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Article: Discovering altered genomic expression patterns in heart: Transcriptome determination by serial analysis of gene expression

TitleDiscovering altered genomic expression patterns in heart: Transcriptome determination by serial analysis of gene expression
Authors
Issue Date2001
Citation
European Journal of Heart Failure, 2001, v. 3 n. 3, p. 271-281 How to Cite?
AbstractThe development of cardiovascular diseases such as heart failure involve functional changes that are beneficial short-term, but may be fatal long-term. Current therapeutic approaches are tailored to limit progression of a disease and to maintain quality of life. At a molecular level, these disease processes involve quantitative and qualitative changes in gene expression. Although some changes in mRNA abundance may not have direct protein correlates, analysis of all the mRNAs present in a cell population (the cells transcriptome) has become a focal point of genomic research. The aim is to provide information about the dynamics of total genome expression in response to environmental changes and point to candidate genes responsible for the cascade of events that result in a disease state. One way of performing these analyses utilizes the technique of Serial Analysis of Gene Expression (SAGE). This method evaluates thousands of expressed transcripts both quantitatively and qualitatively in a single assay. In the first of two reviews on transcriptome analysis, we describe the current state of genomic research for determination of the transcriptome by Serial Analysis of Gene Expression, present the first limited SAGE analysis of rodent heart gene expression, and discuss how results generated with this approach can be applied to the study and treatment of cardiovascular diseases. Published by Elsevier Science Ireland ltd on behalf of European Society of Cardiology.
Persistent Identifierhttp://hdl.handle.net/10722/195250
ISSN
2015 Impact Factor: 5.135
2015 SCImago Journal Rankings: 3.638
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorAnisimov, SV-
dc.contributor.authorLakatta, EG-
dc.contributor.authorBoheler, KR-
dc.date.accessioned2014-02-25T01:40:21Z-
dc.date.available2014-02-25T01:40:21Z-
dc.date.issued2001-
dc.identifier.citationEuropean Journal of Heart Failure, 2001, v. 3 n. 3, p. 271-281-
dc.identifier.issn1388-9842-
dc.identifier.urihttp://hdl.handle.net/10722/195250-
dc.description.abstractThe development of cardiovascular diseases such as heart failure involve functional changes that are beneficial short-term, but may be fatal long-term. Current therapeutic approaches are tailored to limit progression of a disease and to maintain quality of life. At a molecular level, these disease processes involve quantitative and qualitative changes in gene expression. Although some changes in mRNA abundance may not have direct protein correlates, analysis of all the mRNAs present in a cell population (the cells transcriptome) has become a focal point of genomic research. The aim is to provide information about the dynamics of total genome expression in response to environmental changes and point to candidate genes responsible for the cascade of events that result in a disease state. One way of performing these analyses utilizes the technique of Serial Analysis of Gene Expression (SAGE). This method evaluates thousands of expressed transcripts both quantitatively and qualitatively in a single assay. In the first of two reviews on transcriptome analysis, we describe the current state of genomic research for determination of the transcriptome by Serial Analysis of Gene Expression, present the first limited SAGE analysis of rodent heart gene expression, and discuss how results generated with this approach can be applied to the study and treatment of cardiovascular diseases. Published by Elsevier Science Ireland ltd on behalf of European Society of Cardiology.-
dc.languageeng-
dc.relation.ispartofEuropean Journal of Heart Failure-
dc.titleDiscovering altered genomic expression patterns in heart: Transcriptome determination by serial analysis of gene expression-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/S1388-9842(01)00131-3-
dc.identifier.pmid11377997-
dc.identifier.scopuseid_2-s2.0-0034837744-
dc.identifier.volume3-
dc.identifier.issue3-
dc.identifier.spage271-
dc.identifier.epage281-
dc.identifier.isiWOS:000169189700002-

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