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SigCS base: an integrated genetic information resource for human cerebral stroke

BACKGROUND: To understand how stroke risk factors mechanistically contribute to stroke, the genetic components regulating each risk factor need to be integrated and evaluated with respect to biological function and through pathway-based algorithms. This resource will provide information to researche...

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Autores principales: Park, Young-Kyu, Bang, Ok Sun, Cha, Min-Ho, Kim, Jaeheup, Cole, John W, Lee, Doheon, Kim, Young Joo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287476/
https://www.ncbi.nlm.nih.gov/pubmed/22784567
http://dx.doi.org/10.1186/1752-0509-5-S2-S10
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author Park, Young-Kyu
Bang, Ok Sun
Cha, Min-Ho
Kim, Jaeheup
Cole, John W
Lee, Doheon
Kim, Young Joo
author_facet Park, Young-Kyu
Bang, Ok Sun
Cha, Min-Ho
Kim, Jaeheup
Cole, John W
Lee, Doheon
Kim, Young Joo
author_sort Park, Young-Kyu
collection PubMed
description BACKGROUND: To understand how stroke risk factors mechanistically contribute to stroke, the genetic components regulating each risk factor need to be integrated and evaluated with respect to biological function and through pathway-based algorithms. This resource will provide information to researchers studying the molecular and genetic causes of stroke in terms of genomic variants, genes, and pathways. METHODS: Reported genetic variants, gene structure, phenotypes, and literature information regarding stroke were collected and extracted from publicly available databases describing variants, genome, proteome, functional annotation, and disease subtypes. Stroke related candidate pathways and etiologic genes that participate significantly in risk were analyzed in terms of canonical pathways in public biological pathway databases. These efforts resulted in a relational database of genetic signals of cerebral stroke, SigCS base, which implements an effective web retrieval system. RESULTS: The current version of SigCS base documents 1943 non-redundant genes with 11472 genetic variants and 165 non-redundant pathways. The web retrieval system of SigCS base consists of two principal search flows, including: 1) a gene-based variant search using gene table browsing or a keyword search, and, 2) a pathway-based variant search using pathway table browsing. SigCS base is freely accessible at http://sysbio.kribb.re.kr/sigcs. CONCLUSIONS: SigCS base is an effective tool that can assist researchers in the identification of the genetic factors associated with stroke by utilizing existing literature information, selecting candidate genes and variants for experimental studies, and examining the pathways that contribute to the pathophysiological mechanisms of stroke.
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spelling pubmed-32874762012-02-28 SigCS base: an integrated genetic information resource for human cerebral stroke Park, Young-Kyu Bang, Ok Sun Cha, Min-Ho Kim, Jaeheup Cole, John W Lee, Doheon Kim, Young Joo BMC Syst Biol Proceedings BACKGROUND: To understand how stroke risk factors mechanistically contribute to stroke, the genetic components regulating each risk factor need to be integrated and evaluated with respect to biological function and through pathway-based algorithms. This resource will provide information to researchers studying the molecular and genetic causes of stroke in terms of genomic variants, genes, and pathways. METHODS: Reported genetic variants, gene structure, phenotypes, and literature information regarding stroke were collected and extracted from publicly available databases describing variants, genome, proteome, functional annotation, and disease subtypes. Stroke related candidate pathways and etiologic genes that participate significantly in risk were analyzed in terms of canonical pathways in public biological pathway databases. These efforts resulted in a relational database of genetic signals of cerebral stroke, SigCS base, which implements an effective web retrieval system. RESULTS: The current version of SigCS base documents 1943 non-redundant genes with 11472 genetic variants and 165 non-redundant pathways. The web retrieval system of SigCS base consists of two principal search flows, including: 1) a gene-based variant search using gene table browsing or a keyword search, and, 2) a pathway-based variant search using pathway table browsing. SigCS base is freely accessible at http://sysbio.kribb.re.kr/sigcs. CONCLUSIONS: SigCS base is an effective tool that can assist researchers in the identification of the genetic factors associated with stroke by utilizing existing literature information, selecting candidate genes and variants for experimental studies, and examining the pathways that contribute to the pathophysiological mechanisms of stroke. BioMed Central 2011-12-14 /pmc/articles/PMC3287476/ /pubmed/22784567 http://dx.doi.org/10.1186/1752-0509-5-S2-S10 Text en Copyright ©2011 Park et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Proceedings
Park, Young-Kyu
Bang, Ok Sun
Cha, Min-Ho
Kim, Jaeheup
Cole, John W
Lee, Doheon
Kim, Young Joo
SigCS base: an integrated genetic information resource for human cerebral stroke
title SigCS base: an integrated genetic information resource for human cerebral stroke
title_full SigCS base: an integrated genetic information resource for human cerebral stroke
title_fullStr SigCS base: an integrated genetic information resource for human cerebral stroke
title_full_unstemmed SigCS base: an integrated genetic information resource for human cerebral stroke
title_short SigCS base: an integrated genetic information resource for human cerebral stroke
title_sort sigcs base: an integrated genetic information resource for human cerebral stroke
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287476/
https://www.ncbi.nlm.nih.gov/pubmed/22784567
http://dx.doi.org/10.1186/1752-0509-5-S2-S10
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