The use of omics-based approaches in regulatory toxicology: an alternative approach to assess the no observed transcriptional effect level

In this paper we present a method for evaluating the NOTEL based on anomaly detection: a classifier is built that discriminates between target class instances, i.e., normal cases, and anomalies, i.e., samples with significant transcriptional effects. The strength of this method is that (i) it can be applied to cases in which few samples are available and the space dimension is high and (ii) it makes use of the complete gene expression profiles.