Premium
Gene Expression Microarray Data Analysis for Toxicology Profiling
Author(s) -
CUNNINGHAM M. J.,
LIANG S.,
FURMAN S.,
SEILHAMER J. J.,
SOMOGYI R.
Publication year - 2000
Publication title -
annals of the new york academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.712
H-Index - 248
eISSN - 1749-6632
pISSN - 0077-8923
DOI - 10.1111/j.1749-6632.2000.tb06867.x
Subject(s) - gene , microarray analysis techniques , gene expression profiling , computational biology , microarray , profiling (computer programming) , gene expression , biology , genetics , computer science , operating system
A bstract : When dealing with thousands of genes, all potentially interesting, it is desirable to rank the genes according to their degree of participation in a physiological process. Therefore, genes with the highest Shannon entropy and ERL can be selected as the best toxicity target candidates, permitting preclinical scientists to focus their research and resources on those genes.