Application of the GA/KNN method to SELDI proteomics data

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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.

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