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Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology by Quoc Nam Tran, Hamid R Arabnia

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Chapter 12

Feature Selection and Analysis of Gene Expression Data Using Low-Dimensional Linear Programming

Satish Ch. Panigrahi; Md. Shafiul Alam alam9@uwindsor.ca; Asish Mukhopadhyay    University of Windsor, Windsor, Ontario, Canada

Abstract

The availability of large volumes of gene expression data from microarray analysis [complementary DNA (cDNA) and oligonucleotide] has opened the door to the diagnoses and treatments of various diseases based on gene expression profiling. This chapter discusses a new profiling tool based on linear programming. Given gene expression data from two subclasses of the same disease (e.g., leukemia), we were able to determine efficiently if the samples are LS with respect to triplets of genes. This was left ...

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