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IMP 2.0: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks
IMP (Integrative Multi-species Prediction), originally released in 2012, is an interactive web server that enables molecular biologists to interpret experimental results and to generate hypotheses in the context of a large cross-organism compendium of functional predictions and networks. The system...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4489318/ https://www.ncbi.nlm.nih.gov/pubmed/25969450 http://dx.doi.org/10.1093/nar/gkv486 |
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author | Wong, Aaron K. Krishnan, Arjun Yao, Victoria Tadych, Alicja Troyanskaya, Olga G. |
author_facet | Wong, Aaron K. Krishnan, Arjun Yao, Victoria Tadych, Alicja Troyanskaya, Olga G. |
author_sort | Wong, Aaron K. |
collection | PubMed |
description | IMP (Integrative Multi-species Prediction), originally released in 2012, is an interactive web server that enables molecular biologists to interpret experimental results and to generate hypotheses in the context of a large cross-organism compendium of functional predictions and networks. The system provides biologists with a framework to analyze their candidate gene sets in the context of functional networks, expanding or refining their sets using functional relationships predicted from integrated high-throughput data. IMP 2.0 integrates updated prior knowledge and data collections from the last three years in the seven supported organisms (Homo sapiens, Mus musculus, Rattus norvegicus, Drosophila melanogaster, Danio rerio, Caenorhabditis elegans, and Saccharomyces cerevisiae) and extends function prediction coverage to include human disease. IMP identifies homologs with conserved functional roles for disease knowledge transfer, allowing biologists to analyze disease contexts and predictions across all organisms. Additionally, IMP 2.0 implements a new flexible platform for experts to generate custom hypotheses about biological processes or diseases, making sophisticated data-driven methods easily accessible to researchers. IMP does not require any registration or installation and is freely available for use at http://imp.princeton.edu. |
format | Online Article Text |
id | pubmed-4489318 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-44893182015-07-07 IMP 2.0: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks Wong, Aaron K. Krishnan, Arjun Yao, Victoria Tadych, Alicja Troyanskaya, Olga G. Nucleic Acids Res Web Server issue IMP (Integrative Multi-species Prediction), originally released in 2012, is an interactive web server that enables molecular biologists to interpret experimental results and to generate hypotheses in the context of a large cross-organism compendium of functional predictions and networks. The system provides biologists with a framework to analyze their candidate gene sets in the context of functional networks, expanding or refining their sets using functional relationships predicted from integrated high-throughput data. IMP 2.0 integrates updated prior knowledge and data collections from the last three years in the seven supported organisms (Homo sapiens, Mus musculus, Rattus norvegicus, Drosophila melanogaster, Danio rerio, Caenorhabditis elegans, and Saccharomyces cerevisiae) and extends function prediction coverage to include human disease. IMP identifies homologs with conserved functional roles for disease knowledge transfer, allowing biologists to analyze disease contexts and predictions across all organisms. Additionally, IMP 2.0 implements a new flexible platform for experts to generate custom hypotheses about biological processes or diseases, making sophisticated data-driven methods easily accessible to researchers. IMP does not require any registration or installation and is freely available for use at http://imp.princeton.edu. Oxford University Press 2015-07-01 2015-05-12 /pmc/articles/PMC4489318/ /pubmed/25969450 http://dx.doi.org/10.1093/nar/gkv486 Text en © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Web Server issue Wong, Aaron K. Krishnan, Arjun Yao, Victoria Tadych, Alicja Troyanskaya, Olga G. IMP 2.0: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks |
title | IMP 2.0: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks |
title_full | IMP 2.0: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks |
title_fullStr | IMP 2.0: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks |
title_full_unstemmed | IMP 2.0: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks |
title_short | IMP 2.0: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks |
title_sort | imp 2.0: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks |
topic | Web Server issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4489318/ https://www.ncbi.nlm.nih.gov/pubmed/25969450 http://dx.doi.org/10.1093/nar/gkv486 |
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