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MalaCards: an integrated compendium for diseases and their annotation
Comprehensive disease classification, integration and annotation are crucial for biomedical discovery. At present, disease compilation is incomplete, heterogeneous and often lacking systematic inquiry mechanisms. We introduce MalaCards, an integrated database of human maladies and their annotations,...
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/PMC3625956/ https://www.ncbi.nlm.nih.gov/pubmed/23584832 http://dx.doi.org/10.1093/database/bat018 |
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author | Rappaport, Noa Nativ, Noam Stelzer, Gil Twik, Michal Guan-Golan, Yaron Iny Stein, Tsippi Bahir, Iris Belinky, Frida Morrey, C. Paul Safran, Marilyn Lancet, Doron |
author_facet | Rappaport, Noa Nativ, Noam Stelzer, Gil Twik, Michal Guan-Golan, Yaron Iny Stein, Tsippi Bahir, Iris Belinky, Frida Morrey, C. Paul Safran, Marilyn Lancet, Doron |
author_sort | Rappaport, Noa |
collection | PubMed |
description | Comprehensive disease classification, integration and annotation are crucial for biomedical discovery. At present, disease compilation is incomplete, heterogeneous and often lacking systematic inquiry mechanisms. We introduce MalaCards, an integrated database of human maladies and their annotations, modeled on the architecture and strategy of the GeneCards database of human genes. MalaCards mines and merges 44 data sources to generate a computerized card for each of 16 919 human diseases. Each MalaCard contains disease-specific prioritized annotations, as well as inter-disease connections, empowered by the GeneCards relational database, its searches and GeneDecks set analyses. First, we generate a disease list from 15 ranked sources, using disease-name unification heuristics. Next, we use four schemes to populate MalaCards sections: (i) directly interrogating disease resources, to establish integrated disease names, synonyms, summaries, drugs/therapeutics, clinical features, genetic tests and anatomical context; (ii) searching GeneCards for related publications, and for associated genes with corresponding relevance scores; (iii) analyzing disease-associated gene sets in GeneDecks to yield affiliated pathways, phenotypes, compounds and GO terms, sorted by a composite relevance score and presented with GeneCards links; and (iv) searching within MalaCards itself, e.g. for additional related diseases and anatomical context. The latter forms the basis for the construction of a disease network, based on shared MalaCards annotations, embodying associations based on etiology, clinical features and clinical conditions. This broadly disposed network has a power-law degree distribution, suggesting that this might be an inherent property of such networks. Work in progress includes hierarchical malady classification, ontological mapping and disease set analyses, striving to make MalaCards an even more effective tool for biomedical research. Database URL: http://www.malacards.org/ |
format | Online Article Text |
id | pubmed-3625956 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-36259562013-04-15 MalaCards: an integrated compendium for diseases and their annotation Rappaport, Noa Nativ, Noam Stelzer, Gil Twik, Michal Guan-Golan, Yaron Iny Stein, Tsippi Bahir, Iris Belinky, Frida Morrey, C. Paul Safran, Marilyn Lancet, Doron Database (Oxford) Original Article Comprehensive disease classification, integration and annotation are crucial for biomedical discovery. At present, disease compilation is incomplete, heterogeneous and often lacking systematic inquiry mechanisms. We introduce MalaCards, an integrated database of human maladies and their annotations, modeled on the architecture and strategy of the GeneCards database of human genes. MalaCards mines and merges 44 data sources to generate a computerized card for each of 16 919 human diseases. Each MalaCard contains disease-specific prioritized annotations, as well as inter-disease connections, empowered by the GeneCards relational database, its searches and GeneDecks set analyses. First, we generate a disease list from 15 ranked sources, using disease-name unification heuristics. Next, we use four schemes to populate MalaCards sections: (i) directly interrogating disease resources, to establish integrated disease names, synonyms, summaries, drugs/therapeutics, clinical features, genetic tests and anatomical context; (ii) searching GeneCards for related publications, and for associated genes with corresponding relevance scores; (iii) analyzing disease-associated gene sets in GeneDecks to yield affiliated pathways, phenotypes, compounds and GO terms, sorted by a composite relevance score and presented with GeneCards links; and (iv) searching within MalaCards itself, e.g. for additional related diseases and anatomical context. The latter forms the basis for the construction of a disease network, based on shared MalaCards annotations, embodying associations based on etiology, clinical features and clinical conditions. This broadly disposed network has a power-law degree distribution, suggesting that this might be an inherent property of such networks. Work in progress includes hierarchical malady classification, ontological mapping and disease set analyses, striving to make MalaCards an even more effective tool for biomedical research. Database URL: http://www.malacards.org/ Oxford University Press 2013-04-12 /pmc/articles/PMC3625956/ /pubmed/23584832 http://dx.doi.org/10.1093/database/bat018 Text en © The Author(s) 2013. 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 Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Rappaport, Noa Nativ, Noam Stelzer, Gil Twik, Michal Guan-Golan, Yaron Iny Stein, Tsippi Bahir, Iris Belinky, Frida Morrey, C. Paul Safran, Marilyn Lancet, Doron MalaCards: an integrated compendium for diseases and their annotation |
title | MalaCards: an integrated compendium for diseases and their annotation |
title_full | MalaCards: an integrated compendium for diseases and their annotation |
title_fullStr | MalaCards: an integrated compendium for diseases and their annotation |
title_full_unstemmed | MalaCards: an integrated compendium for diseases and their annotation |
title_short | MalaCards: an integrated compendium for diseases and their annotation |
title_sort | malacards: an integrated compendium for diseases and their annotation |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3625956/ https://www.ncbi.nlm.nih.gov/pubmed/23584832 http://dx.doi.org/10.1093/database/bat018 |
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