DESTAF: A database of text-mined associations for reproductive toxins potentially affecting human fertility
AuthorsDawe, Adam Sean
Seshadri, Sundararajan Vijayaraghava
Christoffels, Alan G.
Bajic, Vladimir B.
KAUST DepartmentComputational Bioscience Research Center (CBRC)
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Applied Mathematics and Computational Science Program
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AbstractThe Dragon Exploration System for Toxicants and Fertility (DESTAF) is a publicly available resource which enables researchers to efficiently explore both known and potentially novel information and associations in the field of reproductive toxicology. To create DESTAF we used data from the literature (including over 10. 500 PubMed abstracts), several publicly available biomedical repositories, and specialized, curated dictionaries. DESTAF has an interface designed to facilitate rapid assessment of the key associations between relevant concepts, allowing for a more in-depth exploration of information based on different gene/protein-, enzyme/metabolite-, toxin/chemical-, disease- or anatomically centric perspectives. As a special feature, DESTAF allows for the creation and initial testing of potentially new association hypotheses that suggest links between biological entities identified through the database.DESTAF, along with a PDF manual, can be found at http://cbrc.kaust.edu.sa/destaf. It is free to academic and non-commercial users and will be updated quarterly. © 2011 Elsevier Inc.
SponsorsSVS and AC have been supported by the South African Department of Science and Technology/National Research Foundation (DST/NRF) Research Chair in Bioinformatics and Human Health.
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