Application of the GA/KNN method to SELDI proteomics data

Authors:
Leping Li;David M. Umbach;Paul Terry;Jack A. Taylor
Affiliations:
Biostatistics Branch,;Biostatistics Branch,;Epidemiology Branch;Epidemiology Branch
Venue:
Bioinformatics
Year:
2004

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Abstract

Summary: Proteomics technology has shown promise in identifying biomarkers for disease, toxicant exposure and stress. We show by example that the genetic algorithm/k-nearest neighbors method, developed for mining high-dimensional microarray gene expression data, is also capable of mining surface enhanced laser desorption/ionization--time-of-flight proteomics data. Availability: The source code of the program and documentation on how to use it are freely available to non-commercial users at http://dir.niehs.nih.gov/dirbb/lifiles/softlic.htm