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We present a systematic approach to evaluate the performance of different feature sets based on recursive feature elimination, RFE. Based on a systematic ...
May 24, 2005 · We present a systematic approach to evaluate the performance of different feature sets based on recursive feature elimination, RFE. Based on a ...
High weighted features are more likely to apply to positive samples (NEWGENE), low weighted features to negative samples. Names in bold indicate binary ...
This helps us to identify descriptive features, to learn about the structure of the problem, and to design systems that are faster and easier to understand. We ...
Abstract In task 1A of the BioCreAtIvE evaluation, systems had to be devised that recognize words and phrases forming gene or protein names in natural ...
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 ...
We compared the performance of 41 analysis models based on 14 software packages and different data sets, including high-quality data and low-quality data from ...
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A high-quality manually annotated corpus for genes developed at the US National Library of Medicine (NLM), covering ambiguous gene names.
(2005), 'Systematic feature evaluation for gene name recognition', BMC Bioinformatics, Vol. 6(Suppl 1), p.S9. 33. Rebholz-Schuhmann, D., Kirsch, H. and.