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Payao: a community platform for SBML pathway model curation

Summary: Payao is a community-based, collaborative web service platform for gene-regulatory and biochemical pathway model curation. The system combines Web 2.0 technologies and online model visualization functions to enable a collaborative community to annotate and curate biological models. Payao re...

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Detalles Bibliográficos
Autores principales: Matsuoka, Yukiko, Ghosh, Samik, Kikuchi, Norihiro, Kitano, Hiroaki
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2865864/
https://www.ncbi.nlm.nih.gov/pubmed/20371497
http://dx.doi.org/10.1093/bioinformatics/btq143
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author Matsuoka, Yukiko
Ghosh, Samik
Kikuchi, Norihiro
Kitano, Hiroaki
author_facet Matsuoka, Yukiko
Ghosh, Samik
Kikuchi, Norihiro
Kitano, Hiroaki
author_sort Matsuoka, Yukiko
collection PubMed
description Summary: Payao is a community-based, collaborative web service platform for gene-regulatory and biochemical pathway model curation. The system combines Web 2.0 technologies and online model visualization functions to enable a collaborative community to annotate and curate biological models. Payao reads the models in Systems Biology Markup Language format, displays them with CellDesigner, a process diagram editor, which complies with the Systems Biology Graphical Notation, and provides an interface for model enrichment (adding tags and comments to the models) for the access-controlled community members. Availability and implementation: Freely available for model curation service at http://www.payaologue.org. Web site implemented in Seaser Framework 2.0 with S2Flex2, MySQL 5.0 and Tomcat 5.5, with all major browsers supported. Contact: kitano@sbi.jp
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spelling pubmed-28658642010-05-10 Payao: a community platform for SBML pathway model curation Matsuoka, Yukiko Ghosh, Samik Kikuchi, Norihiro Kitano, Hiroaki Bioinformatics Applications Note Summary: Payao is a community-based, collaborative web service platform for gene-regulatory and biochemical pathway model curation. The system combines Web 2.0 technologies and online model visualization functions to enable a collaborative community to annotate and curate biological models. Payao reads the models in Systems Biology Markup Language format, displays them with CellDesigner, a process diagram editor, which complies with the Systems Biology Graphical Notation, and provides an interface for model enrichment (adding tags and comments to the models) for the access-controlled community members. Availability and implementation: Freely available for model curation service at http://www.payaologue.org. Web site implemented in Seaser Framework 2.0 with S2Flex2, MySQL 5.0 and Tomcat 5.5, with all major browsers supported. Contact: kitano@sbi.jp Oxford University Press 2010-05-15 2010-04-05 /pmc/articles/PMC2865864/ /pubmed/20371497 http://dx.doi.org/10.1093/bioinformatics/btq143 Text en © The Author 2010. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Matsuoka, Yukiko
Ghosh, Samik
Kikuchi, Norihiro
Kitano, Hiroaki
Payao: a community platform for SBML pathway model curation
title Payao: a community platform for SBML pathway model curation
title_full Payao: a community platform for SBML pathway model curation
title_fullStr Payao: a community platform for SBML pathway model curation
title_full_unstemmed Payao: a community platform for SBML pathway model curation
title_short Payao: a community platform for SBML pathway model curation
title_sort payao: a community platform for sbml pathway model curation
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2865864/
https://www.ncbi.nlm.nih.gov/pubmed/20371497
http://dx.doi.org/10.1093/bioinformatics/btq143
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