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Oct 25, 2023 · GNorm2 integrates a range of advanced deep learning-based methods, resulting in the highest levels of accuracy and efficiency for gene recognition and ...
Aug 26, 2024 · We systematically evaluate 47 highly variable gene (HVG) selection methods, consisting of 21 baseline methods developed based on different data transformations.
Missing: recognition | Show results with:recognition
Jan 2, 2024 · Our work provides a rich resource identifying regulatory and functional genes and placing them into pathways, thereby opening the door to a system-level ...
Missing: feature recognition
Jun 3, 2024 · We systematically evaluated 49 simulation methods developed for scRNA-seq and/or SRT data in terms of accuracy, functionality, scalability, and usability.
Missing: recognition | Show results with:recognition
Jun 7, 2024 · The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth.
Missing: recognition | Show results with:recognition
Jun 28, 2024 · In this study, a transcriptome-wide identification of reference genes was conducted based on 447 transcriptome datasets, comprising 200 tissue samples, 107 ...
Missing: recognition | Show results with:recognition
Apr 1, 2024 · Here we evaluate five Large Language Models (LLMs) for their ability to discover the common biological functions represented by a gene set.
Missing: feature | Show results with:feature
May 15, 2024 · The goal of the GENCODE project is to identify and classify all gene features in the human and mouse genomes with high accuracy based on biological evidence.
Jun 5, 2024 · Our paper explores the field of Biomedical Named Entity Recognition (BioNER) by closely analysing two advanced models, SciSpaCy and BioBERT.
Apr 4, 2024 · PubTator 3.0 uses AIONER (8), a recently developed named entity recognition (NER) model, to recognize entities of six types: genes/proteins, chemicals, diseases ...
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