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TOPSAN: a dynamic web database for structural genomics

The Open Protein Structure Annotation Network (TOPSAN) is a web-based collaboration platform for exploring and annotating structures determined by structural genomics efforts. Characterization of those structures presents a challenge since the majority of the proteins themselves have not yet been ch...

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Detalles Bibliográficos
Autores principales: Ellrott, Kyle, Zmasek, Christian M., Weekes, Dana, Sri Krishna, S., Bakolitsa, Constantina, Godzik, Adam, Wooley, John
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3013775/
https://www.ncbi.nlm.nih.gov/pubmed/20961957
http://dx.doi.org/10.1093/nar/gkq902
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author Ellrott, Kyle
Zmasek, Christian M.
Weekes, Dana
Sri Krishna, S.
Bakolitsa, Constantina
Godzik, Adam
Wooley, John
author_facet Ellrott, Kyle
Zmasek, Christian M.
Weekes, Dana
Sri Krishna, S.
Bakolitsa, Constantina
Godzik, Adam
Wooley, John
author_sort Ellrott, Kyle
collection PubMed
description The Open Protein Structure Annotation Network (TOPSAN) is a web-based collaboration platform for exploring and annotating structures determined by structural genomics efforts. Characterization of those structures presents a challenge since the majority of the proteins themselves have not yet been characterized. Responding to this challenge, the TOPSAN platform facilitates collaborative annotation and investigation via a user-friendly web-based interface pre-populated with automatically generated information. Semantic web technologies expand and enrich TOPSAN’s content through links to larger sets of related databases, and thus, enable data integration from disparate sources and data mining via conventional query languages. TOPSAN can be found at http://www.topsan.org.
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spelling pubmed-30137752011-01-03 TOPSAN: a dynamic web database for structural genomics Ellrott, Kyle Zmasek, Christian M. Weekes, Dana Sri Krishna, S. Bakolitsa, Constantina Godzik, Adam Wooley, John Nucleic Acids Res Articles The Open Protein Structure Annotation Network (TOPSAN) is a web-based collaboration platform for exploring and annotating structures determined by structural genomics efforts. Characterization of those structures presents a challenge since the majority of the proteins themselves have not yet been characterized. Responding to this challenge, the TOPSAN platform facilitates collaborative annotation and investigation via a user-friendly web-based interface pre-populated with automatically generated information. Semantic web technologies expand and enrich TOPSAN’s content through links to larger sets of related databases, and thus, enable data integration from disparate sources and data mining via conventional query languages. TOPSAN can be found at http://www.topsan.org. Oxford University Press 2011-01 2010-10-20 /pmc/articles/PMC3013775/ /pubmed/20961957 http://dx.doi.org/10.1093/nar/gkq902 Text en © The Author(s) 2010. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.5 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 Articles
Ellrott, Kyle
Zmasek, Christian M.
Weekes, Dana
Sri Krishna, S.
Bakolitsa, Constantina
Godzik, Adam
Wooley, John
TOPSAN: a dynamic web database for structural genomics
title TOPSAN: a dynamic web database for structural genomics
title_full TOPSAN: a dynamic web database for structural genomics
title_fullStr TOPSAN: a dynamic web database for structural genomics
title_full_unstemmed TOPSAN: a dynamic web database for structural genomics
title_short TOPSAN: a dynamic web database for structural genomics
title_sort topsan: a dynamic web database for structural genomics
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3013775/
https://www.ncbi.nlm.nih.gov/pubmed/20961957
http://dx.doi.org/10.1093/nar/gkq902
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