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rdf:type |
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lifeskim:mentions |
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pubmed:dateCreated |
2009-3-16
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pubmed:abstractText |
A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data.
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pubmed:commentsCorrections |
http://linkedlifedata.com/resource/pubmed/commentcorrection/19239685-10380182,
http://linkedlifedata.com/resource/pubmed/commentcorrection/19239685-11027309,
http://linkedlifedata.com/resource/pubmed/commentcorrection/19239685-11108481,
http://linkedlifedata.com/resource/pubmed/commentcorrection/19239685-11847074,
http://linkedlifedata.com/resource/pubmed/commentcorrection/19239685-11893164,
http://linkedlifedata.com/resource/pubmed/commentcorrection/19239685-11911796,
http://linkedlifedata.com/resource/pubmed/commentcorrection/19239685-11967534,
http://linkedlifedata.com/resource/pubmed/commentcorrection/19239685-11983907,
http://linkedlifedata.com/resource/pubmed/commentcorrection/19239685-14764868,
http://linkedlifedata.com/resource/pubmed/commentcorrection/19239685-15372033,
http://linkedlifedata.com/resource/pubmed/commentcorrection/19239685-15479708,
http://linkedlifedata.com/resource/pubmed/commentcorrection/19239685-15778709,
http://linkedlifedata.com/resource/pubmed/commentcorrection/19239685-15845847,
http://linkedlifedata.com/resource/pubmed/commentcorrection/19239685-16122766,
http://linkedlifedata.com/resource/pubmed/commentcorrection/19239685-16215643,
http://linkedlifedata.com/resource/pubmed/commentcorrection/19239685-17925349,
http://linkedlifedata.com/resource/pubmed/commentcorrection/19239685-18844584,
http://linkedlifedata.com/resource/pubmed/commentcorrection/19239685-9169833,
http://linkedlifedata.com/resource/pubmed/commentcorrection/19239685-9697168,
http://linkedlifedata.com/resource/pubmed/commentcorrection/19239685-9843981
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pubmed:language |
eng
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pubmed:journal |
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pubmed:status |
PubMed-not-MEDLINE
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pubmed:issn |
1748-7188
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pubmed:author |
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pubmed:issnType |
Electronic
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pubmed:volume |
4
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
5
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pubmed:dateRevised |
2009-11-18
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pubmed:year |
2009
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pubmed:articleTitle |
A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data.
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pubmed:affiliation |
Department of Computer Science and Automation, Indian Institute of Science, Bangalore, Karnataka, India. sahely@csa.iisc.ernet.in
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pubmed:publicationType |
Journal Article
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