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Nucleic Acids Res. 2017 Jan 4;45(D1):D712-D722. doi: 10.1093/nar/gkw1128. Epub 2016 Nov 29.

The Monarch Initiative: an integrative data and analytic platform connecting phenotypes to genotypes across species.

Author information

1
Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
2
Department of Medical Informatics and Clinical Epidemiology and OHSU Library, Oregon Health & Science University, Portland, OR, 97239, USA.
3
Institute for Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany.
4
RTI International, Research Triangle Park, NC, 27709, USA.
5
Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, 15260, USA.
6
William Harvey Research Institute, Barts & The London School of Medicine & Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK.
7
Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia.
8
The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032mUSA.
9
Department of Medical Informatics and Clinical Epidemiology and OHSU Library, Oregon Health & Science University, Portland, OR, 97239, USA Haendel@ohsu.edu.

Abstract

The correlation of phenotypic outcomes with genetic variation and environmental factors is a core pursuit in biology and biomedicine. Numerous challenges impede our progress: patient phenotypes may not match known diseases, candidate variants may be in genes that have not been characterized, model organisms may not recapitulate human or veterinary diseases, filling evolutionary gaps is difficult, and many resources must be queried to find potentially significant genotype-phenotype associations. Non-human organisms have proven instrumental in revealing biological mechanisms. Advanced informatics tools can identify phenotypically relevant disease models in research and diagnostic contexts. Large-scale integration of model organism and clinical research data can provide a breadth of knowledge not available from individual sources and can provide contextualization of data back to these sources. The Monarch Initiative (monarchinitiative.org) is a collaborative, open science effort that aims to semantically integrate genotype-phenotype data from many species and sources in order to support precision medicine, disease modeling, and mechanistic exploration. Our integrated knowledge graph, analytic tools, and web services enable diverse users to explore relationships between phenotypes and genotypes across species.

PMID:
27899636
PMCID:
PMC5210586
DOI:
10.1093/nar/gkw1128
[Indexed for MEDLINE]
Free PMC Article

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