Toward a systems level view of the ECM and related proteins: a framework for the systematic definition and analysis of biological systems.
Identifieur interne : 001049 ( Ncbi/Checkpoint ); précédent : 001048; suivant : 001050Toward a systems level view of the ECM and related proteins: a framework for the systematic definition and analysis of biological systems.
Auteurs : Graham L. Cromar [Canada] ; Xuejian Xiong ; Emilie Chautard ; Sylvie Ricard-Blum ; John ParkinsonSource :
- Proteins [ 1097-0134 ] ; 2012.
English descriptors
- KwdEn :
- MESH :
- chemical , chemistry : Extracellular Matrix Proteins.
- chemical , metabolism : Extracellular Matrix Proteins.
- methods : Protein Interaction Mapping, Systems Biology.
- Cluster Analysis, Gene Expression Profiling, Humans, Protein Interaction Maps.
Abstract
Advances in high throughput 'omic technologies are starting to provide unprecedented insights into how components of biological systems are organized and interact. Key to exploiting these datasets is the definition of the components that comprise the system of interest. Although a variety of knowledge bases exist that capture such information, a major challenge is determining how these resources may be best utilized. Here we present a systematic curation strategy to define a systems-level view of the human extracellular matrix (ECM)--a three-dimensional meshwork of proteins and polysaccharides that impart structure and mechanical stability to tissues. Employing our curation strategy we define a set of 357 proteins that represent core components of the ECM, together with an additional 524 genes that mediate related functional roles, and construct a map of their physical interactions. Topological properties help identify modules of functionally related proteins, including those involved in cell adhesion, bone formation and blood clotting. Because of its major role in cell adhesion, proliferation and morphogenesis, defects in the ECM have been implicated in cancer, atherosclerosis, asthma, fibrosis, and arthritis. We use MeSH annotations to identify modules enriched for specific disease terms that aid to strengthen existing as well as predict novel gene-disease associations. Mapping expression and conservation data onto the network reveal modules evolved in parallel to convey tissue-specific functionality on otherwise broadly expressed units. In addition to demonstrating an effective workflow for defining biological systems, this study crystallizes our current knowledge surrounding the organization of the ECM.
DOI: 10.1002/prot.24036
PubMed: 22275077
Affiliations:
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Cromar</name><affiliation wicri:level="4"><nlm:affiliation>Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada.</nlm:affiliation><country xml:lang="fr">Canada</country><wicri:regionArea>Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8</wicri:regionArea><orgName type="university">Université de Toronto</orgName><placeName><settlement type="city">Toronto</settlement><region type="state">Ontario</region></placeName></affiliation></author><author><name sortKey="Xiong, Xuejian" sort="Xiong, Xuejian" uniqKey="Xiong X" first="Xuejian" last="Xiong">Xuejian Xiong</name></author><author><name sortKey="Chautard, Emilie" sort="Chautard, Emilie" uniqKey="Chautard E" first="Emilie" last="Chautard">Emilie Chautard</name></author><author><name sortKey="Ricard Blum, Sylvie" sort="Ricard Blum, Sylvie" uniqKey="Ricard Blum S" first="Sylvie" last="Ricard-Blum">Sylvie Ricard-Blum</name></author><author><name sortKey="Parkinson, John" sort="Parkinson, John" uniqKey="Parkinson J" first="John" last="Parkinson">John Parkinson</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2012">2012</date><idno type="RBID">pubmed:22275077</idno><idno type="pmid">22275077</idno><idno type="doi">10.1002/prot.24036</idno><idno type="wicri:Area/PubMed/Corpus">000A66</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000A66</idno><idno type="wicri:Area/PubMed/Curation">000A66</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Curation">000A66</idno><idno type="wicri:Area/PubMed/Checkpoint">000A66</idno><idno type="wicri:explorRef" wicri:stream="Checkpoint" wicri:step="PubMed">000A66</idno><idno type="wicri:Area/Ncbi/Merge">001049</idno><idno type="wicri:Area/Ncbi/Curation">001049</idno><idno type="wicri:Area/Ncbi/Checkpoint">001049</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Toward a systems level view of the ECM and related proteins: a framework for the systematic definition and analysis of biological systems.</title><author><name sortKey="Cromar, Graham L" sort="Cromar, Graham L" uniqKey="Cromar G" first="Graham L" last="Cromar">Graham L. Cromar</name><affiliation wicri:level="4"><nlm:affiliation>Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada.</nlm:affiliation><country xml:lang="fr">Canada</country><wicri:regionArea>Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8</wicri:regionArea><orgName type="university">Université de Toronto</orgName><placeName><settlement type="city">Toronto</settlement><region type="state">Ontario</region></placeName></affiliation></author><author><name sortKey="Xiong, Xuejian" sort="Xiong, Xuejian" uniqKey="Xiong X" first="Xuejian" last="Xiong">Xuejian Xiong</name></author><author><name sortKey="Chautard, Emilie" sort="Chautard, Emilie" uniqKey="Chautard E" first="Emilie" last="Chautard">Emilie Chautard</name></author><author><name sortKey="Ricard Blum, Sylvie" sort="Ricard Blum, Sylvie" uniqKey="Ricard Blum S" first="Sylvie" last="Ricard-Blum">Sylvie Ricard-Blum</name></author><author><name sortKey="Parkinson, John" sort="Parkinson, John" uniqKey="Parkinson J" first="John" last="Parkinson">John Parkinson</name></author></analytic><series><title level="j">Proteins</title><idno type="eISSN">1097-0134</idno><imprint><date when="2012" type="published">2012</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Cluster Analysis</term><term>Extracellular Matrix Proteins (chemistry)</term><term>Extracellular Matrix Proteins (metabolism)</term><term>Gene Expression Profiling</term><term>Humans</term><term>Protein Interaction Mapping (methods)</term><term>Protein Interaction Maps</term><term>Systems Biology (methods)</term></keywords><keywords scheme="MESH" type="chemical" qualifier="chemistry" xml:lang="en"><term>Extracellular Matrix Proteins</term></keywords><keywords scheme="MESH" type="chemical" qualifier="metabolism" xml:lang="en"><term>Extracellular Matrix Proteins</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Protein Interaction Mapping</term><term>Systems Biology</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Cluster Analysis</term><term>Gene Expression Profiling</term><term>Humans</term><term>Protein Interaction Maps</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Advances in high throughput 'omic technologies are starting to provide unprecedented insights into how components of biological systems are organized and interact. Key to exploiting these datasets is the definition of the components that comprise the system of interest. Although a variety of knowledge bases exist that capture such information, a major challenge is determining how these resources may be best utilized. Here we present a systematic curation strategy to define a systems-level view of the human extracellular matrix (ECM)--a three-dimensional meshwork of proteins and polysaccharides that impart structure and mechanical stability to tissues. Employing our curation strategy we define a set of 357 proteins that represent core components of the ECM, together with an additional 524 genes that mediate related functional roles, and construct a map of their physical interactions. Topological properties help identify modules of functionally related proteins, including those involved in cell adhesion, bone formation and blood clotting. Because of its major role in cell adhesion, proliferation and morphogenesis, defects in the ECM have been implicated in cancer, atherosclerosis, asthma, fibrosis, and arthritis. We use MeSH annotations to identify modules enriched for specific disease terms that aid to strengthen existing as well as predict novel gene-disease associations. Mapping expression and conservation data onto the network reveal modules evolved in parallel to convey tissue-specific functionality on otherwise broadly expressed units. In addition to demonstrating an effective workflow for defining biological systems, this study crystallizes our current knowledge surrounding the organization of the ECM.</div></front></TEI><affiliations><list><country><li>Canada</li></country><region><li>Ontario</li></region><settlement><li>Toronto</li></settlement><orgName><li>Université de Toronto</li></orgName></list><tree><noCountry><name sortKey="Chautard, Emilie" sort="Chautard, Emilie" uniqKey="Chautard E" first="Emilie" last="Chautard">Emilie Chautard</name><name sortKey="Parkinson, John" sort="Parkinson, John" uniqKey="Parkinson J" first="John" last="Parkinson">John Parkinson</name><name sortKey="Ricard Blum, Sylvie" sort="Ricard Blum, Sylvie" uniqKey="Ricard Blum S" first="Sylvie" last="Ricard-Blum">Sylvie Ricard-Blum</name><name sortKey="Xiong, Xuejian" sort="Xiong, Xuejian" uniqKey="Xiong X" first="Xuejian" last="Xiong">Xuejian Xiong</name></noCountry><country name="Canada"><region name="Ontario"><name sortKey="Cromar, Graham L" sort="Cromar, Graham L" uniqKey="Cromar G" first="Graham L" last="Cromar">Graham L. 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