Inferring Gene Networks from gene-expression data

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dc.contributor.authorde la Fuente, Alberto
dc.date.accessioned2014-05-13T09:19:10Z
dc.date.available2014-05-13T09:19:10Z
dc.date.issued2012-05
dc.descriptionCollana seminari interni 2012, Number 20120502.IT
dc.description.abstractThe network representation of cellular regulatory systems allows for application of mathematical tools to gain insights into the fundamental organisation of living entities. Gene Networks (GNs) are abstract models of gene communication with nodes representing the gene activities (gene expression levels, mRNA concentrations), and directed edges representing causal influences. Many techniques for constructing GNs from gene expression data have been proposed and the most popular techniques are based on ordinary differential equations or Bayesian networks. In this seminar, the general problem of reverse-engineering gene networks will be outlined, the report on latest advances in this area and comments on further directions to pursue will be explained.IT
dc.identifier.urihttp://hdl.handle.net/11050/888
dc.language.isoenIT
dc.subjectSysGenSIMIT
dc.subjectgenetics simulatorIT
dc.subjectdiseaseIT
dc.subjectmolecular geneticsIT
dc.subject.een-cordisEEN CORDIS::SCIENZE BIOLOGICHE ::Ricerca sul genoma ::BioinformaticaIT
dc.subject.programProgram::Biomedicine::Bioinformatics (BI)IT
dc.titleInferring Gene Networks from gene-expression dataIT
dc.typeContributo a convegnoIT
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