Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
Identifying The Most Significant Genes From Gene Expression Profiles For Sample Classification
 

Summary: Identifying The Most Significant Genes From Gene
Expression Profiles For Sample Classification
Hisham Al-Mubaid and Noushin Ghaffari, Member, IEEE
Abstract-- The gene expression data generated by the Microarray
technology for thousands of genes simultaneously provide huge
amounts of biomedical data in forms of gene expression profiles.
This generated gene data include complex variations of
expression levels of thousands of gene in the classes of samples.
The gene level variations allow for classifying and clustering the
samples based on only a small subset of genes. In this work, we
want to identify the most significant genes that demonstrate the
highest capabilities of discrimination between the classes of
samples. We present a new gene selection technique for
extracting the most significant genes from the huge gene/feature
space in a given gene expression dataset. Our method is based
on computing the discriminating capability of each gene, and
classifying the data according to only those most significant genes
that have highest discriminating capabilities. We also adapted
from text categorization and information retrieval five feature
selection techniques into the gene selection task to compare with

  

Source: Al-Mubaid, Hisham - School of Science and Computer Engineering, University of Houston-Clear Lake

 

Collections: Computer Technologies and Information Sciences