DTNI: a novel toxicogenomics data analysis tool for identifying the molecular mechanisms underlying the adverse effects of toxic compounds.

ABSTRACT: Unravelling gene regulatory networks (GRNs) influenced by chemicals is a major challenge in systems toxicology. Because toxicant-induced GRNs evolve over time and dose, the analysis of global gene expression data measured at multiple time points and doses will provide insight in the adverse effects of compounds. Therefore, there is a need for mathematical methods for GRN identification from time-over-dose-dependent data. One of the current approaches for GRN inference is Time Series Network Identification (TSNI). TSNI is based on ordinary differential equations (ODE), describing the time evolution of the expression of each gene, which is assumed to be dependent on the expression of other genes and an external perturbation (i.e. chemical exposure). Here, we present Dose-Time Network Identif

SUBMITTER: Hendrickx DM 

PROVIDER: S-EPMC5429357 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature