Identification of biomarkers that distinguish chemical contaminants based on gene expression profiles.

ABSTRACT:

Background

High throughput transcriptomics profiles such as those generated using microarrays have been useful in identifying biomarkers for different classification and toxicity prediction purposes. Here, we investigated the use of microarrays to predict chemical toxicants and their possible mechanisms of action.

Results

In this study, in vitro cultures of primary rat hepatocytes were exposed to 105 chemicals and vehicle controls, representing 14 compound classes. We comprehensively compared various normalization of gene expression profiles, feature selection and classification algorithms for the classification of these 105 chemicals into14 compound classes. We found that normalization had little effect on the averaged classification accuracy. Two support vector machine (SV

SUBMITTER: Wei X 

PROVIDER: S-EPMC4051169 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature