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The ConsensusPathDB interaction database: 2013 update
Knowledge of the various interactions between molecules in the cell is crucial for understanding cellular processes in health and disease. Currently available interaction databases, being largely complementary to each other, must be integrated to obtain a comprehensive global map of the different ty...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531102/ https://www.ncbi.nlm.nih.gov/pubmed/23143270 http://dx.doi.org/10.1093/nar/gks1055 |
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author | Kamburov, Atanas Stelzl, Ulrich Lehrach, Hans Herwig, Ralf |
author_facet | Kamburov, Atanas Stelzl, Ulrich Lehrach, Hans Herwig, Ralf |
author_sort | Kamburov, Atanas |
collection | PubMed |
description | Knowledge of the various interactions between molecules in the cell is crucial for understanding cellular processes in health and disease. Currently available interaction databases, being largely complementary to each other, must be integrated to obtain a comprehensive global map of the different types of interactions. We have previously reported the development of an integrative interaction database called ConsensusPathDB (http://ConsensusPathDB.org) that aims to fulfill this task. In this update article, we report its significant progress in terms of interaction content and web interface tools. ConsensusPathDB has grown mainly due to the integration of 12 further databases; it now contains 215 541 unique interactions and 4601 pathways from overall 30 databases. Binary protein interactions are scored with our confidence assessment tool, IntScore. The ConsensusPathDB web interface allows users to take advantage of these integrated interaction and pathway data in different contexts. Recent developments include pathway analysis of metabolite lists, visualization of functional gene/metabolite sets as overlap graphs, gene set analysis based on protein complexes and induced network modules analysis that connects a list of genes through various interaction types. To facilitate the interactive, visual interpretation of interaction and pathway data, we have re-implemented the graph visualization feature of ConsensusPathDB using the Cytoscape.js library. |
format | Online Article Text |
id | pubmed-3531102 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-35311022013-01-03 The ConsensusPathDB interaction database: 2013 update Kamburov, Atanas Stelzl, Ulrich Lehrach, Hans Herwig, Ralf Nucleic Acids Res Articles Knowledge of the various interactions between molecules in the cell is crucial for understanding cellular processes in health and disease. Currently available interaction databases, being largely complementary to each other, must be integrated to obtain a comprehensive global map of the different types of interactions. We have previously reported the development of an integrative interaction database called ConsensusPathDB (http://ConsensusPathDB.org) that aims to fulfill this task. In this update article, we report its significant progress in terms of interaction content and web interface tools. ConsensusPathDB has grown mainly due to the integration of 12 further databases; it now contains 215 541 unique interactions and 4601 pathways from overall 30 databases. Binary protein interactions are scored with our confidence assessment tool, IntScore. The ConsensusPathDB web interface allows users to take advantage of these integrated interaction and pathway data in different contexts. Recent developments include pathway analysis of metabolite lists, visualization of functional gene/metabolite sets as overlap graphs, gene set analysis based on protein complexes and induced network modules analysis that connects a list of genes through various interaction types. To facilitate the interactive, visual interpretation of interaction and pathway data, we have re-implemented the graph visualization feature of ConsensusPathDB using the Cytoscape.js library. Oxford University Press 2013-01 2012-11-10 /pmc/articles/PMC3531102/ /pubmed/23143270 http://dx.doi.org/10.1093/nar/gks1055 Text en © The Author(s) 2012. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com. |
spellingShingle | Articles Kamburov, Atanas Stelzl, Ulrich Lehrach, Hans Herwig, Ralf The ConsensusPathDB interaction database: 2013 update |
title | The ConsensusPathDB interaction database: 2013 update |
title_full | The ConsensusPathDB interaction database: 2013 update |
title_fullStr | The ConsensusPathDB interaction database: 2013 update |
title_full_unstemmed | The ConsensusPathDB interaction database: 2013 update |
title_short | The ConsensusPathDB interaction database: 2013 update |
title_sort | consensuspathdb interaction database: 2013 update |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531102/ https://www.ncbi.nlm.nih.gov/pubmed/23143270 http://dx.doi.org/10.1093/nar/gks1055 |
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