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Molecular Interaction Search Tool (MIST): an integrated resource for mining gene and protein interaction data
Model organism and human databases are rich with information about genetic and physical interactions. These data can be used to interpret and guide the analysis of results from new studies and develop new hypotheses. Here, we report the development of the Molecular Interaction Search Tool (MIST; htt...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5753374/ https://www.ncbi.nlm.nih.gov/pubmed/29155944 http://dx.doi.org/10.1093/nar/gkx1116 |
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author | Hu, Yanhui Vinayagam, Arunachalam Nand, Ankita Comjean, Aram Chung, Verena Hao, Tong Mohr, Stephanie E Perrimon, Norbert |
author_facet | Hu, Yanhui Vinayagam, Arunachalam Nand, Ankita Comjean, Aram Chung, Verena Hao, Tong Mohr, Stephanie E Perrimon, Norbert |
author_sort | Hu, Yanhui |
collection | PubMed |
description | Model organism and human databases are rich with information about genetic and physical interactions. These data can be used to interpret and guide the analysis of results from new studies and develop new hypotheses. Here, we report the development of the Molecular Interaction Search Tool (MIST; http://fgrtools.hms.harvard.edu/MIST/). The MIST database integrates biological interaction data from yeast, nematode, fly, zebrafish, frog, rat and mouse model systems, as well as human. For individual or short gene lists, the MIST user interface can be used to identify interacting partners based on protein–protein and genetic interaction (GI) data from the species of interest as well as inferred interactions, known as interologs, and to view a corresponding network. The data, interologs and search tools at MIST are also useful for analyzing ‘omics datasets. In addition to describing the integrated database, we also demonstrate how MIST can be used to identify an appropriate cut-off value that balances false positive and negative discovery, and present use-cases for additional types of analysis. Altogether, the MIST database and search tools support visualization and navigation of existing protein and GI data, as well as comparison of new and existing data. |
format | Online Article Text |
id | pubmed-5753374 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-57533742018-01-05 Molecular Interaction Search Tool (MIST): an integrated resource for mining gene and protein interaction data Hu, Yanhui Vinayagam, Arunachalam Nand, Ankita Comjean, Aram Chung, Verena Hao, Tong Mohr, Stephanie E Perrimon, Norbert Nucleic Acids Res Database Issue Model organism and human databases are rich with information about genetic and physical interactions. These data can be used to interpret and guide the analysis of results from new studies and develop new hypotheses. Here, we report the development of the Molecular Interaction Search Tool (MIST; http://fgrtools.hms.harvard.edu/MIST/). The MIST database integrates biological interaction data from yeast, nematode, fly, zebrafish, frog, rat and mouse model systems, as well as human. For individual or short gene lists, the MIST user interface can be used to identify interacting partners based on protein–protein and genetic interaction (GI) data from the species of interest as well as inferred interactions, known as interologs, and to view a corresponding network. The data, interologs and search tools at MIST are also useful for analyzing ‘omics datasets. In addition to describing the integrated database, we also demonstrate how MIST can be used to identify an appropriate cut-off value that balances false positive and negative discovery, and present use-cases for additional types of analysis. Altogether, the MIST database and search tools support visualization and navigation of existing protein and GI data, as well as comparison of new and existing data. Oxford University Press 2018-01-04 2017-11-16 /pmc/articles/PMC5753374/ /pubmed/29155944 http://dx.doi.org/10.1093/nar/gkx1116 Text en © The Author(s) 2017. 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 | Database Issue Hu, Yanhui Vinayagam, Arunachalam Nand, Ankita Comjean, Aram Chung, Verena Hao, Tong Mohr, Stephanie E Perrimon, Norbert Molecular Interaction Search Tool (MIST): an integrated resource for mining gene and protein interaction data |
title | Molecular Interaction Search Tool (MIST): an integrated resource for mining gene and protein interaction data |
title_full | Molecular Interaction Search Tool (MIST): an integrated resource for mining gene and protein interaction data |
title_fullStr | Molecular Interaction Search Tool (MIST): an integrated resource for mining gene and protein interaction data |
title_full_unstemmed | Molecular Interaction Search Tool (MIST): an integrated resource for mining gene and protein interaction data |
title_short | Molecular Interaction Search Tool (MIST): an integrated resource for mining gene and protein interaction data |
title_sort | molecular interaction search tool (mist): an integrated resource for mining gene and protein interaction data |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5753374/ https://www.ncbi.nlm.nih.gov/pubmed/29155944 http://dx.doi.org/10.1093/nar/gkx1116 |
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