生物谷编者按：目前大量的基因转录和表达资源，但却没有良好的实验方法和手段，本文提供了一个新的思路去分析这些大量信息，生物信息学专业人员应该值得参考，后附全文下载（PDF）

High-throughputproteinanalysisintegratingbioinformaticsandexperimentalassays.

NucleicAcidsRes.2004Feb3;32(2):742-8

Thewealthoftranscriptinformationthathasbeenmadepubliclyavailableinrecentyearsrequiresthedevelopmentofhigh-throughputfunctionalgenomicsandproteomicsapproachesforitsanalysis.Suchapproachesneedsuitabledataintegrationproceduresandahighlevelofautomationinordertogainmaximumbenefitfromtheresultsgenerated.WehavedesignedanautomaticpipelinetoanalyseannotatedopenreADIngframes(ORFs)stemmingfromfull-lengthCDNAsproducedmainlybytheGermancDNAConsortium.TheORFsareclonedintoexpressionvectorsforuseinlarge-scaleassayssuchasthedeterminationofsubcellularproteinlocalizationorkinasereactionspecificity.Additionally,allidentifiedORFsundergoexhaustivebioinformaticanalysissuchassimilaritysearches,proteindomainarchitecturedeterminationandpredictionofphysicochemicalcharacteristicsandsecondarystructure,usingawidevarietyofbioinformaticmethodsincombinationwiththemostup-to-datepublicdatabases(e.g.PRINTS,BLOCKS,INTERPRO,PROSITESWISSPROT).Datafromexperimentalresultsandfromthebioinformaticanalysisareintegratedandstoredinarelationaldatabase(MSSQL-Server),whichmakesitpossIBLeforresearcherstofindanswerstoBIOLOGicalquestionseasily,therebyspeedinguptheselectionoftargetsforfurtheranalysis.ThedesignedpipelineconstitutesanewautomaticapproachtoobtainingandadmiNISTratingrelevantbiologicaldatafromhigh-throughputinvestigationsofcDNAsinordertosystematicallyidentifyandcharacterizenovelgenes,aswellastocomprehensivelydescribethefunctionoftheencodedproteins.

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