Crowdsourcing genetic prediction of clinical utility in the Rheumatoid Arthritis Responder Challenge
Year: 2013
Type: article
Abstract: The ability to translate large-scale genetics and genomics data into biological knowledge has not kept pace with our ability to generate these data sets. As a consequence, a major bottleneck in biomedical research has become access to data within a computational workspace that allows for robust, collaborative analyses. One innovative solution is to bring together scientific data, code, tools and disease models into an open commons or workspace, for example, the Synapse platform of Sage Bionetworks 1 . This environment allows for real-time sharing of large genomic data sets, continuous peer review and rapid learning within a system constructed to provide data access in a manner aligned with the informed consent provided by patients and research participants.
Source: Nature Genetics
DOI: 10.1038/ng.2623
Authors: Robert M Plenge, Jeffrey D Greenberg, Lara M Mangravite, Jonathan M J Derry, Eli A Stahl, Marieke J H Coenen, Anne Barton, Leonid Padyukov, Lars Klareskog, Peter K Gregersen, Xavier Mariette, Larry W Moreland, S Louis Bridges, Niek de Vries, Tom W J Huizinga, Henk-Jan Guchelaar, Stephen H Friend, Gustavo Stolovitzky
Institutions: Broad Institute, Brigham and Women's Hospital, Harvard University, New York University, Sage Bionetworks, Icahn School of Medicine at Mount Sinai, Radboud University Medical Center, Manchester Academic Health Science Centre, University of Manchester, Karolinska Institutet, Northwell Health, Feinstein Institute for Medical Research, Université Paris-Sud, Inserm, Assistance Publique – Hôpitaux de Paris, Hôpitaux universitaires Paris Sud, University of Pittsburgh, University of Alabama at Birmingham, Amsterdam UMC Location University of Amsterdam, University of Amsterdam, Leiden University Medical Center, IBM (United States), IBM Research - Thomas J. Watson Research Center
Language: English
Subfield: Rheumatology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $12,690
OpenAlex ID: W1974481128