DC Field | Value | Language |
---|---|---|
dc.contributor.author | 박종명 | ko |
dc.contributor.author | 김현욱 | ko |
dc.contributor.author | 김태용 | ko |
dc.contributor.author | Lee, SangYup | ko |
dc.date.accessioned | 2013-03-28T04:14:41Z | - |
dc.date.available | 2013-03-28T04:14:41Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 2007-04 | - |
dc.identifier.citation | Annual Spring Meeting of KIChE, pp.424 | - |
dc.identifier.uri | http://hdl.handle.net/10203/162739 | - |
dc.description.abstract | Metabolic fluxes, an ultimate phenotype of the cell, are condition-specific, so that it is very difficult to predict their distribution patterns under conditions of interest. To provide insight into this problem, we developed a framework that employes constraint-based flux analysis and Bayesian network analysis. This framework first performs constraint-based flux analysis with constraints adopted from 13C isotope-labelling experiments. Information from 13C isotope-labelling experiments is used in order to calculate more accurate genome-scale metabolic flux distributions. Also, least absolute deviation method is used to account for infeasibility of the system due to a large number of constraints. The calculated metabolic flux profiles are then categorized into functional sub-metabolisms, and each of these is subjected to Bayesian network analysis in oder to infer the causal relationship among metabolic fluxes. | - |
dc.language | Korean | - |
dc.publisher | Annual Spring Meeting of KIChE | - |
dc.title | Framework for elucidating the causal relationship of metabolic fluxes | - |
dc.type | Conference | - |
dc.type.rims | CONF | - |
dc.citation.beginningpage | 424 | - |
dc.citation.publicationname | Annual Spring Meeting of KIChE | - |
dc.identifier.conferencecountry | KO | - |
dc.identifier.conferencelocation | 울산 롯데호텔 | - |
dc.contributor.localauthor | Lee, SangYup | - |
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