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A machine-compiled database of genome-wide association studies

Tens of thousands of genotype-phenotype associations have been discovered to date, yet not all of them are easily accessible to scientists. Here, we describe GWASkb, a machine-compiled knowledge base of genetic associations collected from the scientific literature using automated information extract...

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Autores principales: Kuleshov, Volodymyr, Ding, Jialin, Vo, Christopher, Hancock, Braden, Ratner, Alexander, Li, Yang, Ré, Christopher, Batzoglou, Serafim, Snyder, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6659642/
https://www.ncbi.nlm.nih.gov/pubmed/31350405
http://dx.doi.org/10.1038/s41467-019-11026-x
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author Kuleshov, Volodymyr
Ding, Jialin
Vo, Christopher
Hancock, Braden
Ratner, Alexander
Li, Yang
Ré, Christopher
Batzoglou, Serafim
Snyder, Michael
author_facet Kuleshov, Volodymyr
Ding, Jialin
Vo, Christopher
Hancock, Braden
Ratner, Alexander
Li, Yang
Ré, Christopher
Batzoglou, Serafim
Snyder, Michael
author_sort Kuleshov, Volodymyr
collection PubMed
description Tens of thousands of genotype-phenotype associations have been discovered to date, yet not all of them are easily accessible to scientists. Here, we describe GWASkb, a machine-compiled knowledge base of genetic associations collected from the scientific literature using automated information extraction algorithms. Our information extraction system helps curators by automatically collecting over 6,000 associations from open-access publications with an estimated recall of 60–80% and with an estimated precision of 78–94% (measured relative to existing manually curated knowledge bases). This system represents a fully automated GWAS curation effort and is made possible by a paradigm for constructing machine learning systems called data programming. Our work represents a step towards making the curation of scientific literature more efficient using automated systems.
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spelling pubmed-66596422019-07-29 A machine-compiled database of genome-wide association studies Kuleshov, Volodymyr Ding, Jialin Vo, Christopher Hancock, Braden Ratner, Alexander Li, Yang Ré, Christopher Batzoglou, Serafim Snyder, Michael Nat Commun Article Tens of thousands of genotype-phenotype associations have been discovered to date, yet not all of them are easily accessible to scientists. Here, we describe GWASkb, a machine-compiled knowledge base of genetic associations collected from the scientific literature using automated information extraction algorithms. Our information extraction system helps curators by automatically collecting over 6,000 associations from open-access publications with an estimated recall of 60–80% and with an estimated precision of 78–94% (measured relative to existing manually curated knowledge bases). This system represents a fully automated GWAS curation effort and is made possible by a paradigm for constructing machine learning systems called data programming. Our work represents a step towards making the curation of scientific literature more efficient using automated systems. Nature Publishing Group UK 2019-07-26 /pmc/articles/PMC6659642/ /pubmed/31350405 http://dx.doi.org/10.1038/s41467-019-11026-x Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Kuleshov, Volodymyr
Ding, Jialin
Vo, Christopher
Hancock, Braden
Ratner, Alexander
Li, Yang
Ré, Christopher
Batzoglou, Serafim
Snyder, Michael
A machine-compiled database of genome-wide association studies
title A machine-compiled database of genome-wide association studies
title_full A machine-compiled database of genome-wide association studies
title_fullStr A machine-compiled database of genome-wide association studies
title_full_unstemmed A machine-compiled database of genome-wide association studies
title_short A machine-compiled database of genome-wide association studies
title_sort machine-compiled database of genome-wide association studies
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6659642/
https://www.ncbi.nlm.nih.gov/pubmed/31350405
http://dx.doi.org/10.1038/s41467-019-11026-x
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