Session 1: Predicting mechanisms of toxicity

Integrating literature-based curated data to predict mechanisms of toxicity
OpenTox USA 2015 speaker: Carolyn Mattingly, North Carolina State University
PRESENTING AUTHOR: 

Carolyn Mattingly, PhD, Associate Professor

INSTITUTION / COMPANY : 

North Carolina State University
Dept of Biological Sciences

AUTHOR(S): 

C.J. Mattingly, C.J. Grondin, K. Lennon-Hopkins, C. Saraceni-Richards, D. Sciaky, J. Wiegers, T.C. Wiegers and A.P. Davis - Department of Biological Sciences, North Carolina State University, Raleigh, NCĀ  27695-7617
B.L. King - MDIBL, Salisbury Cove, ME 04672

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ABSTRACT CONTENT / DETAILS: 

The Comparative Toxicogenomics Database (CTD; http://ctdbase.org) is a freely available resource that informs hypothesis development about environmental effects on human health.

CTD content consists of manually curated chemical-gene-disease interactions, which are integrated with functional information, canonical pathways, and novel tools to infer relationships between chemical exposures and biological events.

A new curated exposure data module will be integrated and released through CTD in early 2015, which includes metrics for stressors, receptors, exposure events and outcomes. An additional project is underway that will capture chemical-phenotype information.

The goal of this project is to determine whether inclusion of non-disease phenotypes in CTD could advance:

a) understanding of environmental disease progression,
b) identification of exposure biomarkers, and
c) the capacity to conduct and interpret studies across species and experimental systems.

Preliminary results indicate that integration of mechanistic, phenotypic and exposure data will help to generate meaningful links between what is currently disconnected information in the literature.

Outcomes from integrating and analyzing these data with other high-throughput data sets may further inform hypotheses and help to build adverse outcome pathways.

This presentation will discuss CTD data content and applications for advancing mechanistic understanding of and health outcomes resulting from environmental exposures.