omniBiomarker: A Web-Based Application for Knowledge-Driven Biomarker Identification.
We have developed omniBiomarker, a web-based application that uses knowledge from the NCI Cancer Gene Index to guide the selection of biologically relevant algorithms for identifying biomarkers. Biomarker identification from high-throughput genomic expression data is difficult because of data properties (i.e., small-sample size compared to large-feature size) as well as the large number of available feature selection algorithms. Thus, it is unclear which algorithm should be used for a particular dataset. These factors lead to instability in biomarker identification and affect the reproducibility of results. We introduce a method for computing the biological relevance of feature selection algorithms using an externally validated knowledge base of manually curated cancer biomarkers. Results suggest that knowledge-driven biomarker identification can improve microarray-based clinical prediction performance. omniBiomarker can be accessed at http://omnibiomarker.bme.gatech.edu/.
John H
JH
Phan
Andrew N
AN
Young
May D
MD
Wang
D000465:Algorithms; D014408:Biomarkers, Tumor / Q000145:classification*; D019295:Computational Biology / Q000379:methods*; D020869:Gene Expression Profiling / Q000379:methods; D006801:Humans; D020407:Internet; D051188:Knowledge Bases; D000069550:Machine Learning; D012984:Software
D014408:Biomarkers, Tumor