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The Alliance of Genome Resources: Building a Modern Data Ecosystem for Model Organism Databases

Bult, Carol J. and Blake, Judith A. and Calvi, Brian R. and Cherry, J. Michael and DiFrancesco, Valentina and Fullem, Robert and Howe, Kevin L. and Kaufman, Thom and Mungall, Christopher and Perrimon, Norbert and Shimoyama, Mary and Sternberg, Paul W. and Thomas, Paul and Westerfield, Monte (2019) The Alliance of Genome Resources: Building a Modern Data Ecosystem for Model Organism Databases. Genetics, 213 (4). pp. 1189-1196. ISSN 0016-6731. https://resolver.caltech.edu/CaltechAUTHORS:20200102-160631829

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Abstract

Model organisms are essential experimental platforms for discovering gene functions, defining protein and genetic networks, uncovering functional consequences of human genome variation, and for modeling human disease. For decades, researchers who use model organisms have relied on Model Organism Databases (MODs) and the Gene Ontology Consortium (GOC) for expertly curated annotations, and for access to integrated genomic and biological information obtained from the scientific literature and public data archives. Through the development and enforcement of data and semantic standards, these genome resources provide rapid access to the collected knowledge of model organisms in human readable and computation-ready formats that would otherwise require countless hours for individual researchers to assemble on their own. Since their inception, the MODs for the predominant biomedical model organisms [Mus sp. (laboratory mouse), Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans, Danio rerio, and Rattus norvegicus] along with the GOC have operated as a network of independent, highly collaborative genome resources. In 2016, these six MODs and the GOC joined forces as the Alliance of Genome Resources (the Alliance). By implementing shared programmatic access methods and data-specific web pages with a unified “look and feel,” the Alliance is tackling barriers that have limited the ability of researchers to easily compare common data types and annotations across model organisms. To adapt to the rapidly changing landscape for evaluating and funding core data resources, the Alliance is building a modern, extensible, and operationally efficient “knowledge commons” for model organisms using shared, modular infrastructure.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1534/genetics.119.302523DOIArticle
ORCID:
AuthorORCID
Mungall, Christopher0000-0002-6601-2165
Sternberg, Paul W.0000-0002-7699-0173
Thomas, Paul0000-0002-9074-3507
Additional Information:© 2019 Bult et al. Available freely online through the author-supported open access option. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Manuscript received July 15, 2019; accepted for publication October 11, 2019; published Early Online October 17, 2019. We thank all members of the Alliance of Genome Resources, the staff of the MODs and GOC, and the Alliance Scientific Advisory Board for their contributions to developing the vision and approach for the Alliance. V.D.F. and R.F. contributed to this manuscript in their official roles as program coordinators for the National Institutes of Health National Human Genome Research Institute.
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Funding AgencyGrant Number
NIHUNSPECIFIED
Subject Keywords:model organism databases; bioinformatics; data stewardship; database sustainability
Issue or Number:4
Record Number:CaltechAUTHORS:20200102-160631829
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200102-160631829
Official Citation:The Alliance of Genome Resources: Building a Modern Data Ecosystem for Model Organism Databases. The Alliance of Genome Resources Consortium. GENETICS; December 1, 2019 vol. 213 no. 4 1189-1196; https://doi.org/10.1534/genetics.119.302523
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:100474
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:03 Jan 2020 02:39
Last Modified:03 Jan 2020 02:39

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