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- Title
CTD<sup>2</sup> Dashboard: a searchable web interface to connect validated results from the Cancer Target Discovery and Development Network.
- Authors
Aksoy, Bülent Arman; Dančík, Vlado; Smith, Kenneth; Mazerik, Jessica N.; Ji, Zhou; Gross, Benjamin; Nikolova, Olga; Jaber, Nadia; Califano, Andrea; Schreiber, Stuart L.; Gerhard, Daniela S.; Hermida, Leandro C.; Jagu, Subhashini; Sander, Chris; Floratos, Aris; Clemons, Paul A.
- Abstract
The Cancer Target Discovery and Development (CTD2) Network aims to use functional genomics to accelerate the translation of high-throughput and high-content genomic and small-molecule data towards use in precision oncology. As part of this goal, and to share its conclusions with the research community, the Network developed the ‘CTD2 Dashboard’ [https://ctd2-dashboard.nci.nih.gov/], which compiles CTD2 Network-generated conclusions, termed ‘observations’, associated with experimental entities, collected by its member groups (‘Centers’). Any researcher interested in learning about a given gene, protein, or compound (a ‘subject’) studied by the Network can come to the CTD2 Dashboard to quickly and easily find, review, and understand Network-generated experimental results. In particular, the Dashboard allows visitors to connect experiments about the same target, biomarker, etc., carried out by multiple Centers in the Network. The Dashboard’s unique knowledge representation allows information to be compiled around a subject, so as to become greater than the sum of the individual contributions. The CTD2 Network has broadly defined levels of validation for evidence (‘Tiers’) pertaining to a particular finding, and the CTD2 Dashboard uses these Tiers to indicate the extent to which results have been validated. Researchers can use the Network’s insights and tools to develop a new hypothesis or confirm existing hypotheses, in turn advancing the findings towards clinical applications.
- Publication
Database: The Journal of Biological Databases & Curation, 2017, Vol 2017, Issue 1, p1
- ISSN
1758-0463
- Publication type
Article
- DOI
10.1093/database/bax054