Abstract
We have designed and developed a data integration and visualization platform that provides evidence about the association of known and potential drug targets with diseases. The platform is designed to support identification and prioritization of biological targets for follow-up. Each drug target is linked to a disease using integrated genome-wide data from a broad range of data sources. The platform provides either a target-centric workflow to identify diseases that may be associated with a specific target, or a disease-centric workflow to identify targets that may be associated with a specific disease. Users can easily transition between these target- and disease-centric workflows. The Open Targets Validation Platform is accessible at https://www.targetvalidation.org.
Highlights
The fundamental tenet of pharmacology is that a drug can be identified that interacts with a target molecule to modulate a physiological process and alter the course of a disease [1,2]
We defined a set of core data types that were of primary importance to target validation. These include information on genetic associations with either common disease primarily from genome-wide association studies (GWAS) or rare Mendelian disease from sequencing of exons of protein coding genes; somatic mutations implicated in cancer; significant changes in gene expression in appropriate sample comparisons from microarray or RNA-seq experiments; existing drugs that engage a target and treat a disease; animal models with gene knockouts and phenotypes concordant with human disease; biochemical pathways that are affected by disease; and associations of targets with disease in the biomedical literature identified through text mining
We provide access to common disease genetic evidence based on GWAS study results from the GWAS Catalog and rare Mendelian disease evidence based on clinical variant information accessible from EVA
Summary
The fundamental tenet of pharmacology is that a drug (small molecule or biological) can be identified that interacts with a target molecule (usually a protein) to modulate a physiological process and alter the course of a disease [1,2]. We defined a set of core data types that were of primary importance to target validation These include information on genetic associations with either common disease primarily from GWAS or rare Mendelian disease from sequencing of exons of protein coding genes; somatic mutations implicated in cancer; significant changes in gene expression in appropriate sample comparisons from microarray or RNA-seq experiments; existing drugs that engage a target and treat a disease; animal models with gene knockouts and phenotypes concordant with human disease; biochemical pathways that are affected by disease; and associations of targets with disease in the biomedical literature identified through text mining.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
