IMR Press / FBL / Volume 13 / Issue 2 / DOI: 10.2741/2712

Frontiers in Bioscience-Landmark (FBL) is published by IMR Press from Volume 26 Issue 5 (2021). Previous articles were published by another publisher on a subscription basis, and they are hosted by IMR Press on imrpress.com as a courtesy and upon agreement with Frontiers in Bioscience.

Article
Classification algorithms for phenotype prediction in genomics and proteomics
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1 Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, 3970 Reservoir Rd NW, Washington, DC 20057
2 Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University Medical Center, 3970 Reservoir Rd NW, Washington, DC 20057
3 Department of Oncology, Georgetown University Medical Center, 3970 Reservoir Rd NW, Washington, DC 20057
4 Department of Pathology, Johns Hopkins Medical Institutions, Baltimore, MD 21287
5 Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA
6 Department of Physiology and Biophysics, Georgetown University Medical Center, 3970 Reservoir Rd NW, Washington, DC 20057
Front. Biosci. (Landmark Ed) 2008, 13(2), 691–708; https://doi.org/10.2741/2712
Published: 1 January 2008
Abstract

This paper gives an overview of statistical and machine learning-based feature selection and pattern classification algorithms and their application in molecular cancer classification or phenotype prediction. In particular, the paper focuses on the use of these computational methods for gene and peak selection from microarray and mass spectrometry data, respectively. The selected features are presented to a classifier for phenotype prediction.

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