Maximum entropy decomposition of flux distribution at steady state to elementary modes
Enzyme Control Flux (ECF) is a method of correlating enzyme activity and flux distribution. The advantage of ECF is that the measurement integrates proteome data with metabolic flux analysis through Elementary Modes (EMs). But there are a few methods of effectively determining the Elementary Mode Co...
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| Veröffentlicht in: | Journal of bioscience and bioengineering 2009, Vol.107 (1), p.84-89 |
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| creator | Zhao, Quanyu Kurata, Hiroyuki |
| description | Enzyme Control Flux (ECF) is a method of correlating enzyme activity and flux distribution. The advantage of ECF is that the measurement integrates proteome data with metabolic flux analysis through Elementary Modes (EMs). But there are a few methods of effectively determining the Elementary Mode Coefficient (EMC) in cases where no objective biological function is available. Therefore, we proposed a new algorithm implementing the maximum entropy principle (MEP) as an objective function for estimating the EMC. To demonstrate the feasibility of using the MEP in this way, we compared it with Linear Programming and Quadratic Programming for modeling the metabolic networks of Chinese Hamster Ovary,
Escherichia coli, and
Saccharomyces cerevisiae cells. The use of the MEP presents the most plausible distribution of EMCs in the absence of any biological hypotheses describing the physiological state of cells, thereby enhancing the prediction accuracy of the flux distribution in various mutants. |
| doi_str_mv | 10.1016/j.jbiosc.2008.09.011 |
| format | Article |
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Escherichia coli, and
Saccharomyces cerevisiae cells. The use of the MEP presents the most plausible distribution of EMCs in the absence of any biological hypotheses describing the physiological state of cells, thereby enhancing the prediction accuracy of the flux distribution in various mutants.</description><identifier>ISSN: 1389-1723</identifier><identifier>EISSN: 1347-4421</identifier><identifier>DOI: 10.1016/j.jbiosc.2008.09.011</identifier><identifier>PMID: 19147116</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Algorithms ; Animals ; Bacillus subtilis - genetics ; Biological and medical sciences ; Biotechnology ; CELLS ; CELLULE ; CELULAS ; CHO Cells ; Cricetinae ; Cricetulus ; Elementary mode ; Entropy ; ENZIMAS ; ENZYME ; Enzyme control flux ; ENZYMES ; Enzymes - chemistry ; ESCHERICHIA COLI ; Escherichia coli - genetics ; EXPRESION GENICA ; EXPRESSION DES GENES ; Fundamental and applied biological sciences. Psychology ; GENE EXPRESSION ; HAMSTER ; HAMSTERS ; Linear programming ; Maximum entropy principle ; Metabolic flux analysis ; METABOLISM ; METABOLISME ; METABOLISMO ; Models, Biological ; Models, Statistical ; Models, Theoretical ; MUTANT ; MUTANTES ; MUTANTS ; Mutation ; NETWORKS ; Quadratic programming ; REDES ; Reproducibility of Results ; RESEAU ; Saccharomyces cerevisiae ; Saccharomyces cerevisiae - genetics</subject><ispartof>Journal of bioscience and bioengineering, 2009, Vol.107 (1), p.84-89</ispartof><rights>2008 Elsevier Inc.</rights><rights>2009 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c534t-19fac212e35ff24852c2c7febeb115b4bb90ab2e15452ddb770adf0303d01d803</citedby><cites>FETCH-LOGICAL-c534t-19fac212e35ff24852c2c7febeb115b4bb90ab2e15452ddb770adf0303d01d803</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jbiosc.2008.09.011$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>315,781,785,3551,4025,27927,27928,27929,45999</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=21148678$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/19147116$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhao, Quanyu</creatorcontrib><creatorcontrib>Kurata, Hiroyuki</creatorcontrib><title>Maximum entropy decomposition of flux distribution at steady state to elementary modes</title><title>Journal of bioscience and bioengineering</title><addtitle>J Biosci Bioeng</addtitle><description>Enzyme Control Flux (ECF) is a method of correlating enzyme activity and flux distribution. The advantage of ECF is that the measurement integrates proteome data with metabolic flux analysis through Elementary Modes (EMs). But there are a few methods of effectively determining the Elementary Mode Coefficient (EMC) in cases where no objective biological function is available. Therefore, we proposed a new algorithm implementing the maximum entropy principle (MEP) as an objective function for estimating the EMC. To demonstrate the feasibility of using the MEP in this way, we compared it with Linear Programming and Quadratic Programming for modeling the metabolic networks of Chinese Hamster Ovary,
Escherichia coli, and
Saccharomyces cerevisiae cells. The use of the MEP presents the most plausible distribution of EMCs in the absence of any biological hypotheses describing the physiological state of cells, thereby enhancing the prediction accuracy of the flux distribution in various mutants.</description><subject>Algorithms</subject><subject>Animals</subject><subject>Bacillus subtilis - genetics</subject><subject>Biological and medical sciences</subject><subject>Biotechnology</subject><subject>CELLS</subject><subject>CELLULE</subject><subject>CELULAS</subject><subject>CHO Cells</subject><subject>Cricetinae</subject><subject>Cricetulus</subject><subject>Elementary mode</subject><subject>Entropy</subject><subject>ENZIMAS</subject><subject>ENZYME</subject><subject>Enzyme control flux</subject><subject>ENZYMES</subject><subject>Enzymes - chemistry</subject><subject>ESCHERICHIA COLI</subject><subject>Escherichia coli - genetics</subject><subject>EXPRESION GENICA</subject><subject>EXPRESSION DES GENES</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>GENE EXPRESSION</subject><subject>HAMSTER</subject><subject>HAMSTERS</subject><subject>Linear programming</subject><subject>Maximum entropy principle</subject><subject>Metabolic flux analysis</subject><subject>METABOLISM</subject><subject>METABOLISME</subject><subject>METABOLISMO</subject><subject>Models, Biological</subject><subject>Models, Statistical</subject><subject>Models, Theoretical</subject><subject>MUTANT</subject><subject>MUTANTES</subject><subject>MUTANTS</subject><subject>Mutation</subject><subject>NETWORKS</subject><subject>Quadratic programming</subject><subject>REDES</subject><subject>Reproducibility of Results</subject><subject>RESEAU</subject><subject>Saccharomyces cerevisiae</subject><subject>Saccharomyces cerevisiae - genetics</subject><issn>1389-1723</issn><issn>1347-4421</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkUuPFSEQRjtG44yj_0ANm3HXPRTQr42JmYyvzEQX6pbwKAw33c0VaDP338u1b3SnqyLUqQ84VNVzoA1Q6K52zU77kEzDKB0aOjYU4EF1Dlz0tRAMHh7Xw1hDz_hZ9SSlHaXQ0x4eV2cwgugBuvPq25269_M6E1xyDPsDsWjCvA_JZx8WEhxx03pPrE85er3-3lSZpIzKHkpRGUkOBCecS4KKBzIHi-lp9cipKeGzU72ovr69-XL9vr799O7D9Zvb2rRc5BpGpwwDhrx1jomhZYaZ3qFGDdBqofVIlWYIrWiZtbrvqbKOcsotBTtQflG92nL3MfxYMWU5-2RwmtSCYU2y6wbGOv5_kNHiivGxgGIDTQwpRXRyH_1cHiaByqN4uZObeHkUL-koi_gy9vKUv-oZ7d-hk-kCXJ4AlYyaXFSL8ekPxwDE0PVD4V5snFNBqu-xMB8_l5PG8nvAeOm_3vpYtP70GGUyHheD1kc0Wdrg_33TX2RirOc</recordid><startdate>2009</startdate><enddate>2009</enddate><creator>Zhao, Quanyu</creator><creator>Kurata, Hiroyuki</creator><general>Elsevier B.V</general><general>Elsevier</general><scope>FBQ</scope><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QL</scope><scope>7QO</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>M7N</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>2009</creationdate><title>Maximum entropy decomposition of flux distribution at steady state to elementary modes</title><author>Zhao, Quanyu ; Kurata, Hiroyuki</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c534t-19fac212e35ff24852c2c7febeb115b4bb90ab2e15452ddb770adf0303d01d803</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Algorithms</topic><topic>Animals</topic><topic>Bacillus subtilis - genetics</topic><topic>Biological and medical sciences</topic><topic>Biotechnology</topic><topic>CELLS</topic><topic>CELLULE</topic><topic>CELULAS</topic><topic>CHO Cells</topic><topic>Cricetinae</topic><topic>Cricetulus</topic><topic>Elementary mode</topic><topic>Entropy</topic><topic>ENZIMAS</topic><topic>ENZYME</topic><topic>Enzyme control flux</topic><topic>ENZYMES</topic><topic>Enzymes - chemistry</topic><topic>ESCHERICHIA COLI</topic><topic>Escherichia coli - genetics</topic><topic>EXPRESION GENICA</topic><topic>EXPRESSION DES GENES</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>GENE EXPRESSION</topic><topic>HAMSTER</topic><topic>HAMSTERS</topic><topic>Linear programming</topic><topic>Maximum entropy principle</topic><topic>Metabolic flux analysis</topic><topic>METABOLISM</topic><topic>METABOLISME</topic><topic>METABOLISMO</topic><topic>Models, Biological</topic><topic>Models, Statistical</topic><topic>Models, Theoretical</topic><topic>MUTANT</topic><topic>MUTANTES</topic><topic>MUTANTS</topic><topic>Mutation</topic><topic>NETWORKS</topic><topic>Quadratic programming</topic><topic>REDES</topic><topic>Reproducibility of Results</topic><topic>RESEAU</topic><topic>Saccharomyces cerevisiae</topic><topic>Saccharomyces cerevisiae - genetics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhao, Quanyu</creatorcontrib><creatorcontrib>Kurata, Hiroyuki</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of bioscience and bioengineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhao, Quanyu</au><au>Kurata, Hiroyuki</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Maximum entropy decomposition of flux distribution at steady state to elementary modes</atitle><jtitle>Journal of bioscience and bioengineering</jtitle><addtitle>J Biosci Bioeng</addtitle><date>2009</date><risdate>2009</risdate><volume>107</volume><issue>1</issue><spage>84</spage><epage>89</epage><pages>84-89</pages><issn>1389-1723</issn><eissn>1347-4421</eissn><abstract>Enzyme Control Flux (ECF) is a method of correlating enzyme activity and flux distribution. 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Escherichia coli, and
Saccharomyces cerevisiae cells. The use of the MEP presents the most plausible distribution of EMCs in the absence of any biological hypotheses describing the physiological state of cells, thereby enhancing the prediction accuracy of the flux distribution in various mutants.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><pmid>19147116</pmid><doi>10.1016/j.jbiosc.2008.09.011</doi><tpages>6</tpages></addata></record> |
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| subjects | Algorithms Animals Bacillus subtilis - genetics Biological and medical sciences Biotechnology CELLS CELLULE CELULAS CHO Cells Cricetinae Cricetulus Elementary mode Entropy ENZIMAS ENZYME Enzyme control flux ENZYMES Enzymes - chemistry ESCHERICHIA COLI Escherichia coli - genetics EXPRESION GENICA EXPRESSION DES GENES Fundamental and applied biological sciences. Psychology GENE EXPRESSION HAMSTER HAMSTERS Linear programming Maximum entropy principle Metabolic flux analysis METABOLISM METABOLISME METABOLISMO Models, Biological Models, Statistical Models, Theoretical MUTANT MUTANTES MUTANTS Mutation NETWORKS Quadratic programming REDES Reproducibility of Results RESEAU Saccharomyces cerevisiae Saccharomyces cerevisiae - genetics |
| title | Maximum entropy decomposition of flux distribution at steady state to elementary modes |
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