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The Systems Genetics Resource: A Web Application to Mine Global Data for Complex Disease Traits
The Systems Genetics Resource (SGR) (http://systems.genetics.ucla.edu) is a new open-access web application and database that contains genotypes and clinical and intermediate phenotypes from both human and mouse studies. The mouse data include studies using crosses between specific inbred strains an...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3657633/ https://www.ncbi.nlm.nih.gov/pubmed/23730305 http://dx.doi.org/10.3389/fgene.2013.00084 |
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author | van Nas, Atila Pan, Calvin Ingram-Drake, Leslie A. Ghazalpour, Anatole Drake, Thomas A. Sobel, Eric M. Papp, Jeanette C. Lusis, Aldons J. |
author_facet | van Nas, Atila Pan, Calvin Ingram-Drake, Leslie A. Ghazalpour, Anatole Drake, Thomas A. Sobel, Eric M. Papp, Jeanette C. Lusis, Aldons J. |
author_sort | van Nas, Atila |
collection | PubMed |
description | The Systems Genetics Resource (SGR) (http://systems.genetics.ucla.edu) is a new open-access web application and database that contains genotypes and clinical and intermediate phenotypes from both human and mouse studies. The mouse data include studies using crosses between specific inbred strains and studies using the Hybrid Mouse Diversity Panel. SGR is designed to assist researchers studying genes and pathways contributing to complex disease traits, including obesity, diabetes, atherosclerosis, heart failure, osteoporosis, and lipoprotein metabolism. Over the next few years, we hope to add data relevant to deafness, addiction, hepatic steatosis, toxin responses, and vascular injury. The intermediate phenotypes include expression array data for a variety of tissues and cultured cells, metabolite levels, and protein levels. Pre-computed tables of genetic loci controlling intermediate and clinical phenotypes, as well as phenotype correlations, are accessed via a user-friendly web interface. The web site includes detailed protocols for all of the studies. Data from published studies are freely available; unpublished studies have restricted access during their embargo period. |
format | Online Article Text |
id | pubmed-3657633 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-36576332013-05-31 The Systems Genetics Resource: A Web Application to Mine Global Data for Complex Disease Traits van Nas, Atila Pan, Calvin Ingram-Drake, Leslie A. Ghazalpour, Anatole Drake, Thomas A. Sobel, Eric M. Papp, Jeanette C. Lusis, Aldons J. Front Genet Genetics The Systems Genetics Resource (SGR) (http://systems.genetics.ucla.edu) is a new open-access web application and database that contains genotypes and clinical and intermediate phenotypes from both human and mouse studies. The mouse data include studies using crosses between specific inbred strains and studies using the Hybrid Mouse Diversity Panel. SGR is designed to assist researchers studying genes and pathways contributing to complex disease traits, including obesity, diabetes, atherosclerosis, heart failure, osteoporosis, and lipoprotein metabolism. Over the next few years, we hope to add data relevant to deafness, addiction, hepatic steatosis, toxin responses, and vascular injury. The intermediate phenotypes include expression array data for a variety of tissues and cultured cells, metabolite levels, and protein levels. Pre-computed tables of genetic loci controlling intermediate and clinical phenotypes, as well as phenotype correlations, are accessed via a user-friendly web interface. The web site includes detailed protocols for all of the studies. Data from published studies are freely available; unpublished studies have restricted access during their embargo period. Frontiers Media S.A. 2013-05-20 /pmc/articles/PMC3657633/ /pubmed/23730305 http://dx.doi.org/10.3389/fgene.2013.00084 Text en Copyright © 2013 van Nas, Pan, Ingram-Drake, Ghazalpour, Drake, Sobel, Papp and Lusis. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc. |
spellingShingle | Genetics van Nas, Atila Pan, Calvin Ingram-Drake, Leslie A. Ghazalpour, Anatole Drake, Thomas A. Sobel, Eric M. Papp, Jeanette C. Lusis, Aldons J. The Systems Genetics Resource: A Web Application to Mine Global Data for Complex Disease Traits |
title | The Systems Genetics Resource: A Web Application to Mine Global Data for Complex Disease Traits |
title_full | The Systems Genetics Resource: A Web Application to Mine Global Data for Complex Disease Traits |
title_fullStr | The Systems Genetics Resource: A Web Application to Mine Global Data for Complex Disease Traits |
title_full_unstemmed | The Systems Genetics Resource: A Web Application to Mine Global Data for Complex Disease Traits |
title_short | The Systems Genetics Resource: A Web Application to Mine Global Data for Complex Disease Traits |
title_sort | systems genetics resource: a web application to mine global data for complex disease traits |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3657633/ https://www.ncbi.nlm.nih.gov/pubmed/23730305 http://dx.doi.org/10.3389/fgene.2013.00084 |
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