Combined transcriptomics classifier analysis reveals a set of adverse effect genes for use as potential endpoint in effect based screening

ABSTRACT: Environmental risk assessment relies heavily on the use of bioassays to assess the environmental impact of chemicals. Gene expression is gaining acceptance as a valuable mechanistic endpoint in bioassays and effect-based screening. Data analysis and its results however, are often complex and not directly applicable in risk assessment. Classifier analysis is a promising method to turn complex gene expression analysis results into answers suitable for risk assessment. We have assembled a large gene expression dataset assembled from multiple studies and experiments in the springtail Folsomia candida, with the aim of selecting a set of genes that can be trained to classify general toxic stress. By performing differential expression analysis prior to classification we were able to select a set

ORGANISM(S): Folsomia candida

SUBMITTER: Tjalf de Boer 

PROVIDER: E-GEOD-70877 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress