Discovery and validation of gene classifiers for endocrine disrupting chemicals in Zebrafish (Danio rerio)

ABSTRACT: Background: Development and application of transcriptomics-based gene classifiers for ecotoxicological applications lag far behind those of human biomedical science. Many such classifiers discovered thus far lack vigorous statistical and experimental validations, with their stability and reliability unknown. A combination of genetic algorithm/support vector machines and genetic algorithm/K nearest neighbors were used in this study to search for classifiers of endocrine disrupting chemicals (EDCs) in zebrafish. Searches were conducted on both tissue-specific and all tissue combined datasets, either across the entire transcriptome or within individual transcription factor (TF) networks previously linked to EDC effects. Candidate classifiers were evaluated by gene set enrichment analysis (G

ORGANISM(S): Danio rerio

SUBMITTER: Rong-Lin Wang 

PROVIDER: E-GEOD-38070 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress