Approaches in Integrative Bioinformatics: Towards the Virtual Cell PDF
Preview Approaches in Integrative Bioinformatics: Towards the Virtual Cell
Ming Chen Ralf Hofestädt Editors Approaches in Integrative Bioinformatics Towards the Virtual Cell Approaches in Integrative Bioinformatics Ming Chen • Ralf Hofesta¨dt Editors Approaches in Integrative Bioinformatics Towards the Virtual Cell 123 Editors MingChen RalfHofesta¨dt CollegeofLifeSciences DepartmentofBioinformatics ZhejiangUniversity andMedicalInformatics Hangzhou BielefeldUniversity People’sRepublicofChina Bielefeld,Germany Additionalmaterialtothisbookcanbedownloadedfromhttp://extras.springer.com ISBN978-3-642-41280-6 ISBN978-3-642-41281-3(eBook) DOI10.1007/978-3-642-41281-3 SpringerHeidelbergNewYorkDordrechtLondon LibraryofCongressControlNumber:2013956814 ©Springer-VerlagBerlinHeidelberg2014 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpartof thematerialisconcerned,specificallytherightsoftranslation,reprinting,reuseofillustrations,recitation, broadcasting,reproductiononmicrofilmsorinanyotherphysicalway,andtransmissionorinformation storageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilarmethodology nowknownorhereafterdeveloped.Exemptedfromthislegalreservationarebriefexcerptsinconnection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. 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Printedonacid-freepaper SpringerispartofSpringerScience+BusinessMedia(www.springer.com) Preface Theunprecedentedaccumulationofhigh-throughputdatafromgenomics,transcrip- tomics, proteomics, metabolomics, phenomics, etc., has resulted not only in new attemptstoanswertraditionalbiologicalquestionsandsolvelongstandingissuesin biology but also in the formulation of novel hypotheses that arise precisely from this wealth of data. At the present, with thousands of biological data resources andinformationsystemsinsidetheInternet,anunknownnumberofanalysistools, and exponential growths of molecular data (especially high-throughputdata), the storage,processing,description,transmission,connection,andintegrativeanalysis of this data becomesa greatchallenge for bioinformatics.Thus, the so-called Big Data becomes the new keyword describing the actual situation for which new softwaretoolsareneededtoanalyzethisexponentiallyincreasingdata. Importantapplicationsof Big Data are systems biologyand systemsmedicine. For instance, hospital information systems represent complex patient data. The diagnosis process is now supported by new methods of biotechnology using, for example, high-throughput sequencing approaches. Therefore, we have complex patient data inside the hospital information system which needs to be stored, transported,andanalyzed.Newsoftwaretoolsareneededtoallowtheuser-specific dataaccessandanalysisofthisdata.Overall,todevelopandimplementnewtools for automatic data integration and analysis will help implement better diagnostic methods in practice. In the future, the entire genomes of patients will be stored withinhospitalinformationsystems.Furthermore,itwillbenecessarytosharethe genome sequences inside the hospital computer network and analyze the genome data to detect, for example, cancer genes. With the availability of Internet, the automaticintegrationandanalysis of data are of the most relevantresearchtopics incomputerscience.Inbiology,suchtoolshavebecomemoreandmoreimportant. Methodslikehigh-throughputsequencingandomicsanalysisareresponsibleforthe exponentialdatagenerationprocess. This book will focus on the integration and analysis of omics data. The Introductionwillpresentrelevantbiologicalbackgroundandan overviewof these actual methods. When the Internet merged, methods such as data fusion and federated database systems became relevant. The initial tools were implemented v vi Preface andgavebirthtoanewfieldofresearch:IntegrativeBioinformatics,whichstrivesto implementuser-specificintegrationandanalysisofcomplexdata.TheIntroduction of this bookwill givea definitionand overviewof this pertinentfield of research. Since then, complex information systems have been developed and implemented. Finally, the data warehouse concept became more relevant. Today the data ware- house concept is still the best construction for the implementation of integrative information systems. The Information Fusion and Retrieval section will focus on the said data warehouse concept. Furthermore, this part of the book will give an overview of information retrieval and data mining tools, which allow the user- specificidentificationandintegrationofdata.Basedonthemethodsdescribedhere, weareabletoimplementuser-specificintegrationtools.Theanalysisofthisdatacan bedoneusingstatistic,visualization,oranimationtools.Furthermore,modelingand simulation are importantanalysis methods. The Network Visualization, Modeling, and Analysis section will focus on methods for network prediction, network modeling,andsimulation.Inthecaseofnetworksimulation,wepreferthePetrinet method,whichallowstheparallelsimulationofcomplexmetabolicpathways.Our applicationsectionisdividedintotwoparts.First,wefocusonmethodsofBioData Mapping. One interesting aspect is the possibility of molecular disease mapping whichallowsthepathwaypredictionofanydiseaseandthesemiautomaticmapping of this pathway into a virtual 3D cell. The genotype-phenotype map enables us touncoverthecasualnetworksinsidethe“blackbox”thatliesbetweengenotypes andphenotypeswithadvancesinhigh-throughputandhigh-dimensionalgenotyping andphenotypingtechnologies.Anotherimportantandactualtopic ispresentedby theBiocomputionsection.Afterthereconstructionofabiologicaldiseasenetwork, theidentificationofbiomarkersorhubsforfurtheranalysisisimportant.Torealize suchtasks,theimplementationofparallelalgorithmsisfundamental. Importantresearch topics for the nextfew years will be Big Data and Systems Medicine.IntegrativeBioinformaticswillbefundamentalindevelopmentsforboth fieldsandthisbookattemptstopresentanoverviewofrelevantandactualresearch activities. We are very grateful to all the authors for sharing their time, wisdom, and expertise. Finally, we want to thank Ms. Na Xu, the editor of Springer Beijing Office,forhercontinuousadvice. Hangzhou,People’sRepublicofChina MingChen Bielefeld,Germany RalfHofesta¨dt June2013 Contents PartI Introduction 1 IntegrativeBioinformatics................................................. 3 MingChenandRalfHofesta¨dt 2 AnOverviewofGeneRegulation......................................... 21 AndrewHarrisonandHughShanahan PartII InformationFusionandRetrieval 3 InformationRetrievalinLifeSciences:AProgrammaticSurvey..... 73 Matthias Lange, Ron Henkel, Wolfgang Mu¨ller, DagmarWaltemath,andStephanWeise 4 DataWarehousesinBioinformatics...................................... 111 BenjaminKormeier 5 MolecularInformationFusioninOndex ................................ 131 JanTaubertandJacobKo¨hler 6 TextMiningonPubMed................................................... 161 TimofeyV.Ivanisenko, PavelS.Demenkov, andVladimirA.Ivanisenko PartIII NetworkVisualization,ModelingandAnalysis 7 NetworkVisualizationforIntegrativeBioinformatics.................. 173 AndreasKerrenandFalkSchreiber 8 BiologicalNetworkModelingandAnalysis.............................. 203 Sebastian Jan Janowski, Barbara Kaltschmidt, andChristianKaltschmidt vii viii Contents 9 PetriNets for Modeling and Analyzing Biochemical ReactionNetworks ......................................................... 245 FeiLiuandMonikaHeiner PartIV BioDataMapping 10 NetworkAnalysisandIntegrationinaVirtualCellEnvironment.... 275 Bjo¨rnSommer 11 BridgingGenomicsandPhenomics ...................................... 299 DijunChen, MingChen, ThomasAltmann, andChristianKlukas PartV Biocompution 12 ParallelComputingforGeneNetworksReverseEngineering ........ 337 JaroslawZola 13 ComputationalBiomarkerDiscovery .................................... 355 FanZhang,XiaogangWu,andJakeY.Chen Part I Introduction
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