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PathoPhenoDB, linking human pathogens to their phenotypes in support of infectious disease research
Understanding the relationship between the pathophysiology of infectious disease, the biology of the causative agent and the development of therapeutic and diagnostic approaches is dependent on the synthesis of a wide range of types of information. Provision of a comprehensive and integrated disease...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6546783/ https://www.ncbi.nlm.nih.gov/pubmed/31160594 http://dx.doi.org/10.1038/s41597-019-0090-x |
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author | Kafkas, Şenay Abdelhakim, Marwa Hashish, Yasmeen Kulmanov, Maxat Abdellatif, Marwa Schofield, Paul N. Hoehndorf, Robert |
author_facet | Kafkas, Şenay Abdelhakim, Marwa Hashish, Yasmeen Kulmanov, Maxat Abdellatif, Marwa Schofield, Paul N. Hoehndorf, Robert |
author_sort | Kafkas, Şenay |
collection | PubMed |
description | Understanding the relationship between the pathophysiology of infectious disease, the biology of the causative agent and the development of therapeutic and diagnostic approaches is dependent on the synthesis of a wide range of types of information. Provision of a comprehensive and integrated disease phenotype knowledgebase has the potential to provide novel and orthogonal sources of information for the understanding of infectious agent pathogenesis, and support for research on disease mechanisms. We have developed PathoPhenoDB, a database containing pathogen-to-phenotype associations. PathoPhenoDB relies on manual curation of pathogen-disease relations, on ontology-based text mining as well as manual curation to associate host disease phenotypes with infectious agents. Using Semantic Web technologies, PathoPhenoDB also links to knowledge about drug resistance mechanisms and drugs used in the treatment of infectious diseases. PathoPhenoDB is accessible at http://patho.phenomebrowser.net/, and the data are freely available through a public SPARQL endpoint. |
format | Online Article Text |
id | pubmed-6546783 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-65467832019-06-17 PathoPhenoDB, linking human pathogens to their phenotypes in support of infectious disease research Kafkas, Şenay Abdelhakim, Marwa Hashish, Yasmeen Kulmanov, Maxat Abdellatif, Marwa Schofield, Paul N. Hoehndorf, Robert Sci Data Data Descriptor Understanding the relationship between the pathophysiology of infectious disease, the biology of the causative agent and the development of therapeutic and diagnostic approaches is dependent on the synthesis of a wide range of types of information. Provision of a comprehensive and integrated disease phenotype knowledgebase has the potential to provide novel and orthogonal sources of information for the understanding of infectious agent pathogenesis, and support for research on disease mechanisms. We have developed PathoPhenoDB, a database containing pathogen-to-phenotype associations. PathoPhenoDB relies on manual curation of pathogen-disease relations, on ontology-based text mining as well as manual curation to associate host disease phenotypes with infectious agents. Using Semantic Web technologies, PathoPhenoDB also links to knowledge about drug resistance mechanisms and drugs used in the treatment of infectious diseases. PathoPhenoDB is accessible at http://patho.phenomebrowser.net/, and the data are freely available through a public SPARQL endpoint. Nature Publishing Group UK 2019-06-03 /pmc/articles/PMC6546783/ /pubmed/31160594 http://dx.doi.org/10.1038/s41597-019-0090-x Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Kafkas, Şenay Abdelhakim, Marwa Hashish, Yasmeen Kulmanov, Maxat Abdellatif, Marwa Schofield, Paul N. Hoehndorf, Robert PathoPhenoDB, linking human pathogens to their phenotypes in support of infectious disease research |
title | PathoPhenoDB, linking human pathogens to their phenotypes in support of infectious disease research |
title_full | PathoPhenoDB, linking human pathogens to their phenotypes in support of infectious disease research |
title_fullStr | PathoPhenoDB, linking human pathogens to their phenotypes in support of infectious disease research |
title_full_unstemmed | PathoPhenoDB, linking human pathogens to their phenotypes in support of infectious disease research |
title_short | PathoPhenoDB, linking human pathogens to their phenotypes in support of infectious disease research |
title_sort | pathophenodb, linking human pathogens to their phenotypes in support of infectious disease research |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6546783/ https://www.ncbi.nlm.nih.gov/pubmed/31160594 http://dx.doi.org/10.1038/s41597-019-0090-x |
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