FiGS: a filter-based gene selection workbench for microarray data

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. Results: FiGS is a web-based workbench that automatically compares various gene selection procedures and provides the optimal gene selection result for an input microarray dataset. FiGS builds up diverse gene selection procedures by aligning different feature selection techniques and classifiers. In addition to the highly reputed techniques, FiGS diversifies the gene selection procedures by incorporating gene clustering options in the feature selection step and d...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Taeho Hwang, Choong-Hyun Sun, Taegyun Yun, Gwan-Su Yi
• Keywords: BMCBI 2010, Gene Selection, Gene Selection Methods, Gene Selection Procedures