Predicting causal genes from psychiatric genome-wide association studies using high-level etiological knowledge.

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Bibliographic Details
Title: Predicting causal genes from psychiatric genome-wide association studies using high-level etiological knowledge.
Authors: Wainberg M; Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada., Merico D; Deep Genomics Inc, Toronto, ON, Canada.; The Centre for Applied Genomics (TCAG), The Hospital for Sick Children, Toronto, ON, Canada., Keller MC; Department of Psychology and Neuroscience, University of Colorado, Boulder, CO, USA.; Institute for Behavioral Genetics, University of Colorado, Boulder, CO, USA., Fauman EB; Internal Medicine Research Unit, Pfizer Worldwide Research, Development and Medical, Cambridge, MA, USA., Tripathy SJ; Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada. shreejoy.tripathy@utoronto.ca.; Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada. shreejoy.tripathy@utoronto.ca.; Department of Psychiatry, University of Toronto, Toronto, ON, Canada. shreejoy.tripathy@utoronto.ca.; Department of Physiology, University of Toronto, Toronto, ON, Canada. shreejoy.tripathy@utoronto.ca.
Source: Molecular psychiatry [Mol Psychiatry] 2022 Jul; Vol. 27 (7), pp. 3095-3106. Date of Electronic Publication: 2022 Apr 11.
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Nature Publishing Group Specialist Journals Country of Publication: England NLM ID: 9607835 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1476-5578 (Electronic) Linking ISSN: 13594184 NLM ISO Abbreviation: Mol Psychiatry Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1476-5578
DOI:10.1038/s41380-022-01542-6