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Crowdsourcing the nodulation gene network discovery environment

BACKGROUND: The Legumes (Fabaceae) are an economically and ecologically important group of plant species with the conspicuous capacity for symbiotic nitrogen fixation in root nodules, specialized plant organs containing symbiotic microbes. With the aim of understanding the underlying molecular mecha...

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Detalles Bibliográficos
Autores principales: Li, Yupeng, Jackson, Scott A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4880984/
https://www.ncbi.nlm.nih.gov/pubmed/27230384
http://dx.doi.org/10.1186/s12859-016-1089-3
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author Li, Yupeng
Jackson, Scott A.
author_facet Li, Yupeng
Jackson, Scott A.
author_sort Li, Yupeng
collection PubMed
description BACKGROUND: The Legumes (Fabaceae) are an economically and ecologically important group of plant species with the conspicuous capacity for symbiotic nitrogen fixation in root nodules, specialized plant organs containing symbiotic microbes. With the aim of understanding the underlying molecular mechanisms leading to nodulation, many efforts are underway to identify nodulation-related genes and determine how these genes interact with each other. In order to accurately and efficiently reconstruct nodulation gene network, a crowdsourcing platform, CrowdNodNet, was created. RESULTS: The platform implements the jQuery and vis.js JavaScript libraries, so that users are able to interactively visualize and edit the gene network, and easily access the information about the network, e.g. gene lists, gene interactions and gene functional annotations. In addition, all the gene information is written on MediaWiki pages, enabling users to edit and contribute to the network curation. CONCLUSIONS: Utilizing the continuously updated, collaboratively written, and community-reviewed Wikipedia model, the platform could, in a short time, become a comprehensive knowledge base of nodulation-related pathways. The platform could also be used for other biological processes, and thus has great potential for integrating and advancing our understanding of the functional genomics and systems biology of any process for any species. The platform is available at http://crowd.bioops.info/, and the source code can be openly accessed at https://github.com/bioops/crowdnodnet under MIT License.
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spelling pubmed-48809842016-06-07 Crowdsourcing the nodulation gene network discovery environment Li, Yupeng Jackson, Scott A. BMC Bioinformatics Software BACKGROUND: The Legumes (Fabaceae) are an economically and ecologically important group of plant species with the conspicuous capacity for symbiotic nitrogen fixation in root nodules, specialized plant organs containing symbiotic microbes. With the aim of understanding the underlying molecular mechanisms leading to nodulation, many efforts are underway to identify nodulation-related genes and determine how these genes interact with each other. In order to accurately and efficiently reconstruct nodulation gene network, a crowdsourcing platform, CrowdNodNet, was created. RESULTS: The platform implements the jQuery and vis.js JavaScript libraries, so that users are able to interactively visualize and edit the gene network, and easily access the information about the network, e.g. gene lists, gene interactions and gene functional annotations. In addition, all the gene information is written on MediaWiki pages, enabling users to edit and contribute to the network curation. CONCLUSIONS: Utilizing the continuously updated, collaboratively written, and community-reviewed Wikipedia model, the platform could, in a short time, become a comprehensive knowledge base of nodulation-related pathways. The platform could also be used for other biological processes, and thus has great potential for integrating and advancing our understanding of the functional genomics and systems biology of any process for any species. The platform is available at http://crowd.bioops.info/, and the source code can be openly accessed at https://github.com/bioops/crowdnodnet under MIT License. BioMed Central 2016-05-26 /pmc/articles/PMC4880984/ /pubmed/27230384 http://dx.doi.org/10.1186/s12859-016-1089-3 Text en © Li and Jackson. 2016 Open AccessThis 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 Software
Li, Yupeng
Jackson, Scott A.
Crowdsourcing the nodulation gene network discovery environment
title Crowdsourcing the nodulation gene network discovery environment
title_full Crowdsourcing the nodulation gene network discovery environment
title_fullStr Crowdsourcing the nodulation gene network discovery environment
title_full_unstemmed Crowdsourcing the nodulation gene network discovery environment
title_short Crowdsourcing the nodulation gene network discovery environment
title_sort crowdsourcing the nodulation gene network discovery environment
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4880984/
https://www.ncbi.nlm.nih.gov/pubmed/27230384
http://dx.doi.org/10.1186/s12859-016-1089-3
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