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1、CHAPTER4MaterialBalancesandDataConsistencyQuantitativeanalysisofmetabolismrequiresexperimentaldataforthedeterminationofmetabolicfluxes,fluxdistributions,andmeasuresoffluxcontrol(seeChapter11),amongotherparameters.Assuch,thesecalcula-tionsexemplifymethodsandproced
2、uresforupgradingtheinformationcon-tentofprimaryfermentationdata.Whereasourfocusinthisbookisonmetabolismanditscontrol,thebasicphilosophyofinformationcontentupgradeisapplicablethroughoutthelifesciences,solongasquantitativemeasurementsareavailable.Becausethesemethod
3、sofinformationupgradearedata-driven,itisoftheutmostimportancetoensurethereliabilityofthedataused.Thiscanbedonebyapplyingtheusualmethodsofrandomerrorminimization,i.e.useofrepeatexperiments,multiplesensors,carefulcalibrations,etc.Anaddi-tionalconsideration(whichist
4、hesubjectofthischapter)istheintroductionofdataredundancyforthevalidationofboththeactualmeasurements,andthebroadermechanisticframeworkwithinwhichsuchmeasurementsare115116MetabolicEngineeringanalyzed.Forexample,inthecontextofmetabolicanalysis,fluxcalculationsarebas
5、edonthemeasurementofthespecificratesforsubstrateuptakeandproductformation,whichrepresentthefluxesinandoutofthecells.Beforeanysuchderivativecalculationsarecarriedout,itisimportantthattheconsistencyofthedatabeconfirmed,forexample,theclosureofthecarbonbalance.Datare
6、dundancyisintroducedwhenmultiplesensorsareemployedforthemeasurementofthesamevariableorwhencertainconstraintsmustbesatisfiedbythemeasurementssoobtained,suchasclosureofmaterialbalances.Obviously,thegreatertheredundancy,thehigherthedegreeofconfidenceforthedataandthe
7、irderivativeparameters.Furthermore,redun-danciescanbeemployedforthesystematicdetectionofthesourceofgrossmeasurementerrorsortheidentificationofaparticularelementoftheframework(i.e.model)mostlikelyresponsibleforanyobservedinconsisten-cies.Wedemonstratetheseideasint
8、hischapterinthecontextoffluxes,metabolism,andmaterialbalances.Forthispurpose,experimentaldatathataretobeusedforquantitativeanalysismustbeComplete.Thisdoesnotme
