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Disbiome database: linking the microbiome to disease
BACKGROUND: Recent research has provided fascinating indications and evidence that the host health is linked to its microbial inhabitants. Due to the development of high-throughput sequencing technologies, more and more data covering microbial composition changes in different disease types are emerg...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5987391/ https://www.ncbi.nlm.nih.gov/pubmed/29866037 http://dx.doi.org/10.1186/s12866-018-1197-5 |
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author | Janssens, Yorick Nielandt, Joachim Bronselaer, Antoon Debunne, Nathan Verbeke, Frederick Wynendaele, Evelien Van Immerseel, Filip Vandewynckel, Yves-Paul De Tré, Guy De Spiegeleer, Bart |
author_facet | Janssens, Yorick Nielandt, Joachim Bronselaer, Antoon Debunne, Nathan Verbeke, Frederick Wynendaele, Evelien Van Immerseel, Filip Vandewynckel, Yves-Paul De Tré, Guy De Spiegeleer, Bart |
author_sort | Janssens, Yorick |
collection | PubMed |
description | BACKGROUND: Recent research has provided fascinating indications and evidence that the host health is linked to its microbial inhabitants. Due to the development of high-throughput sequencing technologies, more and more data covering microbial composition changes in different disease types are emerging. However, this information is dispersed over a wide variety of medical and biomedical disciplines. DESCRIPTION: Disbiome is a database which collects and presents published microbiota-disease information in a standardized way. The diseases are classified using the MedDRA classification system and the micro-organisms are linked to their NCBI and SILVA taxonomy. Finally, each study included in the Disbiome database is assessed for its reporting quality using a standardized questionnaire. CONCLUSIONS: Disbiome is the first database giving a clear, concise and up-to-date overview of microbial composition differences in diseases, together with the relevant information of the studies published. The strength of this database lies within the combination of the presence of references to other databases, which enables both specific and diverse search strategies within the Disbiome database, and the human annotation which ensures a simple and structured presentation of the available data. |
format | Online Article Text |
id | pubmed-5987391 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-59873912018-07-10 Disbiome database: linking the microbiome to disease Janssens, Yorick Nielandt, Joachim Bronselaer, Antoon Debunne, Nathan Verbeke, Frederick Wynendaele, Evelien Van Immerseel, Filip Vandewynckel, Yves-Paul De Tré, Guy De Spiegeleer, Bart BMC Microbiol Database BACKGROUND: Recent research has provided fascinating indications and evidence that the host health is linked to its microbial inhabitants. Due to the development of high-throughput sequencing technologies, more and more data covering microbial composition changes in different disease types are emerging. However, this information is dispersed over a wide variety of medical and biomedical disciplines. DESCRIPTION: Disbiome is a database which collects and presents published microbiota-disease information in a standardized way. The diseases are classified using the MedDRA classification system and the micro-organisms are linked to their NCBI and SILVA taxonomy. Finally, each study included in the Disbiome database is assessed for its reporting quality using a standardized questionnaire. CONCLUSIONS: Disbiome is the first database giving a clear, concise and up-to-date overview of microbial composition differences in diseases, together with the relevant information of the studies published. The strength of this database lies within the combination of the presence of references to other databases, which enables both specific and diverse search strategies within the Disbiome database, and the human annotation which ensures a simple and structured presentation of the available data. BioMed Central 2018-06-04 /pmc/articles/PMC5987391/ /pubmed/29866037 http://dx.doi.org/10.1186/s12866-018-1197-5 Text en © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Database Janssens, Yorick Nielandt, Joachim Bronselaer, Antoon Debunne, Nathan Verbeke, Frederick Wynendaele, Evelien Van Immerseel, Filip Vandewynckel, Yves-Paul De Tré, Guy De Spiegeleer, Bart Disbiome database: linking the microbiome to disease |
title | Disbiome database: linking the microbiome to disease |
title_full | Disbiome database: linking the microbiome to disease |
title_fullStr | Disbiome database: linking the microbiome to disease |
title_full_unstemmed | Disbiome database: linking the microbiome to disease |
title_short | Disbiome database: linking the microbiome to disease |
title_sort | disbiome database: linking the microbiome to disease |
topic | Database |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5987391/ https://www.ncbi.nlm.nih.gov/pubmed/29866037 http://dx.doi.org/10.1186/s12866-018-1197-5 |
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