Source:http://linkedlifedata.com/resource/pubmed/id/17038344
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
4
|
| pubmed:dateCreated |
2007-2-15
|
| pubmed:abstractText |
High-throughput technologies now allow the acquisition of biological data, such as comprehensive biochemical time-courses at unprecedented rates. These temporal profiles carry topological and kinetic information regarding the biochemical network from which they were drawn. Retrieving this information will require systematic application of both experimental and computational methods.
|
| pubmed:language |
eng
|
| pubmed:journal | |
| pubmed:citationSubset |
IM
|
| pubmed:chemical | |
| pubmed:status |
MEDLINE
|
| pubmed:month |
Feb
|
| pubmed:issn |
1367-4811
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| pubmed:author | |
| pubmed:issnType |
Electronic
|
| pubmed:day |
15
|
| pubmed:volume |
23
|
| pubmed:owner |
NLM
|
| pubmed:authorsComplete |
Y
|
| pubmed:pagination |
480-6
|
| pubmed:dateRevised |
2009-11-4
|
| pubmed:meshHeading |
pubmed-meshheading:17038344-Biochemistry,
pubmed-meshheading:17038344-Computer Simulation,
pubmed-meshheading:17038344-Gene Expression Profiling,
pubmed-meshheading:17038344-Models, Biological,
pubmed-meshheading:17038344-Proteome,
pubmed-meshheading:17038344-Signal Transduction,
pubmed-meshheading:17038344-Software
|
| pubmed:year |
2007
|
| pubmed:articleTitle |
Parameter estimation using Simulated Annealing for S-system models of biochemical networks.
|
| pubmed:affiliation |
Department of Computer Science University of the Philippines-Diliman, Munich, Germany. gonzalez@bio.ifi.lmu.de
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| pubmed:publicationType |
Journal Article
|