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The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species
In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven’t been characterized, research organisms may not recapitulate human or veterin...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7056945/ https://www.ncbi.nlm.nih.gov/pubmed/31701156 http://dx.doi.org/10.1093/nar/gkz997 |
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author | Shefchek, Kent A Harris, Nomi L Gargano, Michael Matentzoglu, Nicolas Unni, Deepak Brush, Matthew Keith, Daniel Conlin, Tom Vasilevsky, Nicole Zhang, Xingmin Aaron Balhoff, James P Babb, Larry Bello, Susan M Blau, Hannah Bradford, Yvonne Carbon, Seth Carmody, Leigh Chan, Lauren E Cipriani, Valentina Cuzick, Alayne Della Rocca, Maria Dunn, Nathan Essaid, Shahim Fey, Petra Grove, Chris Gourdine, Jean-Phillipe Hamosh, Ada Harris, Midori Helbig, Ingo Hoatlin, Maureen Joachimiak, Marcin Jupp, Simon Lett, Kenneth B Lewis, Suzanna E McNamara, Craig Pendlington, Zoë M Pilgrim, Clare Putman, Tim Ravanmehr, Vida Reese, Justin Riggs, Erin Robb, Sofia Roncaglia, Paola Seager, James Segerdell, Erik Similuk, Morgan Storm, Andrea L Thaxon, Courtney Thessen, Anne Jacobsen, Julius O B McMurry, Julie A Groza, Tudor Köhler, Sebastian Smedley, Damian Robinson, Peter N Mungall, Christopher J Haendel, Melissa A Munoz-Torres, Monica C Osumi-Sutherland, David |
author_facet | Shefchek, Kent A Harris, Nomi L Gargano, Michael Matentzoglu, Nicolas Unni, Deepak Brush, Matthew Keith, Daniel Conlin, Tom Vasilevsky, Nicole Zhang, Xingmin Aaron Balhoff, James P Babb, Larry Bello, Susan M Blau, Hannah Bradford, Yvonne Carbon, Seth Carmody, Leigh Chan, Lauren E Cipriani, Valentina Cuzick, Alayne Della Rocca, Maria Dunn, Nathan Essaid, Shahim Fey, Petra Grove, Chris Gourdine, Jean-Phillipe Hamosh, Ada Harris, Midori Helbig, Ingo Hoatlin, Maureen Joachimiak, Marcin Jupp, Simon Lett, Kenneth B Lewis, Suzanna E McNamara, Craig Pendlington, Zoë M Pilgrim, Clare Putman, Tim Ravanmehr, Vida Reese, Justin Riggs, Erin Robb, Sofia Roncaglia, Paola Seager, James Segerdell, Erik Similuk, Morgan Storm, Andrea L Thaxon, Courtney Thessen, Anne Jacobsen, Julius O B McMurry, Julie A Groza, Tudor Köhler, Sebastian Smedley, Damian Robinson, Peter N Mungall, Christopher J Haendel, Melissa A Munoz-Torres, Monica C Osumi-Sutherland, David |
author_sort | Shefchek, Kent A |
collection | PubMed |
description | In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven’t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics. |
format | Online Article Text |
id | pubmed-7056945 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-70569452020-03-10 The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species Shefchek, Kent A Harris, Nomi L Gargano, Michael Matentzoglu, Nicolas Unni, Deepak Brush, Matthew Keith, Daniel Conlin, Tom Vasilevsky, Nicole Zhang, Xingmin Aaron Balhoff, James P Babb, Larry Bello, Susan M Blau, Hannah Bradford, Yvonne Carbon, Seth Carmody, Leigh Chan, Lauren E Cipriani, Valentina Cuzick, Alayne Della Rocca, Maria Dunn, Nathan Essaid, Shahim Fey, Petra Grove, Chris Gourdine, Jean-Phillipe Hamosh, Ada Harris, Midori Helbig, Ingo Hoatlin, Maureen Joachimiak, Marcin Jupp, Simon Lett, Kenneth B Lewis, Suzanna E McNamara, Craig Pendlington, Zoë M Pilgrim, Clare Putman, Tim Ravanmehr, Vida Reese, Justin Riggs, Erin Robb, Sofia Roncaglia, Paola Seager, James Segerdell, Erik Similuk, Morgan Storm, Andrea L Thaxon, Courtney Thessen, Anne Jacobsen, Julius O B McMurry, Julie A Groza, Tudor Köhler, Sebastian Smedley, Damian Robinson, Peter N Mungall, Christopher J Haendel, Melissa A Munoz-Torres, Monica C Osumi-Sutherland, David Nucleic Acids Res Database Issue In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven’t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics. Oxford University Press 2020-01-08 2019-11-08 /pmc/articles/PMC7056945/ /pubmed/31701156 http://dx.doi.org/10.1093/nar/gkz997 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Database Issue Shefchek, Kent A Harris, Nomi L Gargano, Michael Matentzoglu, Nicolas Unni, Deepak Brush, Matthew Keith, Daniel Conlin, Tom Vasilevsky, Nicole Zhang, Xingmin Aaron Balhoff, James P Babb, Larry Bello, Susan M Blau, Hannah Bradford, Yvonne Carbon, Seth Carmody, Leigh Chan, Lauren E Cipriani, Valentina Cuzick, Alayne Della Rocca, Maria Dunn, Nathan Essaid, Shahim Fey, Petra Grove, Chris Gourdine, Jean-Phillipe Hamosh, Ada Harris, Midori Helbig, Ingo Hoatlin, Maureen Joachimiak, Marcin Jupp, Simon Lett, Kenneth B Lewis, Suzanna E McNamara, Craig Pendlington, Zoë M Pilgrim, Clare Putman, Tim Ravanmehr, Vida Reese, Justin Riggs, Erin Robb, Sofia Roncaglia, Paola Seager, James Segerdell, Erik Similuk, Morgan Storm, Andrea L Thaxon, Courtney Thessen, Anne Jacobsen, Julius O B McMurry, Julie A Groza, Tudor Köhler, Sebastian Smedley, Damian Robinson, Peter N Mungall, Christopher J Haendel, Melissa A Munoz-Torres, Monica C Osumi-Sutherland, David The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species |
title | The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species |
title_full | The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species |
title_fullStr | The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species |
title_full_unstemmed | The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species |
title_short | The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species |
title_sort | monarch initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7056945/ https://www.ncbi.nlm.nih.gov/pubmed/31701156 http://dx.doi.org/10.1093/nar/gkz997 |
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