-30 | 2012-10-23 | Commvault Systems, Inc. | Systems and methods for probabilistic data classification |
US8892523B2 (en) | 2012-06-08 | 2014-11-18 | Commvault Systems, Inc. | Auto summarization of content |
US8984614B2 (en) | 2003-11-26 | 2015-03-17 | Rockstar Consortium Us Lp | Socks tunneling for firewall traversal |
US9134931B2 (en) | 2013-04-30 | 2015-09-15 | Hewlett-Packard Development Company, L.P. | Printing content over a network |
US10389810B2 (en) | 2016-11-02 | 2019-08-20 | Commvault Systems, Inc. | Multi-threaded scanning of distributed file systems |
US10540516B2 (en) | 2016-10-13 | 2020-01-21 | Commvault Systems, Inc. | Data protection within an unsecured storage environment |
US10642886B2 (en) | 2018-02-14 | 2020-05-05 | Commvault Systems, Inc. | Targeted search of backup data using facial recognition |
US10922189B2 (en) | 2016-11-02 | 2021-02-16 | Commvault Systems, Inc. | Historical network data-based scanning thread generation |
US11442820B2 (en) | 2005-12-19 | 2022-09-13 | Commvault Systems, Inc. | Systems and methods of unified reconstruction in storage systems |
Families Citing this family (214)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6090555A (en) * | 1997-12-11 | 2000-07-18 | Affymetrix, Inc. | Scanned image alignment systems and methods |
US5631734A (en) | 1994-02-10 | 1997-05-20 | Affymetrix, Inc. | Method and apparatus for detection of fluorescently labeled materials |
US6741344B1 (en) * | 1994-02-10 | 2004-05-25 | Affymetrix, Inc. | Method and apparatus for detection of fluorescently labeled materials |
EP2290364A1 (en) | 1996-04-25 | 2011-03-02 | BioArray Solutions Ltd. | Light-controlled electrokinetic assembly of particles near surfaces |
US20020150909A1 (en) * | 1999-02-09 | 2002-10-17 | Stuelpnagel John R. | Automated information processing in randomly ordered arrays |
US6136541A (en) | 1999-02-22 | 2000-10-24 | Vialogy Corporation | Method and apparatus for analyzing hybridized biochip patterns using resonance interactions employing quantum expressor functions |
US20040111219A1 (en) * | 1999-02-22 | 2004-06-10 | Sandeep Gulati | Active interferometric signal analysis in software |
US6245511B1 (en) * | 1999-02-22 | 2001-06-12 | Vialogy Corp | Method and apparatus for exponentially convergent therapy effectiveness monitoring using DNA microarray based viral load measurements |
US6142681A (en) | 1999-02-22 | 2000-11-07 | Vialogy Corporation | Method and apparatus for interpreting hybridized bioelectronic DNA microarray patterns using self-scaling convergent reverberant dynamics |
WO2000052646A2 (en) * | 1999-03-03 | 2000-09-08 | Molecularware, Inc. | A method and apparatus for automation of laboratory experimentation |
US6958225B2 (en) | 1999-10-27 | 2005-10-25 | Affymetrix, Inc. | Complexity management of genomic DNA |
US20050069956A1 (en) * | 1999-11-22 | 2005-03-31 | Michael Seul | Color-encoding and in-situ interrogation of matrix-coupled chemical compounds |
EP1107184B1 (en) * | 1999-12-06 | 2005-10-05 | Xerox Corporation | Method and apparatus for registering spatial information |
US6880755B2 (en) | 1999-12-06 | 2005-04-19 | Xerox Coporation | Method and apparatus for display of spatially registered information using embedded data |
US6935562B2 (en) | 1999-12-06 | 2005-08-30 | Xerox Corporation | Operations on images having glyph carpets |
ES2259666T3 (en) | 2000-06-21 | 2006-10-16 | Bioarray Solutions Ltd | MOLECULAR ANALYSIS OF MULTIPLE ANALYTICS USING SERIES OF RANDOM PARTICLES WITH APPLICATION SPECIFICITY. |
US9709559B2 (en) | 2000-06-21 | 2017-07-18 | Bioarray Solutions, Ltd. | Multianalyte molecular analysis using application-specific random particle arrays |
US7062092B2 (en) | 2000-08-22 | 2006-06-13 | Affymetrix, Inc. | System, method, and computer software product for gain adjustment in biological microarray scanner |
AU3511802A (en) | 2000-08-22 | 2002-05-06 | Affymetrix, Inc. | System method, and computer software product for controlling biological microarray scanner |
US6965704B2 (en) * | 2000-08-22 | 2005-11-15 | Affymetrix, Inc. | System, method, and computer software product for grid alignment of multiple scanned images |
US20030045005A1 (en) * | 2000-10-17 | 2003-03-06 | Michael Seul | Light-controlled electrokinetic assembly of particles near surfaces |
US7130458B2 (en) * | 2000-10-24 | 2006-10-31 | Affymetrix, Inc. | Computer software system, method, and product for scanned image alignment |
US6829376B2 (en) | 2000-10-24 | 2004-12-07 | Affymetrix, Inc. | Computer software system, method, and product for scanned image alignment |
US7050087B2 (en) * | 2000-12-06 | 2006-05-23 | Bioview Ltd. | Data acquisition and display system and method |
US20020183936A1 (en) * | 2001-01-24 | 2002-12-05 | Affymetrix, Inc. | Method, system, and computer software for providing a genomic web portal |
GB0102357D0 (en) * | 2001-01-30 | 2001-03-14 | Randox Lab Ltd | Imaging method |
US7262063B2 (en) | 2001-06-21 | 2007-08-28 | Bio Array Solutions, Ltd. | Directed assembly of functional heterostructures |
US20030068621A1 (en) * | 2001-10-04 | 2003-04-10 | Jonathan Briggs | Method and device for producing oligonucleotide arrays |
US20030087289A1 (en) * | 2001-10-12 | 2003-05-08 | Harry Zuzan | Image analysis of high-density synthetic DNA microarrays |
WO2003033128A2 (en) * | 2001-10-12 | 2003-04-24 | Duke University | Methods for image analysis of high-density synthetic dna microarrays |
CA2741049C (en) | 2001-10-15 | 2019-02-05 | Bioarray Solutions, Ltd. | Multiplexed analysis of polymorphic loci by probe elongation-mediated detection |
US20030099952A1 (en) * | 2001-11-26 | 2003-05-29 | Roland Green | Microarrays with visible pattern detection |
CN1927466A (en) * | 2001-12-19 | 2007-03-14 | 阿菲梅特里克斯公司 | Array plate and manufacturing process for array plate assembly |
KR20070061926A (en) * | 2002-02-14 | 2007-06-14 | 도꾸리쯔교세이호징 가가꾸 기쥬쯔 신꼬 기꼬 | Mouse spermatogenesis genes, human male sterility-associated genes and diagnostic system using the same |
WO2003069333A1 (en) | 2002-02-14 | 2003-08-21 | Illumina, Inc. | Automated information processing in randomly ordered arrays |
US20040006431A1 (en) * | 2002-03-21 | 2004-01-08 | Affymetrix, Inc., A Corporation Organized Under The Laws Of Delaware | System, method and computer software product for grid placement, alignment and analysis of images of biological probe arrays |
AU2003245269A1 (en) * | 2002-05-03 | 2003-11-17 | Vialogy Corporation | System and method for characterizing microarray output data |
US7504215B2 (en) | 2002-07-12 | 2009-03-17 | Affymetrix, Inc. | Nucleic acid labeling methods |
AU2003270898A1 (en) * | 2002-09-27 | 2004-04-19 | Nimblegen Systems, Inc. | Microarray with hydrophobic barriers |
US20040110212A1 (en) * | 2002-09-30 | 2004-06-10 | Mccormick Mark | Microarrays with visual alignment marks |
US7526114B2 (en) | 2002-11-15 | 2009-04-28 | Bioarray Solutions Ltd. | Analysis, secure access to, and transmission of array images |
US20040224332A1 (en) * | 2003-01-29 | 2004-11-11 | Affymetrix, Inc. | System and method for calibration and focusing a scanner instrument using elements associated with a biological probe array |
FR2854240B1 (en) * | 2003-04-23 | 2006-08-18 | Commissariat Energie Atomique | BIOPUCE WITH INDEPENDENT RECOGNITION FIELDS AND OPTICAL FORMAT AND ITS FLOATING READING |
WO2005000098A2 (en) | 2003-06-10 | 2005-01-06 | The Trustees Of Boston University | Detection methods for disorders of the lung |
US20040259100A1 (en) | 2003-06-20 | 2004-12-23 | Illumina, Inc. | Methods and compositions for whole genome amplification and genotyping |
US7558419B1 (en) | 2003-08-14 | 2009-07-07 | Brion Technologies, Inc. | System and method for detecting integrated circuit pattern defects |
EP1664762A4 (en) | 2003-09-03 | 2008-08-13 | Us Gov Health & Human Serv | Methods for identifying, diagnosing, and predicting survival of lymphomas |
US8131475B2 (en) | 2003-09-03 | 2012-03-06 | The United States Of America As Represented By The Secretary, Department Of Health And Human Services | Methods for identifying, diagnosing, and predicting survival of lymphomas |
WO2005029705A2 (en) | 2003-09-18 | 2005-03-31 | Bioarray Solutions, Ltd. | Number coding for identification of subtypes of coded types of solid phase carriers |
ES2375962T3 (en) | 2003-09-22 | 2012-03-07 | Bioarray Solutions Ltd | IMMOBILIZED SURFACE POLYELECTROLYTE WITH MULTIPLE FUNCTIONAL GROUPS ABLE TO JOIN COVALENTLY TO BIOMOLECULES. |
US7003758B2 (en) | 2003-10-07 | 2006-02-21 | Brion Technologies, Inc. | System and method for lithography simulation |
CA2899287A1 (en) | 2003-10-28 | 2005-05-12 | Bioarray Solutions Ltd. | Optimization of gene expression analysis using immobilized capture probes |
AU2004287069B2 (en) | 2003-10-29 | 2009-07-16 | Bioarray Solutions, Ltd. | Multiplexed nucleic acid analysis by fragmentation of double-stranded DNA |
US6996476B2 (en) * | 2003-11-07 | 2006-02-07 | University Of North Carolina At Charlotte | Methods and systems for gene expression array analysis |
EP1709198B1 (en) | 2003-11-26 | 2013-08-14 | AdvanDx, Inc. | Peptide nucleic acid probes for analysis of certain staphylococcus species |
EP1564306B1 (en) | 2004-02-17 | 2013-08-07 | Affymetrix, Inc. | Methods for fragmenting and labeling DNA |
US20050266432A1 (en) * | 2004-02-26 | 2005-12-01 | Illumina, Inc. | Haplotype markers for diagnosing susceptibility to immunological conditions |
US8065089B1 (en) | 2004-03-30 | 2011-11-22 | University Of North Carolina At Charlotte | Methods and systems for analysis of dynamic biological pathways |
US7848889B2 (en) | 2004-08-02 | 2010-12-07 | Bioarray Solutions, Ltd. | Automated analysis of multiplexed probe-target interaction patterns: pattern matching and allele identification |
US8484000B2 (en) * | 2004-09-02 | 2013-07-09 | Vialogy Llc | Detecting events of interest using quantum resonance interferometry |
US20060073506A1 (en) | 2004-09-17 | 2006-04-06 | Affymetrix, Inc. | Methods for identifying biological samples |
US20060073511A1 (en) | 2004-10-05 | 2006-04-06 | Affymetrix, Inc. | Methods for amplifying and analyzing nucleic acids |
CA2524964A1 (en) | 2004-10-29 | 2006-04-29 | Affymetrix, Inc. | Automated method of manufacturing polymer arrays |
US7682782B2 (en) | 2004-10-29 | 2010-03-23 | Affymetrix, Inc. | System, method, and product for multiple wavelength detection using single source excitation |
US7647186B2 (en) * | 2004-12-07 | 2010-01-12 | Illumina, Inc. | Oligonucleotide ordering system |
KR101138864B1 (en) * | 2005-03-08 | 2012-05-14 | 삼성전자주식회사 | Method for designing primer and probe set, primer and probe set designed by the method, kit comprising the set, computer readable medium recorded thereon a program to execute the method, and method for identifying target sequence using the set |
US20100035244A1 (en) | 2005-04-14 | 2010-02-11 | The Trustees Of Boston University | Diagnostic for lung disorders using class prediction |
US8486629B2 (en) | 2005-06-01 | 2013-07-16 | Bioarray Solutions, Ltd. | Creation of functionalized microparticle libraries by oligonucleotide ligation or elongation |
CA2611671C (en) | 2005-06-15 | 2013-10-08 | Callida Genomics, Inc. | Single molecule arrays for genetic and chemical analysis |
CN102621053B (en) | 2005-09-21 | 2015-05-06 | 卢米尼克斯股份有限公司 | Methods and systems for image data processing |
US7329860B2 (en) | 2005-11-23 | 2008-02-12 | Illumina, Inc. | Confocal imaging methods and apparatus |
US7634363B2 (en) | 2005-12-07 | 2009-12-15 | Affymetrix, Inc. | Methods for high throughput genotyping |
US20070161031A1 (en) * | 2005-12-16 | 2007-07-12 | The Board Of Trustees Of The Leland Stanford Junior University | Functional arrays for high throughput characterization of gene expression regulatory elements |
US20070154923A1 (en) * | 2005-12-29 | 2007-07-05 | Affymetrix, Inc. | Method for Gridding and Quality Control of Polymer Arrays |
US8055098B2 (en) | 2006-01-27 | 2011-11-08 | Affymetrix, Inc. | System, method, and product for imaging probe arrays with small feature sizes |
US9445025B2 (en) | 2006-01-27 | 2016-09-13 | Affymetrix, Inc. | System, method, and product for imaging probe arrays with small feature sizes |
US20090061454A1 (en) | 2006-03-09 | 2009-03-05 | Brody Jerome S | Diagnostic and prognostic methods for lung disorders using gene expression profiles from nose epithelial cells |
US7914988B1 (en) | 2006-03-31 | 2011-03-29 | Illumina, Inc. | Gene expression profiles to predict relapse of prostate cancer |
JP4431549B2 (en) * | 2006-05-31 | 2010-03-17 | 株式会社日立ハイテクノロジーズ | Fluorescence analyzer |
US8009889B2 (en) * | 2006-06-27 | 2011-08-30 | Affymetrix, Inc. | Feature intensity reconstruction of biological probe array |
CA2660286A1 (en) | 2006-08-09 | 2008-02-21 | Homestead Clinical Corporation | Organ-specific proteins and methods of their use |
US9845494B2 (en) | 2006-10-18 | 2017-12-19 | Affymetrix, Inc. | Enzymatic methods for genotyping on arrays |
JP2010508815A (en) | 2006-11-02 | 2010-03-25 | イエール・ユニバーシテイ | Evaluation of oocyte receptivity |
US20080242560A1 (en) * | 2006-11-21 | 2008-10-02 | Gunderson Kevin L | Methods for generating amplified nucleic acid arrays |
US8293684B2 (en) * | 2006-11-29 | 2012-10-23 | Exiqon | Locked nucleic acid reagents for labelling nucleic acids |
EP1956552B1 (en) * | 2007-02-09 | 2011-06-08 | Agfa-Gevaert | Visual enhancement of interval changes using a temporal subtraction technique |
DE602007002048D1 (en) * | 2007-02-09 | 2009-10-01 | Agfa Gevaert | Visual highlighting of interval changes using a time subtraction technique |
DE602007002693D1 (en) * | 2007-02-09 | 2009-11-19 | Agfa Gevaert | Visual highlighting of interval changes using a time subtraction technique |
WO2008112127A2 (en) * | 2007-03-08 | 2008-09-18 | Switchgear Genomics | Functional arrays for high throughput characterization of regulatory elements in untranslated regions of genes |
US20080241831A1 (en) * | 2007-03-28 | 2008-10-02 | Jian-Bing Fan | Methods for detecting small RNA species |
CA2683559C (en) | 2007-04-13 | 2019-09-24 | Dana Farber Cancer Institute, Inc. | Methods for treating cancer resistant to erbb therapeutics |
US8200440B2 (en) | 2007-05-18 | 2012-06-12 | Affymetrix, Inc. | System, method, and computer software product for genotype determination using probe array data |
EP2245197B1 (en) * | 2008-02-07 | 2016-10-12 | Whitespace Enterprise Corporation | Improvements in and relating to analysis |
US9012370B2 (en) * | 2008-03-11 | 2015-04-21 | National Cancer Center | Method for measuring chromosome, gene or specific nucleotide sequence copy numbers using SNP array |
US8039817B2 (en) | 2008-05-05 | 2011-10-18 | Illumina, Inc. | Compensator for multiple surface imaging |
EP2294214A2 (en) * | 2008-05-07 | 2011-03-16 | Illumina, Inc. | Compositions and methods for providing substances to and from an array |
EP2294420B8 (en) | 2008-06-06 | 2015-10-21 | The United States Of America, As Represented By The Secretary, Dept. Of Health And Human Services | Survival predictor for diffuse large B cell lymphoma |
US20100087325A1 (en) * | 2008-10-07 | 2010-04-08 | Illumina, Inc. | Biological sample temperature control system and method |
EP2340314B8 (en) | 2008-10-22 | 2015-02-18 | Illumina, Inc. | Preservation of information related to genomic dna methylation |
JP5798037B2 (en) | 2008-11-06 | 2015-10-21 | ユニバーシティ オブ マイアミ | Role of soluble uPAR in the pathogenesis of proteinuria |
BRPI1006075A2 (en) | 2009-01-07 | 2016-04-19 | Myriad Genetics Inc | cancer biomarkers |
US20100221726A1 (en) * | 2009-02-09 | 2010-09-02 | Frederic Zenhausern | Relating to devices |
US20100204057A1 (en) * | 2009-02-10 | 2010-08-12 | Samsung Electronics Co., Ltd. | Substrate for microarray, method of manufacturing microarray using the same and method of obtaining light data from microarray |
JP2012517238A (en) | 2009-02-11 | 2012-08-02 | カリス エムピーアイ インコーポレイテッド | Molecular profiling of tumors |
US9767342B2 (en) | 2009-05-22 | 2017-09-19 | Affymetrix, Inc. | Methods and devices for reading microarrays |
US10174368B2 (en) | 2009-09-10 | 2019-01-08 | Centrillion Technology Holdings Corporation | Methods and systems for sequencing long nucleic acids |
WO2011032040A1 (en) | 2009-09-10 | 2011-03-17 | Centrillion Technology Holding Corporation | Methods of targeted sequencing |
US8815779B2 (en) * | 2009-09-16 | 2014-08-26 | SwitchGear Genomics, Inc. | Transcription biomarkers of biological responses and methods |
EP2494077A4 (en) | 2009-10-27 | 2013-08-21 | Caris Mpi Inc | Molecular profiling for personalized medicine |
US20110201008A1 (en) * | 2009-12-01 | 2011-08-18 | University Of Miami | Assays, methods and kits for measuring response to therapy and predicting clinical outcome in patients with b-cell lymphoma |
US8501122B2 (en) | 2009-12-08 | 2013-08-06 | Affymetrix, Inc. | Manufacturing and processing polymer arrays |
US8835358B2 (en) | 2009-12-15 | 2014-09-16 | Cellular Research, Inc. | Digital counting of individual molecules by stochastic attachment of diverse labels |
US9798855B2 (en) | 2010-01-07 | 2017-10-24 | Affymetrix, Inc. | Differential filtering of genetic data |
WO2011091435A2 (en) | 2010-01-25 | 2011-07-28 | Mount Sinai School Of Medicine | Methods of treating liver disease |
WO2011093939A1 (en) | 2010-02-01 | 2011-08-04 | Illumina, Inc. | Focusing methods and optical systems and assemblies using the same |
WO2011112465A1 (en) | 2010-03-06 | 2011-09-15 | Illumina, Inc. | Systems, methods, and apparatuses for detecting optical signals from a sample |
EP2563380B1 (en) | 2010-04-26 | 2018-05-30 | aTyr Pharma, Inc. | Innovative discovery of therapeutic, diagnostic, and antibody compositions related to protein fragments of cysteinyl-trna synthetase |
AU2011248614B2 (en) | 2010-04-27 | 2017-02-16 | Pangu Biopharma Limited | Innovative discovery of therapeutic, diagnostic, and antibody compositions related to protein fragments of isoleucyl tRNA synthetases |
US8993723B2 (en) | 2010-04-28 | 2015-03-31 | Atyr Pharma, Inc. | Innovative discovery of therapeutic, diagnostic, and antibody compositions related to protein fragments of alanyl-tRNA synthetases |
CA2797374C (en) | 2010-04-29 | 2021-02-16 | Pangu Biopharma Limited | Innovative discovery of therapeutic, diagnostic, and antibody compositions related to protein fragments of asparaginyl trna synthetases |
EP2563383B1 (en) | 2010-04-29 | 2017-03-01 | Atyr Pharma, Inc. | Innovative discovery of therapeutic, diagnostic, and antibody compositions related to protein fragments of valyl trna synthetases |
WO2011139986A2 (en) | 2010-05-03 | 2011-11-10 | Atyr Pharma, Inc. | Innovative discovery of therapeutic, diagnostic, and antibody compositions related to protein fragments of arginyl-trna synthetases |
CN103140233B (en) | 2010-05-03 | 2017-04-05 | Atyr 医药公司 | Treatment, diagnosis and the discovery of antibody compositions related to the protein fragments of methionyl-tRNA synthetase |
ES2623805T3 (en) | 2010-05-03 | 2017-07-12 | Atyr Pharma, Inc. | Innovative discovery of therapeutic, diagnostic and antibody compositions related to phenylalanyl-alpha-tRNA synthetase protein fragments |
JP6008844B2 (en) | 2010-05-04 | 2016-10-19 | エータイアー ファーマ, インコーポレイテッド | Innovative discovery of therapeutic, diagnostic and antibody compositions related to protein fragments of the p38 MULTI-tRNA synthetase complex |
AU2011252990B2 (en) | 2010-05-14 | 2017-04-20 | Pangu Biopharma Limited | Innovative discovery of therapeutic, diagnostic, and antibody compositions related to protein fragments of phenylalanyl-beta-tRNA synthetases |
EP2575856B1 (en) | 2010-05-27 | 2017-08-16 | aTyr Pharma, Inc. | Innovative discovery of therapeutic, diagnostic, and antibody compositions related to protein fragments of glutaminyl-trna synthetases |
WO2011153277A2 (en) | 2010-06-01 | 2011-12-08 | Atyr Pharma, Inc. | Innovative discovery of therapeutic, diagnostic, and antibody compositions related to protein fragments of lysyl-trna synthetases |
WO2011159942A1 (en) | 2010-06-18 | 2011-12-22 | Illumina, Inc. | Conformational probes and methods for sequencing nucleic acids |
CA2804391A1 (en) | 2010-07-07 | 2012-01-12 | Myriad Genetics, Inc. | Gene signatures for cancer prognosis |
WO2012021247A2 (en) | 2010-07-12 | 2012-02-16 | Atyr Pharma, Inc. | Innovative discovery of therapeutic, diagnostic, and antibody compositions related to protein fragments of glycyl-trna synthetases |
US8700338B2 (en) | 2011-01-25 | 2014-04-15 | Ariosa Diagnosis, Inc. | Risk calculation for evaluation of fetal aneuploidy |
US11203786B2 (en) | 2010-08-06 | 2021-12-21 | Ariosa Diagnostics, Inc. | Detection of target nucleic acids using hybridization |
US20140342940A1 (en) | 2011-01-25 | 2014-11-20 | Ariosa Diagnostics, Inc. | Detection of Target Nucleic Acids using Hybridization |
US10167508B2 (en) | 2010-08-06 | 2019-01-01 | Ariosa Diagnostics, Inc. | Detection of genetic abnormalities |
US11031095B2 (en) | 2010-08-06 | 2021-06-08 | Ariosa Diagnostics, Inc. | Assay systems for determination of fetal copy number variation |
US10533223B2 (en) | 2010-08-06 | 2020-01-14 | Ariosa Diagnostics, Inc. | Detection of target nucleic acids using hybridization |
US20120034603A1 (en) | 2010-08-06 | 2012-02-09 | Tandem Diagnostics, Inc. | Ligation-based detection of genetic variants |
US20130261003A1 (en) | 2010-08-06 | 2013-10-03 | Ariosa Diagnostics, In. | Ligation-based detection of genetic variants |
US20130040375A1 (en) | 2011-08-08 | 2013-02-14 | Tandem Diagnotics, Inc. | Assay systems for genetic analysis |
AU2011293294B2 (en) | 2010-08-25 | 2016-03-24 | Pangu Biopharma Limited | Innovative discovery of therapeutic, diagnostic, and antibody compositions related to protein fragments of Tyrosyl-tRNA synthetases |
US8759038B2 (en) | 2010-09-29 | 2014-06-24 | Illumina Cambridge Limited | Compositions and methods for sequencing nucleic acids |
WO2012055929A1 (en) | 2010-10-26 | 2012-05-03 | Illumina, Inc. | Sequencing methods |
US8951781B2 (en) | 2011-01-10 | 2015-02-10 | Illumina, Inc. | Systems, methods, and apparatuses to image a sample for biological or chemical analysis |
US11270781B2 (en) | 2011-01-25 | 2022-03-08 | Ariosa Diagnostics, Inc. | Statistical analysis for non-invasive sex chromosome aneuploidy determination |
US8756020B2 (en) | 2011-01-25 | 2014-06-17 | Ariosa Diagnostics, Inc. | Enhanced risk probabilities using biomolecule estimations |
US10131947B2 (en) | 2011-01-25 | 2018-11-20 | Ariosa Diagnostics, Inc. | Noninvasive detection of fetal aneuploidy in egg donor pregnancies |
US20120190020A1 (en) | 2011-01-25 | 2012-07-26 | Aria Diagnostics, Inc. | Detection of genetic abnormalities |
US9994897B2 (en) | 2013-03-08 | 2018-06-12 | Ariosa Diagnostics, Inc. | Non-invasive fetal sex determination |
CN103384832B (en) | 2011-02-24 | 2016-06-29 | 希尔氏宠物营养品公司 | For diagnosing and treat compositions and the method for renal dysfunction in felid |
US20120219950A1 (en) | 2011-02-28 | 2012-08-30 | Arnold Oliphant | Assay systems for detection of aneuploidy and sex determination |
US20120252682A1 (en) | 2011-04-01 | 2012-10-04 | Maples Corporate Services Limited | Methods and systems for sequencing nucleic acids |
WO2012170936A2 (en) | 2011-06-09 | 2012-12-13 | Illumina, Inc. | Patterned flow-cells useful for nucleic acid analysis |
BR112013032354A2 (en) | 2011-06-15 | 2017-01-03 | Hills Pet Nutrition Inc | COMPOSITIONS AND METHODS FOR DIAGNOSIS AND MONITORING HYPERTHYROIDISM IN A FELINE |
US8712697B2 (en) | 2011-09-07 | 2014-04-29 | Ariosa Diagnostics, Inc. | Determination of copy number variations using binomial probability calculations |
CN105894515B (en) | 2011-10-18 | 2019-03-01 | 卢米尼克斯股份有限公司 | Method and system for image real time transfer |
CA3003082C (en) | 2011-10-28 | 2020-12-15 | Illumina, Inc. | Microarray fabrication system and method |
WO2013095935A1 (en) | 2011-12-19 | 2013-06-27 | Hill's Pet Nutrition, Inc. | Compositions and methods for diagnosing and treating hyperthyroidism in companion animals |
EP2807271B1 (en) | 2012-01-24 | 2018-08-22 | CD Diagnostics, Inc. | System for detecting infection in synovial fluid |
US20130196880A1 (en) | 2012-01-27 | 2013-08-01 | Ventana Medical Systems, Inc. | Patterned devices and methods for detecting analytes |
EP2814514B1 (en) | 2012-02-16 | 2017-09-13 | Atyr Pharma, Inc. | Histidyl-trna synthetases for treating autoimmune and inflammatory diseases |
US10202628B2 (en) | 2012-02-17 | 2019-02-12 | President And Fellows Of Harvard College | Assembly of nucleic acid sequences in emulsions |
SG11201405274WA (en) | 2012-02-27 | 2014-10-30 | Cellular Res Inc | Compositions and kits for molecular counting |
ES2776673T3 (en) | 2012-02-27 | 2020-07-31 | Univ North Carolina Chapel Hill | Methods and uses for molecular tags |
US10289800B2 (en) | 2012-05-21 | 2019-05-14 | Ariosa Diagnostics, Inc. | Processes for calculating phased fetal genomic sequences |
CA2878280A1 (en) | 2012-07-19 | 2014-01-23 | Ariosa Diagnostics, Inc. | Multiplexed sequential ligation-based detection of genetic variants |
CA2881823C (en) | 2012-08-20 | 2019-06-11 | Illumina, Inc. | Method and system for fluorescence lifetime based sequencing |
ES2938766T3 (en) | 2012-11-16 | 2023-04-14 | Myriad Genetics Inc | Gene signatures for cancer prognosis |
WO2014085434A1 (en) | 2012-11-27 | 2014-06-05 | Pontificia Universidad Catolica De Chile | Compositions and methods for diagnosing thyroid tumors |
US9146248B2 (en) | 2013-03-14 | 2015-09-29 | Intelligent Bio-Systems, Inc. | Apparatus and methods for purging flow cells in nucleic acid sequencing instruments |
US9591268B2 (en) | 2013-03-15 | 2017-03-07 | Qiagen Waltham, Inc. | Flow cell alignment methods and systems |
EP4043580A1 (en) | 2013-03-15 | 2022-08-17 | Myriad myPath, LLC | Genes and gene signatures for diagnosis and treatment of melanoma |
GB2525568B (en) | 2013-03-15 | 2020-10-14 | Abvitro Llc | Single cell barcoding for antibody discovery |
EP3633048B1 (en) | 2013-03-27 | 2022-10-12 | Alan Handyside | Assessment of risk of aneuploidy |
EP3663414B1 (en) | 2013-06-13 | 2023-11-22 | Roche Diagnostics GmbH | Statistical analysis for non-invasive y chromosome aneuploidy determination |
SG10201806890VA (en) | 2013-08-28 | 2018-09-27 | Cellular Res Inc | Massively parallel single cell analysis |
US9352315B2 (en) | 2013-09-27 | 2016-05-31 | Taiwan Semiconductor Manufacturing Company, Ltd. | Method to produce chemical pattern in micro-fluidic structure |
WO2015069790A1 (en) | 2013-11-06 | 2015-05-14 | The United States Of America, As Represented By The Secretary, Department Of Health And Human Services | Method for subtyping lymphoma types by means expression profiling |
WO2015109234A1 (en) | 2014-01-16 | 2015-07-23 | Illumina, Inc. | Gene expression panel for prognosis of prostate cancer recurrence |
JP6596442B2 (en) | 2014-04-22 | 2019-10-23 | エンバイロロジックス インコーポレイテッド | Compositions and methods for enhancing and / or predicting DNA amplification |
EP3143160B1 (en) | 2014-05-13 | 2019-11-06 | Myriad Genetics, Inc. | Gene signatures for cancer prognosis |
WO2016003810A1 (en) | 2014-07-02 | 2016-01-07 | Myriad Genetics, Inc. | Genes and gene signatures for diagnosis and treatment of melanoma |
AU2015318011B2 (en) | 2014-09-15 | 2020-07-23 | Abvitro Llc | High-throughput nucleotide library sequencing |
BR112017008082A2 (en) | 2014-10-20 | 2017-12-26 | Envirologix Inc | compositions and methods for detecting an rna virus |
BR112017016350A2 (en) | 2015-01-30 | 2018-03-27 | Envirologix Inc. | substrate molecule |
US10801065B2 (en) | 2015-02-10 | 2020-10-13 | Dana-Farber Cancer Institute, Inc. | Methods of determining levels of exposure to radiation and uses thereof |
WO2016154193A1 (en) | 2015-03-24 | 2016-09-29 | Illumina, Inc. | Methods, carrier assemblies, and systems for imaging samples for biological or chemical analysis |
BR112017025587B1 (en) | 2015-05-29 | 2022-09-27 | Illumina, Inc | SAMPLE CARRIER AND ASSAY SYSTEM TO CONDUCT DESIGNATED REACTIONS |
CN108136051A (en) | 2015-08-04 | 2018-06-08 | Cd诊断股份有限公司 | The method for detecting bad local organization reaction (ALTR) necrosis |
EP3130681B1 (en) | 2015-08-13 | 2019-11-13 | Centrillion Technology Holdings Corporation | Methods for synchronizing nucleic acid molecules |
EP3338096B1 (en) | 2015-08-24 | 2024-03-06 | Illumina, Inc. | In-line pressure accumulator and flow-control system for biological or chemical assays |
WO2018057051A1 (en) | 2016-09-24 | 2018-03-29 | Abvitro Llc | Affinity-oligonucleotide conjugates and uses thereof |
US11156611B2 (en) | 2015-09-24 | 2021-10-26 | Abvitro Llc | Single cell characterization using affinity-oligonucleotide conjugates and vessel barcoded polynucleotides |
EP3353550A1 (en) | 2015-09-25 | 2018-08-01 | AbVitro LLC | High throughput process for t cell receptor target identification of natively-paired t cell receptor sequences |
EP3362580B1 (en) | 2015-10-18 | 2021-02-17 | Affymetrix, Inc. | Multiallelic genotyping of single nucleotide polymorphisms and indels |
EP3377650A1 (en) | 2015-11-19 | 2018-09-26 | Susanne Wagner | Signatures for predicting cancer immune therapy response |
CA3010240A1 (en) | 2016-01-06 | 2017-07-13 | Alexander Gutin | Genes and gene signatures for diagnosis and treatment of melanoma |
WO2017184861A1 (en) | 2016-04-20 | 2017-10-26 | The United States Of America, As Represented By The Secretary, Department Of Health And Human Services | Evaluation of mantle cell lymphoma and methods related thereto |
WO2017193062A1 (en) | 2016-05-06 | 2017-11-09 | Myriad Genetics, Inc. | Gene signatures for renal cancer prognosis |
EP3472354A4 (en) | 2016-06-17 | 2020-01-01 | California Institute of Technology | Nucleic acid reactions and related methods and compositions |
WO2018064116A1 (en) | 2016-09-28 | 2018-04-05 | Illumina, Inc. | Methods and systems for data compression |
WO2018213803A1 (en) | 2017-05-19 | 2018-11-22 | Neon Therapeutics, Inc. | Immunogenic neoantigen identification |
WO2018231589A1 (en) | 2017-06-14 | 2018-12-20 | The United States Of America, As Represented By The Secretary, Department Of Health And Human Services | Method for determining lymphoma type |
CN111656179B (en) | 2017-11-13 | 2023-11-03 | 豪夫迈·罗氏有限公司 | Device for sample analysis using epitope electrophoresis |
EP3807648A2 (en) | 2018-06-18 | 2021-04-21 | Igenomix S.L. | Methods for assessing endometrial transformation |
WO2020076897A1 (en) | 2018-10-09 | 2020-04-16 | Genecentric Therapeutics, Inc. | Detecting cancer cell of origin |
EP3864403A1 (en) | 2018-10-12 | 2021-08-18 | F. Hoffmann-La Roche AG | Detection methods for epitachophoresis workflow automation |
WO2020113237A1 (en) | 2018-11-30 | 2020-06-04 | Caris Mpi, Inc. | Next-generation molecular profiling |
JP2022529294A (en) | 2019-04-17 | 2022-06-20 | アイジェノミクス、ソシエダッド、リミターダ | Improved methods for early diagnosis of uterine leiomyoma and leiomyoma |
WO2020229437A1 (en) | 2019-05-14 | 2020-11-19 | F. Hoffmann-La Roche Ag | Devices and methods for sample analysis |
EP4069865A4 (en) | 2019-12-02 | 2023-12-20 | Caris MPI, Inc. | Pan-cancer platinum response predictor |
WO2023122363A1 (en) | 2021-12-23 | 2023-06-29 | Illumina Software, Inc. | Dynamic graphical status summaries for nucelotide sequencing |
US20230215515A1 (en) | 2021-12-23 | 2023-07-06 | Illumina Software, Inc. | Facilitating secure execution of external workflows for genomic sequencing diagnostics |
WO2023129764A1 (en) | 2021-12-29 | 2023-07-06 | Illumina Software, Inc. | Automatically switching variant analysis model versions for genomic analysis applications |
Citations (72)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US3216313A (en) * | 1961-06-23 | 1965-11-09 | Bausch & Lomb | Monochromator of the type having a plane grating therein |
US3385160A (en) * | 1964-02-04 | 1968-05-28 | Nat Res Dev | Scanning spectrophotometer with pulse referencing |
US3632212A (en) * | 1970-06-01 | 1972-01-04 | Honeywell Inc | Gas temperature measurement system employing a laser |
US3798449A (en) * | 1972-05-23 | 1974-03-19 | G Reinheimer | Automatic microscope focussing device |
US3802966A (en) * | 1969-08-22 | 1974-04-09 | Ethyl Corp | Apparatus for delivering a fluid suspension to a forming unit clear reactor power plant |
US3984171A (en) * | 1974-08-21 | 1976-10-05 | Image Information Inc. | Linear scan system |
US4016855A (en) * | 1974-09-04 | 1977-04-12 | Hitachi, Ltd. | Grinding method |
US4070111A (en) * | 1976-06-10 | 1978-01-24 | Nicolas James Harrick | Rapid scan spectrophotometer |
US4176925A (en) * | 1978-06-07 | 1979-12-04 | Gte Laboratories Incorporated | Laser scanner for photolithography of slotted mask color cathode ray tubes |
US4180739A (en) * | 1977-12-23 | 1979-12-25 | Varian Associates, Inc. | Thermostatable flow cell for fluorescence measurements |
US4204929A (en) * | 1978-04-18 | 1980-05-27 | University Patents, Inc. | Isoelectric focusing method |
US4342905A (en) * | 1979-08-31 | 1982-08-03 | Nippon Kogaku K.K. | Automatic focusing device of a microscope |
US4417260A (en) * | 1981-07-23 | 1983-11-22 | Fuji Photo Film Co., Ltd. | Image scanning system |
US4448534A (en) * | 1978-03-30 | 1984-05-15 | American Hospital Corporation | Antibiotic susceptibility testing |
US4537861A (en) * | 1983-02-03 | 1985-08-27 | Elings Virgil B | Apparatus and method for homogeneous immunoassay |
US4579430A (en) * | 1982-12-11 | 1986-04-01 | Carl-Zeiss-Stiftung | Method and apparatus for forming an image of the ocular fundus |
US4580895A (en) * | 1983-10-28 | 1986-04-08 | Dynatech Laboratories, Incorporated | Sample-scanning photometer |
US4626684A (en) * | 1983-07-13 | 1986-12-02 | Landa Isaac J | Rapid and automatic fluorescence immunoassay analyzer for multiple micro-samples |
US4708494A (en) * | 1982-08-06 | 1987-11-24 | Marcos Kleinerman | Methods and devices for the optical measurement of temperature with luminescent materials |
US4772125A (en) * | 1985-06-19 | 1988-09-20 | Hitachi, Ltd. | Apparatus and method for inspecting soldered portions |
US4786170A (en) * | 1985-07-26 | 1988-11-22 | Jenoptik Jena G.M.B.H. | Apparatus for the graphic representation and analysis of fluorescence signals |
US4810869A (en) * | 1986-12-27 | 1989-03-07 | Hitachi, Ltd. | Automatic focusing control method for microscope |
US4844617A (en) * | 1988-01-20 | 1989-07-04 | Tencor Instruments | Confocal measuring microscope with automatic focusing |
US4878971A (en) * | 1987-01-28 | 1989-11-07 | Fuji Photo Film Co., Ltd. | Method of continuously assembling chemical analysis slides |
US4963498A (en) * | 1985-08-05 | 1990-10-16 | Biotrack | Capillary flow device |
US5061075A (en) * | 1989-08-07 | 1991-10-29 | Alfano Robert R | Optical method and apparatus for diagnosing human spermatozoa |
US5091652A (en) * | 1990-01-12 | 1992-02-25 | The Regents Of The University Of California | Laser excited confocal microscope fluorescence scanner and method |
US5132524A (en) * | 1990-05-21 | 1992-07-21 | Lazerdata Corporation | Multi directional laser scanner |
US5143854A (en) * | 1989-06-07 | 1992-09-01 | Affymax Technologies N.V. | Large scale photolithographic solid phase synthesis of polypeptides and receptor binding screening thereof |
US5188963A (en) * | 1989-11-17 | 1993-02-23 | Gene Tec Corporation | Device for processing biological specimens for analysis of nucleic acids |
US5192980A (en) * | 1990-06-27 | 1993-03-09 | A. E. Dixon | Apparatus and method for method for spatially- and spectrally-resolved measurements |
US5198871A (en) * | 1991-06-18 | 1993-03-30 | Southwest Research Institute | Laser-induced-fluorescence inspection of jet fuels |
US5200051A (en) * | 1988-11-14 | 1993-04-06 | I-Stat Corporation | Wholly microfabricated biosensors and process for the manufacture and use thereof |
US5214531A (en) * | 1990-06-22 | 1993-05-25 | Fanuc Ltd. | Operation control system for a scanning galvanometer |
US5235180A (en) * | 1992-03-05 | 1993-08-10 | General Scanning, Inc. | Rotary motor having an angular position transducer and galvanometer scanning system employing such motor |
US5281516A (en) * | 1988-08-02 | 1994-01-25 | Gene Tec Corporation | Temperature control apparatus and method |
US5300779A (en) * | 1985-08-05 | 1994-04-05 | Biotrack, Inc. | Capillary flow device |
US5304810A (en) * | 1990-07-18 | 1994-04-19 | Medical Research Council | Confocal scanning optical microscope |
US5304487A (en) * | 1992-05-01 | 1994-04-19 | Trustees Of The University Of Pennsylvania | Fluid handling in mesoscale analytical devices |
US5310469A (en) * | 1991-12-31 | 1994-05-10 | Abbott Laboratories | Biosensor with a membrane containing biologically active material |
US5320808A (en) * | 1988-08-02 | 1994-06-14 | Abbott Laboratories | Reaction cartridge and carousel for biological sample analyzer |
US5346672A (en) * | 1989-11-17 | 1994-09-13 | Gene Tec Corporation | Devices for containing biological specimens for thermal processing |
US5381224A (en) * | 1993-08-30 | 1995-01-10 | A. E. Dixon | Scanning laser imaging system |
US5382511A (en) * | 1988-08-02 | 1995-01-17 | Gene Tec Corporation | Method for studying nucleic acids within immobilized specimens |
US5384261A (en) * | 1991-11-22 | 1995-01-24 | Affymax Technologies N.V. | Very large scale immobilized polymer synthesis using mechanically directed flow paths |
US5424186A (en) * | 1989-06-07 | 1995-06-13 | Affymax Technologies N.V. | Very large scale immobilized polymer synthesis |
US5424841A (en) * | 1993-05-28 | 1995-06-13 | Molecular Dynamics | Apparatus for measuring spatial distribution of fluorescence on a substrate |
US5459325A (en) * | 1994-07-19 | 1995-10-17 | Molecular Dynamics, Inc. | High-speed fluorescence scanner |
US5471248A (en) * | 1992-11-13 | 1995-11-28 | National Semiconductor Corporation | System for tile coding of moving images |
US5474796A (en) * | 1991-09-04 | 1995-12-12 | Protogene Laboratories, Inc. | Method and apparatus for conducting an array of chemical reactions on a support surface |
US5494124A (en) * | 1993-10-08 | 1996-02-27 | Vortexx Group, Inc. | Negative pressure vortex nozzle |
US5497773A (en) * | 1993-03-12 | 1996-03-12 | Kabushiki Kaisha Toshiba | Nuclear magnetic resonance imaging with patient protection against nerve stimulation and image quality protection against artifacts |
US5498392A (en) * | 1992-05-01 | 1996-03-12 | Trustees Of The University Of Pennsylvania | Mesoscale polynucleotide amplification device and method |
US5527681A (en) * | 1989-06-07 | 1996-06-18 | Affymax Technologies N.V. | Immobilized molecular synthesis of systematically substituted compounds |
US5532873A (en) * | 1993-09-08 | 1996-07-02 | Dixon; Arthur E. | Scanning beam laser microscope with wide range of magnification |
US5572598A (en) * | 1991-08-22 | 1996-11-05 | Kla Instruments Corporation | Automated photomask inspection apparatus |
US5571639A (en) * | 1994-05-24 | 1996-11-05 | Affymax Technologies N.V. | Computer-aided engineering system for design of sequence arrays and lithographic masks |
US5578832A (en) * | 1994-09-02 | 1996-11-26 | Affymetrix, Inc. | Method and apparatus for imaging a sample on a device |
US5583342A (en) * | 1993-06-03 | 1996-12-10 | Hamamatsu Photonics K.K. | Laser scanning optical system and laser scanning optical apparatus |
US5585639A (en) * | 1995-07-27 | 1996-12-17 | Hewlett-Packard Company | Optical scanning apparatus |
US5604819A (en) * | 1993-03-15 | 1997-02-18 | Schlumberger Technologies Inc. | Determining offset between images of an IC |
US5631734A (en) * | 1994-02-10 | 1997-05-20 | Affymetrix, Inc. | Method and apparatus for detection of fluorescently labeled materials |
US5646411A (en) * | 1996-02-01 | 1997-07-08 | Molecular Dynamics, Inc. | Fluorescence imaging system compatible with macro and micro scanning objectives |
US5672880A (en) * | 1994-12-08 | 1997-09-30 | Molecular Dynamics, Inc. | Fluoresecence imaging system |
US5744305A (en) * | 1989-06-07 | 1998-04-28 | Affymetrix, Inc. | Arrays of materials attached to a substrate |
US5760951A (en) * | 1992-09-01 | 1998-06-02 | Arthur Edward Dixon | Apparatus and method for scanning laser imaging of macroscopic samples |
US5835620A (en) * | 1995-12-19 | 1998-11-10 | Neuromedical Systems, Inc. | Boundary mapping system and method |
US5861242A (en) * | 1993-06-25 | 1999-01-19 | Affymetrix, Inc. | Array of nucleic acid probes on biological chips for diagnosis of HIV and methods of using the same |
US5981956A (en) * | 1996-05-16 | 1999-11-09 | Affymetrix, Inc. | Systems and methods for detection of labeled materials |
US6090555A (en) * | 1997-12-11 | 2000-07-18 | Affymetrix, Inc. | Scanned image alignment systems and methods |
US6486335B1 (en) * | 1998-03-31 | 2002-11-26 | Council Of Scientific & Industrial Research (Csir) | Process for the preparation of refined hard sugarcane wax having improved qualities from press mud |
US6741344B1 (en) * | 1994-02-10 | 2004-05-25 | Affymetrix, Inc. | Method and apparatus for detection of fluorescently labeled materials |
Family Cites Families (40)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US2886241A (en) * | 1952-08-26 | 1959-05-12 | Rca Corp | Code converter |
GB8429212D0 (en) * | 1984-11-19 | 1984-12-27 | Vincent Patents Ltd | Exhaust systems for ic engines |
EP0254644A3 (en) * | 1986-07-22 | 1990-07-18 | Schlumberger Technologies, Inc. | Mask alignment and measurement of critical dimensions in integrated circuits |
US5001766A (en) * | 1988-05-16 | 1991-03-19 | At&T Bell Laboratories | Apparatus and method for skew control of document images |
US5720928A (en) * | 1988-09-15 | 1998-02-24 | New York University | Image processing and analysis of individual nucleic acid molecules |
US5800992A (en) * | 1989-06-07 | 1998-09-01 | Fodor; Stephen P.A. | Method of detecting nucleic acids |
US5124102A (en) * | 1990-12-11 | 1992-06-23 | E. I. Du Pont De Nemours And Company | Fabric useful as a concrete form liner |
US5817462A (en) * | 1995-02-21 | 1998-10-06 | Applied Spectral Imaging | Method for simultaneous detection of multiple fluorophores for in situ hybridization and multicolor chromosome painting and banding |
US5486335A (en) * | 1992-05-01 | 1996-01-23 | Trustees Of The University Of Pennsylvania | Analysis based on flow restriction |
US5487115A (en) * | 1992-05-14 | 1996-01-23 | United Parcel Service | Method and apparatus for determining the fine angular orientation of bar code symbols in two-dimensional CCD images |
JP2851023B2 (en) * | 1992-06-29 | 1999-01-27 | 株式会社鷹山 | IC tilt inspection method |
US5858659A (en) * | 1995-11-29 | 1999-01-12 | Affymetrix, Inc. | Polymorphism detection |
US6045996A (en) * | 1993-10-26 | 2000-04-04 | Affymetrix, Inc. | Hybridization assays on oligonucleotide arrays |
US6287850B1 (en) * | 1995-06-07 | 2001-09-11 | Affymetrix, Inc. | Bioarray chip reaction apparatus and its manufacture |
EP0695941B1 (en) * | 1994-06-08 | 2002-07-31 | Affymetrix, Inc. | Method and apparatus for packaging a chip |
US5886353A (en) * | 1995-04-21 | 1999-03-23 | Thermotrex Corporation | Imaging device |
US5916747A (en) * | 1995-06-30 | 1999-06-29 | Visible Genetics Inc. | Method and apparatus for alignment of signals for use in DNA based-calling |
US5733729A (en) * | 1995-09-14 | 1998-03-31 | Affymetrix, Inc. | Computer-aided probability base calling for arrays of nucleic acid probes on chips |
US5801970A (en) * | 1995-12-06 | 1998-09-01 | Martin Marietta Corporation | Model-based feature tracking system |
AU2189397A (en) * | 1996-02-08 | 1997-08-28 | Affymetrix, Inc. | Chip-based speciation and phenotypic characterization of microorganisms |
US5721435A (en) * | 1996-04-09 | 1998-02-24 | Hewlett Packard Company | Methods and apparatus for measuring optical properties of biological and chemical substances |
US5917588A (en) * | 1996-11-04 | 1999-06-29 | Kla-Tencor Corporation | Automated specimen inspection system for and method of distinguishing features or anomalies under either bright field or dark field illumination |
JP4663824B2 (en) * | 1996-12-31 | 2011-04-06 | ハイ スループット ジェノミクス インコーポレイテッド | Multiplexed molecular analyzer and method |
CA2286864A1 (en) * | 1997-01-10 | 1998-07-16 | Pioneer Hi-Bred International, Inc. | Hybridization-based genetic amplification and analysis |
US20020042048A1 (en) * | 1997-01-16 | 2002-04-11 | Radoje Drmanac | Methods and compositions for detection or quantification of nucleic acid species |
US5812272A (en) * | 1997-01-30 | 1998-09-22 | Hewlett-Packard Company | Apparatus and method with tiled light source array for integrated assay sensing |
US6122042A (en) * | 1997-02-07 | 2000-09-19 | Wunderman; Irwin | Devices and methods for optically identifying characteristics of material objects |
US6349144B1 (en) * | 1998-02-07 | 2002-02-19 | Biodiscovery, Inc. | Automated DNA array segmentation and analysis |
US6242266B1 (en) * | 1999-04-30 | 2001-06-05 | Agilent Technologies Inc. | Preparation of biopolymer arrays |
US6362832B1 (en) * | 1999-09-01 | 2002-03-26 | Packard Bioscience Company | Method and system for overlaying at least three microarray images to obtain a multicolor composite image |
US6077674A (en) * | 1999-10-27 | 2000-06-20 | Agilent Technologies Inc. | Method of producing oligonucleotide arrays with features of high purity |
US6406849B1 (en) * | 1999-10-29 | 2002-06-18 | Agilent Technologies, Inc. | Interrogating multi-featured arrays |
US7027629B2 (en) * | 1999-11-05 | 2006-04-11 | Agilent Technologies, Inc. | Method of extracting locations of nucleic acid array features |
EP1967595A3 (en) * | 2000-02-16 | 2008-12-03 | Illumina, Inc. | Parallel genotyping of multiple patient samples |
US6571005B1 (en) * | 2000-04-21 | 2003-05-27 | The Regents Of The University Of California | Feature extraction and normalization algorithms for high-density oligonucleotide gene expression array data |
US6591196B1 (en) * | 2000-06-06 | 2003-07-08 | Agilent Technologies Inc. | Method and system for extracting data from surface array deposited features |
US6599693B1 (en) * | 2000-07-31 | 2003-07-29 | Agilent Technologies Inc. | Array fabrication |
US6829376B2 (en) * | 2000-10-24 | 2004-12-07 | Affymetrix, Inc. | Computer software system, method, and product for scanned image alignment |
US20050049796A1 (en) * | 2003-09-03 | 2005-03-03 | Webb Peter G. | Methods for encoding non-biological information on microarrays |
US20050048506A1 (en) * | 2003-09-03 | 2005-03-03 | Fredrick Joseph P. | Methods for encoding non-biological information on microarrays |
-
1997
- 1997-12-23 US US08/996,737 patent/US6090555A/en not_active Expired - Lifetime
-
1998
- 1998-12-09 JP JP10377796A patent/JP2000069998A/en active Pending
- 1998-12-10 AT AT98310131T patent/ATE284066T1/en not_active IP Right Cessation
- 1998-12-10 EP EP98310131A patent/EP0923050B1/en not_active Expired - Lifetime
- 1998-12-10 CA CA002255384A patent/CA2255384A1/en not_active Abandoned
- 1998-12-10 DE DE69827913T patent/DE69827913T2/en not_active Expired - Lifetime
-
2000
- 2000-04-04 US US09/542,151 patent/US6611767B1/en not_active Expired - Lifetime
-
2003
- 2003-08-25 US US10/648,819 patent/US20050037367A9/en not_active Abandoned
-
2006
- 2006-03-03 US US11/366,515 patent/US20060258002A1/en not_active Abandoned
- 2006-03-09 US US11/372,836 patent/US20060165313A1/en not_active Abandoned
Patent Citations (79)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US3216313A (en) * | 1961-06-23 | 1965-11-09 | Bausch & Lomb | Monochromator of the type having a plane grating therein |
US3385160A (en) * | 1964-02-04 | 1968-05-28 | Nat Res Dev | Scanning spectrophotometer with pulse referencing |
US3802966A (en) * | 1969-08-22 | 1974-04-09 | Ethyl Corp | Apparatus for delivering a fluid suspension to a forming unit clear reactor power plant |
US3632212A (en) * | 1970-06-01 | 1972-01-04 | Honeywell Inc | Gas temperature measurement system employing a laser |
US3798449A (en) * | 1972-05-23 | 1974-03-19 | G Reinheimer | Automatic microscope focussing device |
US3984171A (en) * | 1974-08-21 | 1976-10-05 | Image Information Inc. | Linear scan system |
US4016855A (en) * | 1974-09-04 | 1977-04-12 | Hitachi, Ltd. | Grinding method |
US4070111A (en) * | 1976-06-10 | 1978-01-24 | Nicolas James Harrick | Rapid scan spectrophotometer |
US4180739A (en) * | 1977-12-23 | 1979-12-25 | Varian Associates, Inc. | Thermostatable flow cell for fluorescence measurements |
US4448534A (en) * | 1978-03-30 | 1984-05-15 | American Hospital Corporation | Antibiotic susceptibility testing |
US4204929A (en) * | 1978-04-18 | 1980-05-27 | University Patents, Inc. | Isoelectric focusing method |
US4176925A (en) * | 1978-06-07 | 1979-12-04 | Gte Laboratories Incorporated | Laser scanner for photolithography of slotted mask color cathode ray tubes |
US4342905A (en) * | 1979-08-31 | 1982-08-03 | Nippon Kogaku K.K. | Automatic focusing device of a microscope |
US4417260A (en) * | 1981-07-23 | 1983-11-22 | Fuji Photo Film Co., Ltd. | Image scanning system |
US4708494A (en) * | 1982-08-06 | 1987-11-24 | Marcos Kleinerman | Methods and devices for the optical measurement of temperature with luminescent materials |
US4579430A (en) * | 1982-12-11 | 1986-04-01 | Carl-Zeiss-Stiftung | Method and apparatus for forming an image of the ocular fundus |
US4537861A (en) * | 1983-02-03 | 1985-08-27 | Elings Virgil B | Apparatus and method for homogeneous immunoassay |
US4626684A (en) * | 1983-07-13 | 1986-12-02 | Landa Isaac J | Rapid and automatic fluorescence immunoassay analyzer for multiple micro-samples |
US4580895A (en) * | 1983-10-28 | 1986-04-08 | Dynatech Laboratories, Incorporated | Sample-scanning photometer |
US4772125A (en) * | 1985-06-19 | 1988-09-20 | Hitachi, Ltd. | Apparatus and method for inspecting soldered portions |
US4786170A (en) * | 1985-07-26 | 1988-11-22 | Jenoptik Jena G.M.B.H. | Apparatus for the graphic representation and analysis of fluorescence signals |
US4963498A (en) * | 1985-08-05 | 1990-10-16 | Biotrack | Capillary flow device |
US5300779A (en) * | 1985-08-05 | 1994-04-05 | Biotrack, Inc. | Capillary flow device |
US4810869A (en) * | 1986-12-27 | 1989-03-07 | Hitachi, Ltd. | Automatic focusing control method for microscope |
US4878971A (en) * | 1987-01-28 | 1989-11-07 | Fuji Photo Film Co., Ltd. | Method of continuously assembling chemical analysis slides |
US4844617A (en) * | 1988-01-20 | 1989-07-04 | Tencor Instruments | Confocal measuring microscope with automatic focusing |
US5320808A (en) * | 1988-08-02 | 1994-06-14 | Abbott Laboratories | Reaction cartridge and carousel for biological sample analyzer |
US5281516A (en) * | 1988-08-02 | 1994-01-25 | Gene Tec Corporation | Temperature control apparatus and method |
US5382511A (en) * | 1988-08-02 | 1995-01-17 | Gene Tec Corporation | Method for studying nucleic acids within immobilized specimens |
US5200051A (en) * | 1988-11-14 | 1993-04-06 | I-Stat Corporation | Wholly microfabricated biosensors and process for the manufacture and use thereof |
US5424186A (en) * | 1989-06-07 | 1995-06-13 | Affymax Technologies N.V. | Very large scale immobilized polymer synthesis |
US5405783A (en) * | 1989-06-07 | 1995-04-11 | Affymax Technologies N.V. | Large scale photolithographic solid phase synthesis of an array of polymers |
US5744305A (en) * | 1989-06-07 | 1998-04-28 | Affymetrix, Inc. | Arrays of materials attached to a substrate |
US5527681A (en) * | 1989-06-07 | 1996-06-18 | Affymax Technologies N.V. | Immobilized molecular synthesis of systematically substituted compounds |
US5143854A (en) * | 1989-06-07 | 1992-09-01 | Affymax Technologies N.V. | Large scale photolithographic solid phase synthesis of polypeptides and receptor binding screening thereof |
US5445934A (en) * | 1989-06-07 | 1995-08-29 | Affymax Technologies N.V. | Array of oligonucleotides on a solid substrate |
US5061075A (en) * | 1989-08-07 | 1991-10-29 | Alfano Robert R | Optical method and apparatus for diagnosing human spermatozoa |
US5451500A (en) * | 1989-11-17 | 1995-09-19 | Gene Tec Corporation | Device for processing biological specimens for analysis of nucleic acids |
US5436129A (en) * | 1989-11-17 | 1995-07-25 | Gene Tec Corp. | Process for specimen handling for analysis of nucleic acids |
US5346672A (en) * | 1989-11-17 | 1994-09-13 | Gene Tec Corporation | Devices for containing biological specimens for thermal processing |
US5188963A (en) * | 1989-11-17 | 1993-02-23 | Gene Tec Corporation | Device for processing biological specimens for analysis of nucleic acids |
US5091652A (en) * | 1990-01-12 | 1992-02-25 | The Regents Of The University Of California | Laser excited confocal microscope fluorescence scanner and method |
US5132524A (en) * | 1990-05-21 | 1992-07-21 | Lazerdata Corporation | Multi directional laser scanner |
US5214531A (en) * | 1990-06-22 | 1993-05-25 | Fanuc Ltd. | Operation control system for a scanning galvanometer |
US5192980A (en) * | 1990-06-27 | 1993-03-09 | A. E. Dixon | Apparatus and method for method for spatially- and spectrally-resolved measurements |
US5304810A (en) * | 1990-07-18 | 1994-04-19 | Medical Research Council | Confocal scanning optical microscope |
US5198871A (en) * | 1991-06-18 | 1993-03-30 | Southwest Research Institute | Laser-induced-fluorescence inspection of jet fuels |
US5572598A (en) * | 1991-08-22 | 1996-11-05 | Kla Instruments Corporation | Automated photomask inspection apparatus |
US5474796A (en) * | 1991-09-04 | 1995-12-12 | Protogene Laboratories, Inc. | Method and apparatus for conducting an array of chemical reactions on a support surface |
US5384261A (en) * | 1991-11-22 | 1995-01-24 | Affymax Technologies N.V. | Very large scale immobilized polymer synthesis using mechanically directed flow paths |
US5310469A (en) * | 1991-12-31 | 1994-05-10 | Abbott Laboratories | Biosensor with a membrane containing biologically active material |
US5235180A (en) * | 1992-03-05 | 1993-08-10 | General Scanning, Inc. | Rotary motor having an angular position transducer and galvanometer scanning system employing such motor |
US5498392A (en) * | 1992-05-01 | 1996-03-12 | Trustees Of The University Of Pennsylvania | Mesoscale polynucleotide amplification device and method |
US5304487A (en) * | 1992-05-01 | 1994-04-19 | Trustees Of The University Of Pennsylvania | Fluid handling in mesoscale analytical devices |
US5760951A (en) * | 1992-09-01 | 1998-06-02 | Arthur Edward Dixon | Apparatus and method for scanning laser imaging of macroscopic samples |
US5471248A (en) * | 1992-11-13 | 1995-11-28 | National Semiconductor Corporation | System for tile coding of moving images |
US5497773A (en) * | 1993-03-12 | 1996-03-12 | Kabushiki Kaisha Toshiba | Nuclear magnetic resonance imaging with patient protection against nerve stimulation and image quality protection against artifacts |
US5604819A (en) * | 1993-03-15 | 1997-02-18 | Schlumberger Technologies Inc. | Determining offset between images of an IC |
US5424841A (en) * | 1993-05-28 | 1995-06-13 | Molecular Dynamics | Apparatus for measuring spatial distribution of fluorescence on a substrate |
US5583342A (en) * | 1993-06-03 | 1996-12-10 | Hamamatsu Photonics K.K. | Laser scanning optical system and laser scanning optical apparatus |
US5861242A (en) * | 1993-06-25 | 1999-01-19 | Affymetrix, Inc. | Array of nucleic acid probes on biological chips for diagnosis of HIV and methods of using the same |
US5381224A (en) * | 1993-08-30 | 1995-01-10 | A. E. Dixon | Scanning laser imaging system |
US5532873A (en) * | 1993-09-08 | 1996-07-02 | Dixon; Arthur E. | Scanning beam laser microscope with wide range of magnification |
US5737121A (en) * | 1993-09-08 | 1998-04-07 | Dixon; Arthur E. | Real time scanning optical macroscope |
US5494124A (en) * | 1993-10-08 | 1996-02-27 | Vortexx Group, Inc. | Negative pressure vortex nozzle |
US5631734A (en) * | 1994-02-10 | 1997-05-20 | Affymetrix, Inc. | Method and apparatus for detection of fluorescently labeled materials |
US6741344B1 (en) * | 1994-02-10 | 2004-05-25 | Affymetrix, Inc. | Method and apparatus for detection of fluorescently labeled materials |
US6141096A (en) * | 1994-02-10 | 2000-10-31 | Affymetrix, Inc. | Method and apparatus for detection of fluorescently labeled materials |
US5571639A (en) * | 1994-05-24 | 1996-11-05 | Affymax Technologies N.V. | Computer-aided engineering system for design of sequence arrays and lithographic masks |
US5459325A (en) * | 1994-07-19 | 1995-10-17 | Molecular Dynamics, Inc. | High-speed fluorescence scanner |
US5578832A (en) * | 1994-09-02 | 1996-11-26 | Affymetrix, Inc. | Method and apparatus for imaging a sample on a device |
US5672880A (en) * | 1994-12-08 | 1997-09-30 | Molecular Dynamics, Inc. | Fluoresecence imaging system |
US5585639A (en) * | 1995-07-27 | 1996-12-17 | Hewlett-Packard Company | Optical scanning apparatus |
US5835620A (en) * | 1995-12-19 | 1998-11-10 | Neuromedical Systems, Inc. | Boundary mapping system and method |
US5646411A (en) * | 1996-02-01 | 1997-07-08 | Molecular Dynamics, Inc. | Fluorescence imaging system compatible with macro and micro scanning objectives |
US5981956A (en) * | 1996-05-16 | 1999-11-09 | Affymetrix, Inc. | Systems and methods for detection of labeled materials |
US6090555A (en) * | 1997-12-11 | 2000-07-18 | Affymetrix, Inc. | Scanned image alignment systems and methods |
US6611767B1 (en) * | 1997-12-11 | 2003-08-26 | Affymetrix, Inc. | Scanned image alignment systems and methods |
US6486335B1 (en) * | 1998-03-31 | 2002-11-26 | Council Of Scientific & Industrial Research (Csir) | Process for the preparation of refined hard sugarcane wax having improved qualities from press mud |
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US8131680B2 (en) | 2005-11-28 | 2012-03-06 | Commvault Systems, Inc. | Systems and methods for using metadata to enhance data management operations |
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ATE284066T1 (en) | 2004-12-15 |
US6090555A (en) | 2000-07-18 |
DE69827913T2 (en) | 2005-04-07 |
US20040096883A1 (en) | 2004-05-20 |
CA2255384A1 (en) | 1999-06-11 |
EP0923050A2 (en) | 1999-06-16 |
EP0923050B1 (en) | 2004-12-01 |
JP2000069998A (en) | 2000-03-07 |
EP0923050A3 (en) | 2002-07-31 |
DE69827913D1 (en) | 2005-01-05 |
US20060258002A1 (en) | 2006-11-16 |
US6611767B1 (en) | 2003-08-26 |
US20060165313A1 (en) | 2006-07-27 |
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