Metabolic Flux Analysis View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2012

AUTHORS

Tae Hoon Yang

ABSTRACT

In modern metabolomics, cellular reactions are observed as an integrated and networked system, termed as the metabolic network, instead of individual enzymatic reactions. Based on the metabolic network quantitated in terms of fluxes which are the rates at which materials are processed through the metabolic pathways, functional and regulatory activities of cells can be understood in its entirety. Typically, a realistic metabolic network which comprises catabolic and anabolic pathway fluxes of cells represents an underdetermined system from a stoichiometric viewpoint. This yields the intracellular fluxes that cannot be calculated from other fluxes measured. In order to determine those fluxes, 13C labeling information is most frequently applied. This involves mathematical models that compute distributions of fluxes together with experimental tools for 13C labeling analysis. In this regard, understating the modeling techniques that aim the metabolic flux analysis using 13C isotopomer analysis is one central issue of metabolomics. Therefore, we describe the principle of different modeling strategies of the metabolic flux analysis in this chapter. First, we introduce the stoichiometry-based approach which is the foundation of the 13C-based approaches. Further to this, the modeling aspect of 13C-based approaches and related tools such as computer-aided optimal design of 13C labeling experiments and numerical computation of fluxes from measured 13C labeling states of metabolic products are treated. Also, the mathematical and statistical background is provided, which are relevant to the modeling of 13C-based metabolic flux analysis. More... »

PAGES

231-277

References to SciGraph publications

  • 2002-03-05. Metabolic Flux Analysis Using Mass Spectrometry in TOOLS AND APPLICATIONS OF BIOCHEMICAL ENGINEERING SCIENCE
  • 2005. From Stationary to Instationary Metabolic Flux Analysis in TECHNOLOGY TRANSFER IN BIOTECHNOLOGY
  • 2004-10. Exploiting biological complexity for strain improvement through systems biology in NATURE BIOTECHNOLOGY
  • 1999. Numerical Optimization in NONE
  • 2001-04. Metabolic engineering in APPLIED MICROBIOLOGY AND BIOTECHNOLOGY
  • Book

    TITLE

    The Handbook of Metabolomics

    ISBN

    978-1-61779-617-3
    978-1-61779-618-0

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-1-61779-618-0_8

    DOI

    http://dx.doi.org/10.1007/978-1-61779-618-0_8

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1037767828


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0104", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Statistics", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Mathematical Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Genomatica (United States)", 
              "id": "https://www.grid.ac/institutes/grid.420355.5", 
              "name": [
                "Genomatica, Inc., San Diego, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Yang", 
            "givenName": "Tae Hoon", 
            "id": "sg:person.0674741700.24", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0674741700.24"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1016/j.compbiolchem.2005.02.005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000159546"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.copbio.2003.11.001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002101934"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1058079", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002799894"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/(sici)1097-0290(1999)66:2<86::aid-bit2>3.0.co;2-a", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003373695"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1128/aem.68.12.5843-5859.2002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003807814"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/(sici)1097-0290(19960120)49:2<111::aid-bit1>3.0.co;2-t", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005937734"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1006/jtbi.1993.1202", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006090348"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ymben.2006.06.005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006723154"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1006/mben.2001.0187", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009229172"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1146/annurev.nutr.23.011702.073045", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009315963"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0168-1656(99)00021-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010023637"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1146/annurev.nutr.17.1.559", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010346149"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/(sici)1097-0290(20000320)67:6<872::aid-bit21>3.0.co;2-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010547038"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/bp00029a006", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010711822"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0168-1656(03)00169-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011156480"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0168-1656(03)00169-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011156480"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1046/j.1432-1327.2001.02129.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011497191"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ymben.2006.03.002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013160347"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/bit.21063", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013221991"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1046/j.1432-1327.1998.2520360.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013627258"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/(sici)1097-0290(19980420)58:2/3<119::aid-bit1>3.0.co;2-o", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014486527"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ymben.2006.09.001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014502509"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/bit.1145", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014754079"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/b98874", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015038119", 
              "https://doi.org/10.1007/b98874"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/b98874", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015038119", 
              "https://doi.org/10.1007/b98874"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/b98874", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015038119", 
              "https://doi.org/10.1007/b98874"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/bit.10429", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016251379"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1074/jbc.274.25.17410", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016660230"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1006/mben.2001.0188", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016794596"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/(sici)1097-0290(19970705)55:1<101::aid-bit12>3.0.co;2-p", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018134655"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/(sici)1097-0290(19970705)55:1<118::aid-bit13>3.0.co;2-i", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019657373"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s002530000511", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020346069", 
              "https://doi.org/10.1007/s002530000511"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1006/mben.1999.0117", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022845199"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/bit.10153", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024407210"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/bit.260430103", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025145521"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0168-1656(01)00418-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026546617"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1006/mben.2002.0226", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031500232"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1006/mben.2002.0226", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031500232"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/j.1365-313x.2005.02649.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031726010"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/j.1365-313x.2005.02649.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031726010"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/(sici)1097-0290(19980420)58:2/3<258::aid-bit20>3.0.co;2-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032346709"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/b98921", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034799297", 
              "https://doi.org/10.1007/b98921"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1006/mben.1998.0101", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036215423"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/(sici)1097-0290(19970920)55:6<831::aid-bit2>3.0.co;2-h", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039569952"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/(sici)1097-0290(1999)66:2<69::aid-bit1>3.0.co;2-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039802414"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1146/annurev.physiol.63.1.15", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040238705"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/bit.1143", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040456316"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1006/mben.2001.0184", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040970069"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1515/9781400862528", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040993678"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ymben.2004.02.002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042110275"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0168-1656(99)00205-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042800978"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.95.2.708", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043123527"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ymben.2004.02.003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044205250"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt1016", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046604893", 
              "https://doi.org/10.1038/nbt1016"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt1016", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046604893", 
              "https://doi.org/10.1038/nbt1016"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/3-540-45736-4_3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047074836", 
              "https://doi.org/10.1007/3-540-45736-4_3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/3-540-45736-4_3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047074836", 
              "https://doi.org/10.1007/3-540-45736-4_3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0168-1656(02)00316-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049659955"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0168-1656(02)00316-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049659955"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/14.10.869", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050074049"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/bit.1154", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050113154"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/bp000058h", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051092450"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/nbm.795", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051620821"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/bit.1109", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053392143"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/pcp/pcg063", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053531556"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1088/0143-0807/24/3/701", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1059035463"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1152/ajpendo.1999.276.6.e1146", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1074473740"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1082595939", 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1137/1.9780898719857", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1098555834"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2012", 
        "datePublishedReg": "2012-01-01", 
        "description": "In modern metabolomics, cellular reactions are observed as an integrated and networked system, termed as the metabolic network, instead of individual enzymatic reactions. Based on the metabolic network quantitated in terms of fluxes which are the rates at which materials are processed through the metabolic pathways, functional and regulatory activities of cells can be understood in its entirety. Typically, a realistic metabolic network which comprises catabolic and anabolic pathway fluxes of cells represents an underdetermined system from a stoichiometric viewpoint. This yields the intracellular fluxes that cannot be calculated from other fluxes measured. In order to determine those fluxes, 13C labeling information is most frequently applied. This involves mathematical models that compute distributions of fluxes together with experimental tools for 13C labeling analysis. In this regard, understating the modeling techniques that aim the metabolic flux analysis using 13C isotopomer analysis is one central issue of metabolomics. Therefore, we describe the principle of different modeling strategies of the metabolic flux analysis in this chapter. First, we introduce the stoichiometry-based approach which is the foundation of the 13C-based approaches. Further to this, the modeling aspect of 13C-based approaches and related tools such as computer-aided optimal design of 13C labeling experiments and numerical computation of fluxes from measured 13C labeling states of metabolic products are treated. Also, the mathematical and statistical background is provided, which are relevant to the modeling of 13C-based metabolic flux analysis.", 
        "editor": [
          {
            "familyName": "Fan", 
            "givenName": "Teresa Whei-Mei", 
            "type": "Person"
          }, 
          {
            "familyName": "Lane", 
            "givenName": "Andrew N.", 
            "type": "Person"
          }, 
          {
            "familyName": "Higashi", 
            "givenName": "Richard M.", 
            "type": "Person"
          }
        ], 
        "genre": "chapter", 
        "id": "sg:pub.10.1007/978-1-61779-618-0_8", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": {
          "isbn": [
            "978-1-61779-617-3", 
            "978-1-61779-618-0"
          ], 
          "name": "The Handbook of Metabolomics", 
          "type": "Book"
        }, 
        "name": "Metabolic Flux Analysis", 
        "pagination": "231-277", 
        "productId": [
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/978-1-61779-618-0_8"
            ]
          }, 
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "b3ea2b270521e1fd4eaab3bea2bf637b97c661665ae77f37f9c8b95d0b773328"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1037767828"
            ]
          }
        ], 
        "publisher": {
          "location": "Totowa, NJ", 
          "name": "Humana Press", 
          "type": "Organisation"
        }, 
        "sameAs": [
          "https://doi.org/10.1007/978-1-61779-618-0_8", 
          "https://app.dimensions.ai/details/publication/pub.1037767828"
        ], 
        "sdDataset": "chapters", 
        "sdDatePublished": "2019-04-15T15:22", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8672_00000266.jsonl", 
        "type": "Chapter", 
        "url": "http://link.springer.com/10.1007/978-1-61779-618-0_8"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-1-61779-618-0_8'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-1-61779-618-0_8'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-1-61779-618-0_8'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-1-61779-618-0_8'


     

    This table displays all metadata directly associated to this object as RDF triples.

    262 TRIPLES      23 PREDICATES      88 URIs      20 LITERALS      8 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/978-1-61779-618-0_8 schema:about anzsrc-for:01
    2 anzsrc-for:0104
    3 schema:author N7c639a584a89403db81112b219131c6e
    4 schema:citation sg:pub.10.1007/3-540-45736-4_3
    5 sg:pub.10.1007/b98874
    6 sg:pub.10.1007/b98921
    7 sg:pub.10.1007/s002530000511
    8 sg:pub.10.1038/nbt1016
    9 https://app.dimensions.ai/details/publication/pub.1082595939
    10 https://doi.org/10.1002/(sici)1097-0290(19960120)49:2<111::aid-bit1>3.0.co;2-t
    11 https://doi.org/10.1002/(sici)1097-0290(19970705)55:1<101::aid-bit12>3.0.co;2-p
    12 https://doi.org/10.1002/(sici)1097-0290(19970705)55:1<118::aid-bit13>3.0.co;2-i
    13 https://doi.org/10.1002/(sici)1097-0290(19970920)55:6<831::aid-bit2>3.0.co;2-h
    14 https://doi.org/10.1002/(sici)1097-0290(19980420)58:2/3<119::aid-bit1>3.0.co;2-o
    15 https://doi.org/10.1002/(sici)1097-0290(19980420)58:2/3<258::aid-bit20>3.0.co;2-7
    16 https://doi.org/10.1002/(sici)1097-0290(1999)66:2<69::aid-bit1>3.0.co;2-6
    17 https://doi.org/10.1002/(sici)1097-0290(1999)66:2<86::aid-bit2>3.0.co;2-a
    18 https://doi.org/10.1002/(sici)1097-0290(20000320)67:6<872::aid-bit21>3.0.co;2-x
    19 https://doi.org/10.1002/bit.10153
    20 https://doi.org/10.1002/bit.10429
    21 https://doi.org/10.1002/bit.1109
    22 https://doi.org/10.1002/bit.1143
    23 https://doi.org/10.1002/bit.1145
    24 https://doi.org/10.1002/bit.1154
    25 https://doi.org/10.1002/bit.21063
    26 https://doi.org/10.1002/bit.260430103
    27 https://doi.org/10.1002/nbm.795
    28 https://doi.org/10.1006/jtbi.1993.1202
    29 https://doi.org/10.1006/mben.1998.0101
    30 https://doi.org/10.1006/mben.1999.0117
    31 https://doi.org/10.1006/mben.2001.0184
    32 https://doi.org/10.1006/mben.2001.0187
    33 https://doi.org/10.1006/mben.2001.0188
    34 https://doi.org/10.1006/mben.2002.0226
    35 https://doi.org/10.1016/j.compbiolchem.2005.02.005
    36 https://doi.org/10.1016/j.copbio.2003.11.001
    37 https://doi.org/10.1016/j.ymben.2004.02.002
    38 https://doi.org/10.1016/j.ymben.2004.02.003
    39 https://doi.org/10.1016/j.ymben.2006.03.002
    40 https://doi.org/10.1016/j.ymben.2006.06.005
    41 https://doi.org/10.1016/j.ymben.2006.09.001
    42 https://doi.org/10.1016/s0168-1656(01)00418-7
    43 https://doi.org/10.1016/s0168-1656(02)00316-4
    44 https://doi.org/10.1016/s0168-1656(03)00169-x
    45 https://doi.org/10.1016/s0168-1656(99)00021-8
    46 https://doi.org/10.1016/s0168-1656(99)00205-9
    47 https://doi.org/10.1021/bp000058h
    48 https://doi.org/10.1021/bp00029a006
    49 https://doi.org/10.1046/j.1432-1327.1998.2520360.x
    50 https://doi.org/10.1046/j.1432-1327.2001.02129.x
    51 https://doi.org/10.1073/pnas.95.2.708
    52 https://doi.org/10.1074/jbc.274.25.17410
    53 https://doi.org/10.1088/0143-0807/24/3/701
    54 https://doi.org/10.1093/bioinformatics/14.10.869
    55 https://doi.org/10.1093/pcp/pcg063
    56 https://doi.org/10.1111/j.1365-313x.2005.02649.x
    57 https://doi.org/10.1126/science.1058079
    58 https://doi.org/10.1128/aem.68.12.5843-5859.2002
    59 https://doi.org/10.1137/1.9780898719857
    60 https://doi.org/10.1146/annurev.nutr.17.1.559
    61 https://doi.org/10.1146/annurev.nutr.23.011702.073045
    62 https://doi.org/10.1146/annurev.physiol.63.1.15
    63 https://doi.org/10.1152/ajpendo.1999.276.6.e1146
    64 https://doi.org/10.1515/9781400862528
    65 schema:datePublished 2012
    66 schema:datePublishedReg 2012-01-01
    67 schema:description In modern metabolomics, cellular reactions are observed as an integrated and networked system, termed as the metabolic network, instead of individual enzymatic reactions. Based on the metabolic network quantitated in terms of fluxes which are the rates at which materials are processed through the metabolic pathways, functional and regulatory activities of cells can be understood in its entirety. Typically, a realistic metabolic network which comprises catabolic and anabolic pathway fluxes of cells represents an underdetermined system from a stoichiometric viewpoint. This yields the intracellular fluxes that cannot be calculated from other fluxes measured. In order to determine those fluxes, 13C labeling information is most frequently applied. This involves mathematical models that compute distributions of fluxes together with experimental tools for 13C labeling analysis. In this regard, understating the modeling techniques that aim the metabolic flux analysis using 13C isotopomer analysis is one central issue of metabolomics. Therefore, we describe the principle of different modeling strategies of the metabolic flux analysis in this chapter. First, we introduce the stoichiometry-based approach which is the foundation of the 13C-based approaches. Further to this, the modeling aspect of 13C-based approaches and related tools such as computer-aided optimal design of 13C labeling experiments and numerical computation of fluxes from measured 13C labeling states of metabolic products are treated. Also, the mathematical and statistical background is provided, which are relevant to the modeling of 13C-based metabolic flux analysis.
    68 schema:editor N57447ea2787540cea1813c7b70993ff4
    69 schema:genre chapter
    70 schema:inLanguage en
    71 schema:isAccessibleForFree false
    72 schema:isPartOf Nc46cfe2803034e90b45085d9ef836ab9
    73 schema:name Metabolic Flux Analysis
    74 schema:pagination 231-277
    75 schema:productId N7a50ff729ef941769276277203b1ce97
    76 Na1cb3639e8584ba7a15b2bb9be1dcf8d
    77 Ne96b0d7912a546c49b6aca638ecf661c
    78 schema:publisher Naec54c9543d049fa910f53ca97ebf227
    79 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037767828
    80 https://doi.org/10.1007/978-1-61779-618-0_8
    81 schema:sdDatePublished 2019-04-15T15:22
    82 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    83 schema:sdPublisher Nbffdfbe393274d4dab2c9c6a1b373e51
    84 schema:url http://link.springer.com/10.1007/978-1-61779-618-0_8
    85 sgo:license sg:explorer/license/
    86 sgo:sdDataset chapters
    87 rdf:type schema:Chapter
    88 N3fbf86348f2547789565e77dc7451352 schema:familyName Fan
    89 schema:givenName Teresa Whei-Mei
    90 rdf:type schema:Person
    91 N57447ea2787540cea1813c7b70993ff4 rdf:first N3fbf86348f2547789565e77dc7451352
    92 rdf:rest Nbf59b33d3564491aa1115e0d2adbc22d
    93 N7a50ff729ef941769276277203b1ce97 schema:name doi
    94 schema:value 10.1007/978-1-61779-618-0_8
    95 rdf:type schema:PropertyValue
    96 N7c639a584a89403db81112b219131c6e rdf:first sg:person.0674741700.24
    97 rdf:rest rdf:nil
    98 N9b5d7e192dea4ab2a733a53f6a90a0e9 rdf:first Nfe8bc93587684ccd978556f0bd123973
    99 rdf:rest rdf:nil
    100 Na1cb3639e8584ba7a15b2bb9be1dcf8d schema:name readcube_id
    101 schema:value b3ea2b270521e1fd4eaab3bea2bf637b97c661665ae77f37f9c8b95d0b773328
    102 rdf:type schema:PropertyValue
    103 Naec54c9543d049fa910f53ca97ebf227 schema:location Totowa, NJ
    104 schema:name Humana Press
    105 rdf:type schema:Organisation
    106 Nbf59b33d3564491aa1115e0d2adbc22d rdf:first Nc93dd95063be4b179c5e3d6ad9e70446
    107 rdf:rest N9b5d7e192dea4ab2a733a53f6a90a0e9
    108 Nbffdfbe393274d4dab2c9c6a1b373e51 schema:name Springer Nature - SN SciGraph project
    109 rdf:type schema:Organization
    110 Nc46cfe2803034e90b45085d9ef836ab9 schema:isbn 978-1-61779-617-3
    111 978-1-61779-618-0
    112 schema:name The Handbook of Metabolomics
    113 rdf:type schema:Book
    114 Nc93dd95063be4b179c5e3d6ad9e70446 schema:familyName Lane
    115 schema:givenName Andrew N.
    116 rdf:type schema:Person
    117 Ne96b0d7912a546c49b6aca638ecf661c schema:name dimensions_id
    118 schema:value pub.1037767828
    119 rdf:type schema:PropertyValue
    120 Nfe8bc93587684ccd978556f0bd123973 schema:familyName Higashi
    121 schema:givenName Richard M.
    122 rdf:type schema:Person
    123 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
    124 schema:name Mathematical Sciences
    125 rdf:type schema:DefinedTerm
    126 anzsrc-for:0104 schema:inDefinedTermSet anzsrc-for:
    127 schema:name Statistics
    128 rdf:type schema:DefinedTerm
    129 sg:person.0674741700.24 schema:affiliation https://www.grid.ac/institutes/grid.420355.5
    130 schema:familyName Yang
    131 schema:givenName Tae Hoon
    132 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0674741700.24
    133 rdf:type schema:Person
    134 sg:pub.10.1007/3-540-45736-4_3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047074836
    135 https://doi.org/10.1007/3-540-45736-4_3
    136 rdf:type schema:CreativeWork
    137 sg:pub.10.1007/b98874 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015038119
    138 https://doi.org/10.1007/b98874
    139 rdf:type schema:CreativeWork
    140 sg:pub.10.1007/b98921 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034799297
    141 https://doi.org/10.1007/b98921
    142 rdf:type schema:CreativeWork
    143 sg:pub.10.1007/s002530000511 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020346069
    144 https://doi.org/10.1007/s002530000511
    145 rdf:type schema:CreativeWork
    146 sg:pub.10.1038/nbt1016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046604893
    147 https://doi.org/10.1038/nbt1016
    148 rdf:type schema:CreativeWork
    149 https://app.dimensions.ai/details/publication/pub.1082595939 schema:CreativeWork
    150 https://doi.org/10.1002/(sici)1097-0290(19960120)49:2<111::aid-bit1>3.0.co;2-t schema:sameAs https://app.dimensions.ai/details/publication/pub.1005937734
    151 rdf:type schema:CreativeWork
    152 https://doi.org/10.1002/(sici)1097-0290(19970705)55:1<101::aid-bit12>3.0.co;2-p schema:sameAs https://app.dimensions.ai/details/publication/pub.1018134655
    153 rdf:type schema:CreativeWork
    154 https://doi.org/10.1002/(sici)1097-0290(19970705)55:1<118::aid-bit13>3.0.co;2-i schema:sameAs https://app.dimensions.ai/details/publication/pub.1019657373
    155 rdf:type schema:CreativeWork
    156 https://doi.org/10.1002/(sici)1097-0290(19970920)55:6<831::aid-bit2>3.0.co;2-h schema:sameAs https://app.dimensions.ai/details/publication/pub.1039569952
    157 rdf:type schema:CreativeWork
    158 https://doi.org/10.1002/(sici)1097-0290(19980420)58:2/3<119::aid-bit1>3.0.co;2-o schema:sameAs https://app.dimensions.ai/details/publication/pub.1014486527
    159 rdf:type schema:CreativeWork
    160 https://doi.org/10.1002/(sici)1097-0290(19980420)58:2/3<258::aid-bit20>3.0.co;2-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032346709
    161 rdf:type schema:CreativeWork
    162 https://doi.org/10.1002/(sici)1097-0290(1999)66:2<69::aid-bit1>3.0.co;2-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039802414
    163 rdf:type schema:CreativeWork
    164 https://doi.org/10.1002/(sici)1097-0290(1999)66:2<86::aid-bit2>3.0.co;2-a schema:sameAs https://app.dimensions.ai/details/publication/pub.1003373695
    165 rdf:type schema:CreativeWork
    166 https://doi.org/10.1002/(sici)1097-0290(20000320)67:6<872::aid-bit21>3.0.co;2-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1010547038
    167 rdf:type schema:CreativeWork
    168 https://doi.org/10.1002/bit.10153 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024407210
    169 rdf:type schema:CreativeWork
    170 https://doi.org/10.1002/bit.10429 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016251379
    171 rdf:type schema:CreativeWork
    172 https://doi.org/10.1002/bit.1109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053392143
    173 rdf:type schema:CreativeWork
    174 https://doi.org/10.1002/bit.1143 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040456316
    175 rdf:type schema:CreativeWork
    176 https://doi.org/10.1002/bit.1145 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014754079
    177 rdf:type schema:CreativeWork
    178 https://doi.org/10.1002/bit.1154 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050113154
    179 rdf:type schema:CreativeWork
    180 https://doi.org/10.1002/bit.21063 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013221991
    181 rdf:type schema:CreativeWork
    182 https://doi.org/10.1002/bit.260430103 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025145521
    183 rdf:type schema:CreativeWork
    184 https://doi.org/10.1002/nbm.795 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051620821
    185 rdf:type schema:CreativeWork
    186 https://doi.org/10.1006/jtbi.1993.1202 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006090348
    187 rdf:type schema:CreativeWork
    188 https://doi.org/10.1006/mben.1998.0101 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036215423
    189 rdf:type schema:CreativeWork
    190 https://doi.org/10.1006/mben.1999.0117 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022845199
    191 rdf:type schema:CreativeWork
    192 https://doi.org/10.1006/mben.2001.0184 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040970069
    193 rdf:type schema:CreativeWork
    194 https://doi.org/10.1006/mben.2001.0187 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009229172
    195 rdf:type schema:CreativeWork
    196 https://doi.org/10.1006/mben.2001.0188 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016794596
    197 rdf:type schema:CreativeWork
    198 https://doi.org/10.1006/mben.2002.0226 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031500232
    199 rdf:type schema:CreativeWork
    200 https://doi.org/10.1016/j.compbiolchem.2005.02.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000159546
    201 rdf:type schema:CreativeWork
    202 https://doi.org/10.1016/j.copbio.2003.11.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002101934
    203 rdf:type schema:CreativeWork
    204 https://doi.org/10.1016/j.ymben.2004.02.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042110275
    205 rdf:type schema:CreativeWork
    206 https://doi.org/10.1016/j.ymben.2004.02.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044205250
    207 rdf:type schema:CreativeWork
    208 https://doi.org/10.1016/j.ymben.2006.03.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013160347
    209 rdf:type schema:CreativeWork
    210 https://doi.org/10.1016/j.ymben.2006.06.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006723154
    211 rdf:type schema:CreativeWork
    212 https://doi.org/10.1016/j.ymben.2006.09.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014502509
    213 rdf:type schema:CreativeWork
    214 https://doi.org/10.1016/s0168-1656(01)00418-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026546617
    215 rdf:type schema:CreativeWork
    216 https://doi.org/10.1016/s0168-1656(02)00316-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049659955
    217 rdf:type schema:CreativeWork
    218 https://doi.org/10.1016/s0168-1656(03)00169-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1011156480
    219 rdf:type schema:CreativeWork
    220 https://doi.org/10.1016/s0168-1656(99)00021-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010023637
    221 rdf:type schema:CreativeWork
    222 https://doi.org/10.1016/s0168-1656(99)00205-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042800978
    223 rdf:type schema:CreativeWork
    224 https://doi.org/10.1021/bp000058h schema:sameAs https://app.dimensions.ai/details/publication/pub.1051092450
    225 rdf:type schema:CreativeWork
    226 https://doi.org/10.1021/bp00029a006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010711822
    227 rdf:type schema:CreativeWork
    228 https://doi.org/10.1046/j.1432-1327.1998.2520360.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1013627258
    229 rdf:type schema:CreativeWork
    230 https://doi.org/10.1046/j.1432-1327.2001.02129.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1011497191
    231 rdf:type schema:CreativeWork
    232 https://doi.org/10.1073/pnas.95.2.708 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043123527
    233 rdf:type schema:CreativeWork
    234 https://doi.org/10.1074/jbc.274.25.17410 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016660230
    235 rdf:type schema:CreativeWork
    236 https://doi.org/10.1088/0143-0807/24/3/701 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059035463
    237 rdf:type schema:CreativeWork
    238 https://doi.org/10.1093/bioinformatics/14.10.869 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050074049
    239 rdf:type schema:CreativeWork
    240 https://doi.org/10.1093/pcp/pcg063 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053531556
    241 rdf:type schema:CreativeWork
    242 https://doi.org/10.1111/j.1365-313x.2005.02649.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1031726010
    243 rdf:type schema:CreativeWork
    244 https://doi.org/10.1126/science.1058079 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002799894
    245 rdf:type schema:CreativeWork
    246 https://doi.org/10.1128/aem.68.12.5843-5859.2002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003807814
    247 rdf:type schema:CreativeWork
    248 https://doi.org/10.1137/1.9780898719857 schema:sameAs https://app.dimensions.ai/details/publication/pub.1098555834
    249 rdf:type schema:CreativeWork
    250 https://doi.org/10.1146/annurev.nutr.17.1.559 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010346149
    251 rdf:type schema:CreativeWork
    252 https://doi.org/10.1146/annurev.nutr.23.011702.073045 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009315963
    253 rdf:type schema:CreativeWork
    254 https://doi.org/10.1146/annurev.physiol.63.1.15 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040238705
    255 rdf:type schema:CreativeWork
    256 https://doi.org/10.1152/ajpendo.1999.276.6.e1146 schema:sameAs https://app.dimensions.ai/details/publication/pub.1074473740
    257 rdf:type schema:CreativeWork
    258 https://doi.org/10.1515/9781400862528 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040993678
    259 rdf:type schema:CreativeWork
    260 https://www.grid.ac/institutes/grid.420355.5 schema:alternateName Genomatica (United States)
    261 schema:name Genomatica, Inc., San Diego, CA, USA
    262 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...