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Genetics. 2016 Aug;203(4):1491-5. doi: 10.1534/genetics.116.188870.

Navigating the Phenotype Frontier: The Monarch Initiative.

Author information

1
Department of Medical Informatics and Epidemiology, and Oregon Health and Science University Library, Oregon Health and Science University, Portland, Oregon 97239.
2
Institute for Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, 13353, Germany.
3
Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, California 94720.
4
RTI International, Durham, North Carolina 27709.
5
Department of Biomedical Informatics, University of Pittsburgh, Pennsylvania 15206.
6
Wellcome Trust Sanger Institute, Cambridge, CB10 1SA, United Kingdom.
7
Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Sydney, 2010, Australia.
8
William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, and Queen Mary University of London, EC1M 6BQ, United Kingdom.
9
Department of Medical Informatics and Epidemiology, and Oregon Health and Science University Library, Oregon Health and Science University, Portland, Oregon 97239 haendel@ohsu.edu.

Abstract

The principles of genetics apply across the entire tree of life. At the cellular level we share biological mechanisms with species from which we diverged millions, even billions of years ago. We can exploit this common ancestry to learn about health and disease, by analyzing DNA and protein sequences, but also through the observable outcomes of genetic differences, i.e. phenotypes. To solve challenging disease problems we need to unify the heterogeneous data that relates genomics to disease traits. Without a big-picture view of phenotypic data, many questions in genetics are difficult or impossible to answer. The Monarch Initiative (https://monarchinitiative.org) provides tools for genotype-phenotype analysis, genomic diagnostics, and precision medicine across broad areas of disease.

KEYWORDS:

comparative medicine; data integration; disease diagnosis; disease discovery; phenotype ontologies

PMID:
27516611
PMCID:
PMC4981258
DOI:
10.1534/genetics.116.188870
[Indexed for MEDLINE]
Free PMC Article

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