FiGS: a filter-based gene selection workbench for microarray data
TL;DR: FiGS is an web-based application that automates an extensive search for the optimized gene selection analysis for a microarray dataset in a parallel computing environment and will provide both an efficient and comprehensive means of acquiring optimal gene sets that discriminate disease states from microarray datasets.
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Abstract: Background
The selection of genes that discriminate disease classes from microarray data is widely used for the identification of diagnostic biomarkers. Although various gene selection methods are currently available and some of them have shown excellent performance, no single method can retain the best performance for all types of microarray datasets. It is desirable to use a comparative approach to find the best gene selection result after rigorous test of different methodological strategies for a given microarray dataset.
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