DC Field | Value | Language |
---|---|---|
dc.contributor.author | Cho, Kwang-Hyun | ko |
dc.contributor.author | Kim, JR | ko |
dc.contributor.author | Baek, S | ko |
dc.contributor.author | Choi, HS | ko |
dc.contributor.author | Choo, SM | ko |
dc.date.accessioned | 2013-03-08T02:41:48Z | - |
dc.date.available | 2013-03-08T02:41:48Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 2006-06 | - |
dc.identifier.citation | FEBS LETTERS, v.580, pp.3511 - 3518 | - |
dc.identifier.issn | 0014-5793 | - |
dc.identifier.uri | http://hdl.handle.net/10203/91869 | - |
dc.description.abstract | Reverse engineering of biomolecular regulatory networks such as gene regulatory networks, protein interaction networks, and metabolic networks has received an increasing attention as more high-throughput time-series measurements become available. In spite of various approaches developed from this motivation, it still remains as a challenging subject to develop a new reverse engineering scheme that can effectively uncover the functional interaction structure of a biomolecular network from given time-series expression profiles (TSEPs). We propose a new reverse engineering scheme that makes use of phase portraits constructed by projection of every two TSEPs into respective phase planes. We introduce two measures of a slope index (SI) and a winding index (WI) to quantify the interaction properties embedded in the phase portrait. Based on the SI and WI, we can reconstruct the functional interaction network in a very efficient and systematic way with better inference results compared to previous approaches. By using the SI, we can also estimate the time-lag accompanied with the interaction between molecular components of a network. (c) 2006 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved. | - |
dc.language | English | - |
dc.publisher | ELSEVIER SCIENCE BV | - |
dc.subject | GENE-EXPRESSION | - |
dc.subject | INFERENCE | - |
dc.subject | PROTEIN | - |
dc.subject | CELLS | - |
dc.title | Inferring biomolecular regulatory networks from phase portraits of time-series expression profiles | - |
dc.type | Article | - |
dc.identifier.wosid | 000238320100029 | - |
dc.identifier.scopusid | 2-s2.0-33746453400 | - |
dc.type.rims | ART | - |
dc.citation.volume | 580 | - |
dc.citation.beginningpage | 3511 | - |
dc.citation.endingpage | 3518 | - |
dc.citation.publicationname | FEBS LETTERS | - |
dc.identifier.doi | 10.1016/j.febslet.2006.05.035 | - |
dc.contributor.localauthor | Cho, Kwang-Hyun | - |
dc.contributor.nonIdAuthor | Kim, JR | - |
dc.contributor.nonIdAuthor | Baek, S | - |
dc.contributor.nonIdAuthor | Choi, HS | - |
dc.contributor.nonIdAuthor | Choo, SM | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | regulatory networks | - |
dc.subject.keywordAuthor | phase portraits | - |
dc.subject.keywordAuthor | time-series expression profiles | - |
dc.subject.keywordAuthor | reverse engineering | - |
dc.subject.keywordPlus | GENE-EXPRESSION | - |
dc.subject.keywordPlus | INFERENCE | - |
dc.subject.keywordPlus | PROTEIN | - |
dc.subject.keywordPlus | CELLS | - |
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