Cargando…
mapMECFS: a portal to enhance data discovery across biological disciplines and collaborative sites
BACKGROUND: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating disease which involves multiple body systems (e.g., immune, nervous, digestive, circulatory) and research domains (e.g., immunology, metabolomics, the gut microbiome, genomics, neurology). Despite several decad...
Autores principales: | , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8576927/ https://www.ncbi.nlm.nih.gov/pubmed/34749736 http://dx.doi.org/10.1186/s12967-021-03127-3 |
_version_ | 1784595976623751168 |
---|---|
author | Mathur, Ravi Carnes, Megan U. Harding, Alexander Moore, Amy Thomas, Ian Giarrocco, Alex Long, Michael Underwood, Marcia Townsend, Christopher Ruiz-Esparza, Roman Barnette, Quinn Brown, Linda Morris Schu, Matthew |
author_facet | Mathur, Ravi Carnes, Megan U. Harding, Alexander Moore, Amy Thomas, Ian Giarrocco, Alex Long, Michael Underwood, Marcia Townsend, Christopher Ruiz-Esparza, Roman Barnette, Quinn Brown, Linda Morris Schu, Matthew |
author_sort | Mathur, Ravi |
collection | PubMed |
description | BACKGROUND: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating disease which involves multiple body systems (e.g., immune, nervous, digestive, circulatory) and research domains (e.g., immunology, metabolomics, the gut microbiome, genomics, neurology). Despite several decades of research, there are no established ME/CFS biomarkers available to diagnose and treat ME/CFS. Sharing data and integrating findings across these domains is essential to advance understanding of this complex disease by revealing diagnostic biomarkers and facilitating discovery of novel effective therapies. METHODS: The National Institutes of Health funded the development of a data sharing portal to support collaborative efforts among an initial group of three funded research centers. This was subsequently expanded to include the global ME/CFS research community. Using the open-source comprehensive knowledge archive network (CKAN) framework as the base, the ME/CFS Data Management and Coordinating Center developed an online portal with metadata collection, smart search capabilities, and domain-agnostic data integration to support data findability and reusability while reducing the barriers to sustainable data sharing. RESULTS: We designed the mapMECFS data portal to facilitate data sharing and integration by allowing ME/CFS researchers to browse, share, compare, and download molecular datasets from within one data repository. At the time of publication, mapMECFS contains data curated from public data repositories, peer-reviewed publications, and current ME/CFS Research Network members. CONCLUSIONS: mapMECFS is a disease-specific data portal to improve data sharing and collaboration among ME/CFS researchers around the world. mapMECFS is accessible to the broader research community with registration. Further development is ongoing to include novel systems biology and data integration methods. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-021-03127-3. |
format | Online Article Text |
id | pubmed-8576927 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-85769272021-11-10 mapMECFS: a portal to enhance data discovery across biological disciplines and collaborative sites Mathur, Ravi Carnes, Megan U. Harding, Alexander Moore, Amy Thomas, Ian Giarrocco, Alex Long, Michael Underwood, Marcia Townsend, Christopher Ruiz-Esparza, Roman Barnette, Quinn Brown, Linda Morris Schu, Matthew J Transl Med Research BACKGROUND: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating disease which involves multiple body systems (e.g., immune, nervous, digestive, circulatory) and research domains (e.g., immunology, metabolomics, the gut microbiome, genomics, neurology). Despite several decades of research, there are no established ME/CFS biomarkers available to diagnose and treat ME/CFS. Sharing data and integrating findings across these domains is essential to advance understanding of this complex disease by revealing diagnostic biomarkers and facilitating discovery of novel effective therapies. METHODS: The National Institutes of Health funded the development of a data sharing portal to support collaborative efforts among an initial group of three funded research centers. This was subsequently expanded to include the global ME/CFS research community. Using the open-source comprehensive knowledge archive network (CKAN) framework as the base, the ME/CFS Data Management and Coordinating Center developed an online portal with metadata collection, smart search capabilities, and domain-agnostic data integration to support data findability and reusability while reducing the barriers to sustainable data sharing. RESULTS: We designed the mapMECFS data portal to facilitate data sharing and integration by allowing ME/CFS researchers to browse, share, compare, and download molecular datasets from within one data repository. At the time of publication, mapMECFS contains data curated from public data repositories, peer-reviewed publications, and current ME/CFS Research Network members. CONCLUSIONS: mapMECFS is a disease-specific data portal to improve data sharing and collaboration among ME/CFS researchers around the world. mapMECFS is accessible to the broader research community with registration. Further development is ongoing to include novel systems biology and data integration methods. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-021-03127-3. BioMed Central 2021-11-08 /pmc/articles/PMC8576927/ /pubmed/34749736 http://dx.doi.org/10.1186/s12967-021-03127-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Mathur, Ravi Carnes, Megan U. Harding, Alexander Moore, Amy Thomas, Ian Giarrocco, Alex Long, Michael Underwood, Marcia Townsend, Christopher Ruiz-Esparza, Roman Barnette, Quinn Brown, Linda Morris Schu, Matthew mapMECFS: a portal to enhance data discovery across biological disciplines and collaborative sites |
title | mapMECFS: a portal to enhance data discovery across biological disciplines and collaborative sites |
title_full | mapMECFS: a portal to enhance data discovery across biological disciplines and collaborative sites |
title_fullStr | mapMECFS: a portal to enhance data discovery across biological disciplines and collaborative sites |
title_full_unstemmed | mapMECFS: a portal to enhance data discovery across biological disciplines and collaborative sites |
title_short | mapMECFS: a portal to enhance data discovery across biological disciplines and collaborative sites |
title_sort | mapmecfs: a portal to enhance data discovery across biological disciplines and collaborative sites |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8576927/ https://www.ncbi.nlm.nih.gov/pubmed/34749736 http://dx.doi.org/10.1186/s12967-021-03127-3 |
work_keys_str_mv | AT mathurravi mapmecfsaportaltoenhancedatadiscoveryacrossbiologicaldisciplinesandcollaborativesites AT carnesmeganu mapmecfsaportaltoenhancedatadiscoveryacrossbiologicaldisciplinesandcollaborativesites AT hardingalexander mapmecfsaportaltoenhancedatadiscoveryacrossbiologicaldisciplinesandcollaborativesites AT mooreamy mapmecfsaportaltoenhancedatadiscoveryacrossbiologicaldisciplinesandcollaborativesites AT thomasian mapmecfsaportaltoenhancedatadiscoveryacrossbiologicaldisciplinesandcollaborativesites AT giarroccoalex mapmecfsaportaltoenhancedatadiscoveryacrossbiologicaldisciplinesandcollaborativesites AT longmichael mapmecfsaportaltoenhancedatadiscoveryacrossbiologicaldisciplinesandcollaborativesites AT underwoodmarcia mapmecfsaportaltoenhancedatadiscoveryacrossbiologicaldisciplinesandcollaborativesites AT townsendchristopher mapmecfsaportaltoenhancedatadiscoveryacrossbiologicaldisciplinesandcollaborativesites AT ruizesparzaroman mapmecfsaportaltoenhancedatadiscoveryacrossbiologicaldisciplinesandcollaborativesites AT barnettequinn mapmecfsaportaltoenhancedatadiscoveryacrossbiologicaldisciplinesandcollaborativesites AT brownlindamorris mapmecfsaportaltoenhancedatadiscoveryacrossbiologicaldisciplinesandcollaborativesites AT schumatthew mapmecfsaportaltoenhancedatadiscoveryacrossbiologicaldisciplinesandcollaborativesites |