Transcriptomics in Toxicogenomics, Part III: Data Modelling for Risk Assessment.

ABSTRACT: Transcriptomics data are relevant to address a number of challenges in Toxicogenomics (TGx). After careful planning of exposure conditions and data preprocessing, the TGx data can be used in predictive toxicology, where more advanced modelling techniques are applied. The large volume of molecular profiles produced by omics-based technologies allows the development and application of artificial intelligence (AI) methods in TGx. Indeed, the publicly available omics datasets are constantly increasing together with a plethora of different methods that are made available to facilitate their analysis, interpretation and the generation of accurate and stable predictive models. In this review, we present the state-of-the-art of data modelling applied to transcriptomics data in TGx. We show how the

SUBMITTER: Serra A 

PROVIDER: S-EPMC7221955 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature