The Comparative Toxicogenomics Database's 10th year anniversary: update 2015

By Allan Peter Davis, Cynthia J. Grondin, Kelley Lennon-Hopkins, Cynthia A. Saraceni-Richards, Daniela Sciaky, B. King, Thomas C. Wiegers, Carolyn J. Mattingly. 2014

384 citations recorded by the source corpus.

Ten years ago, the Comparative Toxicogenomics Database (CTD; http://ctdbase.org/) was developed out of a need to formalize, harmonize and centralize the information on numerous genes and proteins responding to environmental toxic agents across diverse species. CTD's initial approach was to facilitate comparisons of nucleotide and protein sequences of toxicologically significant genes by curating these sequences and electronically annotating them with chemical terms from their associated references. Since then, however, CTD has vastly expanded its scope to robustly represent a triad of chemical–gene, chemical–disease and gene–disease interactions that are manually curated from the scientific literature by professional biocurators using controlled vocabularies, ontologies and structured notation. Today, CTD includes 24 million toxicogenomic connections relating chemicals/drugs, genes/proteins, diseases, taxa, phenotypes, Gene Ontology annotations, pathways and interaction modules. In this 10th year anniversary update, we outline the evolution of CTD, including our increased data content, new ‘Pathway View’ visualization tool, enhanced curation practices, pilot chemical–phenotype results and impending exposure data set. The prototype database originally described in our first report has transformed into a sophisticated resource used actively today to help scientists develop and test hypotheses about the etiologies of environmentally influenced diseases.

Subfields: Computational Theory and Mathematics, Molecular Biology

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Citations in the corpus

Assessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) task (2016, background): “…correlative chemical-disease relations (CDR) from unstructured free text into structured knowledge to facilitate identification of potential toxicity has been an important theme for several bioinformatics databases, such as the Comparative Toxicogenomics Database (CTD; http:// ctdbase.org/) (5).”
The BioGRID interaction database: 2017 update (2016, background): “We surveyed the content of the major specialized chemical interaction databases, including DrugBank (37), HMdb (61), T3DB (62), BindingDB (63), CTD (64), Therapeutic Target DB (65), ChemBank (66), PharmGKB (67), DGIdb (68), PubChem (69) and ChEMBL (70) to determine the shared fields housed in each o”
Large-Scale Off-Target Identification Using Fast and Accurate Dual Regularized One-Class Collaborative Filtering and Its Application to Drug Repurposing (2016, methodology): “The largest cluster of drugs contained a total of 313 drugs, and their relationships to diseases were examined based on the known associations annotated in CTD [31].”
Network-based approach to prediction and population-based validation of in silico drug repurposing (2018, methodology): “For each CV event, we collected disease-associated genes from 8 commonly used data sources: The OMIM database (Online Mendelian Inheritance in Man) (66), The Comparative Toxicogenomics Database (67), HuGE Navigator (68), DisGeNET (69), ClinVar (70), GWAS Catalog (71), GWASdb (72), and PheWAS Catalog”