Identification of biomarkers that distinguish chemical contaminants using a gradient feature selection method

ABSTRACT: There are many toxic chemicals to contaminate the world and cause harm to human and other organisms. How to quickly discriminate these compounds and characterize their potential molecular mechanism and toxicity is essential. High through put transcriptomics profiles such as microarray have been proven useful to identify biomarkers for different classification and toxicity prediction purposes. Here we aim to investigate how to use microarray to predict chemical contaminants and their possible mechanisms. In this study, we divided 105 compounds plus vehicle control into 14 compound classes. On the basis of gene expression profiles of in vitro primary cultured hepatocytes, we comprehensively compared various normalization, feature selection and classification algorithms for the classification

ORGANISM(S): Rattus norvegicus

SUBMITTER: Xin Guan 

PROVIDER: E-GEOD-19662 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress