pubmed-article:11800577 | rdf:type | pubmed:Citation | lld:pubmed |
pubmed-article:11800577 | lifeskim:mentions | umls-concept:C0032098 | lld:lifeskim |
pubmed-article:11800577 | lifeskim:mentions | umls-concept:C1291081 | lld:lifeskim |
pubmed-article:11800577 | lifeskim:mentions | umls-concept:C0024934 | lld:lifeskim |
pubmed-article:11800577 | lifeskim:mentions | umls-concept:C0870071 | lld:lifeskim |
pubmed-article:11800577 | pubmed:issue | 1 | lld:pubmed |
pubmed-article:11800577 | pubmed:dateCreated | 2002-1-21 | lld:pubmed |
pubmed-article:11800577 | pubmed:abstractText | The understanding of the control of metabolic flux in plants requires integrated mathematical formulations of gene and protein expression, enzyme kinetics, and developmental biology. Plants have a large number of metabolically active compartments, and non-steady-state conditions are frequently encountered. Consequently steady-state metabolic flux balance and isotopic flux balance modeling approaches have limited utility in probing plant metabolic systems. Transient isotopic flux analysis and kinetic modeling are powerful proven techniques for the quantification of metabolic fluxes in compartmentalized, dynamic metabolic systems. These tools are now widely used to address metabolic flux responses to environmental and genetic perturbations in plant metabolism. Continued developments in isotopic and kinetic modeling, quantifying metabolite exchange between compartments, and transcriptional and posttranscriptional regulatory mechanisms governing enzyme level and activity will enable simulation of large sections of plant metabolism under non-steady-state conditions. Metabolic control analysis will continue to make substantial contributions to the understanding of quantitative distribution of control of flux. From the synergy between mathematical models and experiments, creative methods for controlling the distribution of flux by genetic or environmental means will be discovered and rationally implemented. | lld:pubmed |
pubmed-article:11800577 | pubmed:language | eng | lld:pubmed |
pubmed-article:11800577 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:11800577 | pubmed:citationSubset | IM | lld:pubmed |
pubmed-article:11800577 | pubmed:chemical | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:11800577 | pubmed:status | MEDLINE | lld:pubmed |
pubmed-article:11800577 | pubmed:month | Jan | lld:pubmed |
pubmed-article:11800577 | pubmed:issn | 1096-7176 | lld:pubmed |
pubmed-article:11800577 | pubmed:author | pubmed-author:MorganJohn... | lld:pubmed |
pubmed-article:11800577 | pubmed:author | pubmed-author:RhodesDavidD | lld:pubmed |
pubmed-article:11800577 | pubmed:issnType | Print | lld:pubmed |
pubmed-article:11800577 | pubmed:volume | 4 | lld:pubmed |
pubmed-article:11800577 | pubmed:owner | NLM | lld:pubmed |
pubmed-article:11800577 | pubmed:authorsComplete | Y | lld:pubmed |
pubmed-article:11800577 | pubmed:pagination | 80-9 | lld:pubmed |
pubmed-article:11800577 | pubmed:dateRevised | 2006-11-15 | lld:pubmed |
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pubmed-article:11800577 | pubmed:meshHeading | pubmed-meshheading:11800577... | lld:pubmed |
pubmed-article:11800577 | pubmed:year | 2002 | lld:pubmed |
pubmed-article:11800577 | pubmed:articleTitle | Mathematical modeling of plant metabolic pathways. | lld:pubmed |
pubmed-article:11800577 | pubmed:affiliation | School of Chemical Engineering, Purdue University, West Lafayette, Indiana 47907, USA. jamorgan@ecn.purdue.edu | lld:pubmed |
pubmed-article:11800577 | pubmed:publicationType | Journal Article | lld:pubmed |
pubmed-article:11800577 | pubmed:publicationType | Research Support, U.S. Gov't, Non-P.H.S. | lld:pubmed |
pubmed-article:11800577 | pubmed:publicationType | Review | lld:pubmed |
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