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Statistical Methods in Molecular Biology

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ISBN 10: 1607615789 / ISBN 13: 9781607615781
Published by Humana Press
New Condition New Hardcover
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Hardcover. 636 pages. Dimensions: 10.0in. x 7.0in. x 1.4in.Thisbookisintendedformolecularbiologistswhoperformquantitativeanalysesondata emanatingfromtheireldandforthestatisticianswhoworkwithmolecularbiologists andotherbiomedicalresearchers. Therearemanyexcellenttextbooksthatprovidefun- mentalcomponentsforstatisticaltrainingcurricula. Therearealsomanybyexpertsfor expertsbooksinstatisticsandmolecularbiologywhichrequirein-depthknowledgein bothsubjectstobetakenfulladvantageof. Sofar, nobookinstatisticshasbeenpublished thatprovidesthebasicprinciplesofproperstatisticalanalysesandprogressestoamore advancedstatisticsinresponsetorapidlydevelopingtechnologiesandmethodologiesin theeldofmolecularbiology. Respondingtothissituation, ourbookaimsatbridgingthegapbetweenthesetwo extremes. Molecularbiologistswillbenetfromtheprogressivestyleofthebookwhere basicstatisticalmethodsareintroducedandgraduallyelevatedtoanintermediatelevel. Similarly, statisticianswillbenetfromlearningthevariousbiologicaldatageneratedfrom theeldofmolecularbiology, thetypesofquestionsofinteresttomolecularbiologists, andthestatisticalapproachestoanalyzingthedata. Thestatisticalconceptsandmethods relevanttostudiesinmolecularbiologyarepresentedinasimpleandpracticalmanner. Specically, thebookcoversbasicandintermediatestatisticsthatareusefulforclassical and molecular biology settings and advanced statistical techniques that can be used to helpsolveproblemscommonlyencounteredinmodernmolecularbiologystudies, such assupervisedandunsupervisedlearning, hiddenMarkovmodels, manipulationandan- ysisofdatafromhigh-throughputmicroarrayandproteomicplatform, andsynthesisof these evidences. A tutorial-type format is used to maximize learning in some chapters. Advicefromjournaleditorsonpeer-reviewedpublicationandsomeusefulinformationon softwareimplementationarealsoprovided. Thisbookisrecommendedforuseassupplementarymaterialbothinsideandoutside classroomsorasaself-learningguideforstudents, scientists, andresearcherswhodealwith numericdatainmolecularbiologyandrelatedelds. Thosewhostartasbeginners, but desiretobeatanintermediatelevel, willndthisbookespeciallyusefulintheirlearning pathway. WewanttothankJohnWalker(serieseditor), PatrickMarton, DavidCasey, andAnne Meagher, (editorsatSpringerandHumana)andShanthyJaganathan(Integra-India). The followingpersonsprovidedusefuladviceandcommentsonselectionoftopics, referralto expertsineachtopic, andorchapterreviewsthatwetrulyappreciate: StephenLooney(a former editor of this book), Stan Young, Dmitri Zaykin, Douglas Hawkins, Wei Pan, Alexandre Almeida, John Ho, Rebecca Doerge, Paula Trushin, Kevin Morgan, Jason Osborne, PeterWestfall, JennyXiang, Ya-linChiu, YolandaBarron, HuiboShao, Alvin Mushlin, andRonaldFanta. Drs. Bang, Zhou, andMazumdarwerepartiallysupported byClinicalTranslationalScienceCenter(CTSC)grant(UL1-RR024996). HeejungBang vii Contents Preface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii Contributors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi PARTIBASICSTATISTICS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1. ExperimentalStatisticsforBiologicalSciences. . . . . . . . . . . . . . . . . . . 3 HeejungBangandMarieDavidian 2. NonparametricMethodsforMolecularBiology. . . . . . . . . . . . . . . . . . 105 KnutM. WittkowskiandTingtingSong 3. BasicsofBayesianMethods. . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 SujitK. Ghosh 4. TheBayesiant-TestandBeyond . . . . . . . . . . . . . . . . . . . . . . . . . 179 MithatGnen PARTII DESIGNSANDMETHODSFORMOLECULARBIOLOGY. . . . . . . . . . 201 5. SampleSizeandPowerCalculationforMolecularBiologyStudies. . . . . . . . 203 Sin-HoJung 6. DesignsforLinkageAnalysisandAssociationStudiesofComplexDiseases. . . . 219 YuehuaCui, GengxinLi, ShaoyuLi, andRonglingWu 7. IntroductiontoEpigenomicsandEpigenome-WideAnalysis This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Bookseller Inventory # 9781607615781

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Synopsis:

Thisbookisintendedformolecularbiologistswhoperformquantitativeanalysesondata emanatingfromtheir?eldandforthestatisticianswhoworkwithmolecularbiologists andotherbiomedicalresearchers. Therearemanyexcellenttextbooksthatprovidefun- mentalcomponentsforstatisticaltrainingcurricula. Therearealsomany?byexpertsfor experts?booksinstatisticsandmolecularbiologywhichrequirein-depthknowledgein bothsubjectstobetakenfulladvantageof. Sofar,nobookinstatisticshasbeenpublished thatprovidesthebasicprinciplesofproperstatisticalanalysesandprogressestoamore advancedstatisticsinresponsetorapidlydevelopingtechnologiesandmethodologiesin the?eldofmolecularbiology. Respondingtothissituation,ourbookaimsatbridgingthegapbetweenthesetwo extremes. Molecularbiologistswillbene?tfromtheprogressivestyleofthebookwhere basicstatisticalmethodsareintroducedandgraduallyelevatedtoanintermediatelevel. Similarly,statisticianswillbene?tfromlearningthevariousbiologicaldatageneratedfrom the?eldofmolecularbiology,thetypesofquestionsofinteresttomolecularbiologists, andthestatisticalapproachestoanalyzingthedata. Thestatisticalconceptsandmethods relevanttostudiesinmolecularbiologyarepresentedinasimpleandpracticalmanner. Speci?cally,thebookcoversbasicandintermediatestatisticsthatareusefulforclassical and molecular biology settings and advanced statistical techniques that can be used to helpsolveproblemscommonlyencounteredinmodernmolecularbiologystudies,such assupervisedandunsupervisedlearning,hiddenMarkovmodels,manipulationandan- ysisofdatafromhigh-throughputmicroarrayandproteomicplatform,andsynthesisof these evidences. A tutorial-type format is used to maximize learning in some chapters. Advicefromjournaleditorsonpeer-reviewedpublicationandsomeusefulinformationon softwareimplementationarealsoprovided. Thisbookisrecommendedforuseassupplementarymaterialbothinsideandoutside classroomsorasaself-learningguideforstudents,scientists,andresearcherswhodealwith numericdatainmolecularbiologyandrelated?elds. Thosewhostartasbeginners,but desiretobeatanintermediatelevel,will?ndthisbookespeciallyusefulintheirlearning pathway. WewanttothankJohnWalker(serieseditor),PatrickMarton,DavidCasey,andAnne Meagher,(editorsatSpringerandHumana)andShanthyJaganathan(Integra-India). The followingpersonsprovidedusefuladviceandcommentsonselectionoftopics,referralto expertsineachtopic,and/orchapterreviewsthatwetrulyappreciate:StephenLooney(a former editor of this book), Stan Young, Dmitri Zaykin, Douglas Hawkins, Wei Pan, Alexandre Almeida, John Ho, Rebecca Doerge, Paula Trushin, Kevin Morgan, Jason Osborne,PeterWestfall,JennyXiang,Ya-linChiu,YolandaBarron,HuiboShao,Alvin Mushlin,andRonaldFanta. Drs. Bang,Zhou,andMazumdarwerepartiallysupported byClinicalTranslationalScienceCenter(CTSC)grant(UL1-RR024996). HeejungBang vii Contents Preface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii Contributors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi PARTIBASICSTATISTICS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1. ExperimentalStatisticsforBiologicalSciences. . . . . . . . . . . . . . . . . . . 3 HeejungBangandMarieDavidian 2. NonparametricMethodsforMolecularBiology. . . . . . . . . . . . . . . . . . 105 KnutM. WittkowskiandTingtingSong 3. BasicsofBayesianMethods. . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 SujitK. Ghosh 4. TheBayesiant-TestandBeyond . . . . . . . . . . . . . . . . . . . . . . . . . 179 MithatGönen PARTII DESIGNSANDMETHODSFORMOLECULARBIOLOGY. . . . . . . . . . 201 5. SampleSizeandPowerCalculationforMolecularBiologyStudies. . . . . . . . 203 Sin-HoJung 6. DesignsforLinkageAnalysisandAssociationStudiesofComplexDiseases. . . . 219 YuehuaCui,GengxinLi,ShaoyuLi,andRonglingWu 7. IntroductiontoEpigenomicsandEpigenome-WideAnalysis. . . . . . . . . . . 243 MelissaJ. FazzariandJohnM. Greally 8. Exploration,Visualization,andPreprocessingofHigh?DimensionalData. . . . 267 ZhijinWuandZhiqiangWu PARTIII STATISTICALMETHODSFORMICROARRAYDATA . . . . . . . . . . . . 285 9. IntroductiontotheStatisticalAnalysisofTwo-ColorMicroarrayData. . . . . . 287 MartinaBremer,EdwardHimelblau,andAndreasMadlung 10. BuildingNetworkswithMicroarrayData. . . . . . . . . . . . . . . . . . . . . 315 BradleyM. Broom,WareeRinsurongkawong,LajosPusztai, andKim-AnhDo PARTIV ADVANCEDORSPECIALIZEDMETHODSFORMOLECULARBIOLOGY. . 345 11. SupportVectorMachinesforClassi?cation:AStatisticalPortrait. . . . . . . . . 347 YoonkyungLee 12. AnOverviewofClusteringAppliedtoMolecularBiology . . . . . . . . . . . . 369 RebeccaNugentandMarinaMeila ix xContents 13. HiddenMarkovModelandItsApplicationsinMotifFindings. . . . . . . . . . 405 JingWuandJunXie 14. DimensionReductionforHigh-DimensionalData. . . . . . . . . . . . . . . . 417 LexinLi 15. IntroductiontotheDevelopmentandValidationofPredictiveBiomarker ModelsfromHigh-ThroughputDataSets . . . . . . . . . . . . . . . . . . . . 435 XutaoDengandFabienCampagne 16. Multi-geneExpression-basedStatisticalApproachestoPredicting Patients?ClinicalOutcomesandResponses. . . . . . . . . . . . . . . . . . . . 471 FengCheng,Sang-HoonCho,andJaeK. Lee 17. Two-StageTestingStrategiesforGenome-WideAssociationStudies inFamily-BasedDesigns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 485 AmyMurphy,ScottT. Weiss,andChristophLange 18. StatisticalMethodsforProteomics . . . . . . . . . . . . . . . . . . . . . . . . 497 KlausJung PARTVMETA-ANALYSISFORHIGH-DIMENSIONALDATA . . . . . . . . . . . . 509 19. StatisticalMethodsforIntegratingMultipleTypesofHigh-ThroughputData. . 511 YangXieandChulAhn 20. ABayesianHierarchicalModelforHigh-DimensionalMeta-analysis. . . . . . . 531 FeiLiu 21. MethodsforCombiningMultipleGenome-WideLinkageStudies. . . . . . . . 541 TreciaA. KippolaandStephanieA. Santorico PARTVI OTHERPRACTICALINFORMATION . . . . . . . . . . . . . . . . . . . . 561 22. ImprovedReportingofStatisticalDesignandAnalysis:Guidelines, Education,andEditorialPolicies. . . . . . . . . . . . . . . . . . . . . . . . . 563 MadhuMazumdar,SampritBanerjee,andHeatherL. VanEpps 23. StataCompanion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 599 JenniferSousaBrennan SubjectIndex. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 627 Contributors CHULAHN? Division of Biostatistics, Department of Clinical Sciences, The Harold C.

Product Description:

While there is a wide selection of 'by experts, for experts? books in statistics and molecular biology, there is a distinct need for a book that presents the basic principles of proper statistical analyses and progresses to more advanced statistical methods in response to rapidly developing technologies and methodologies in the field of molecular biology. Statistical Methods in Molecular Biology strives to fill that gap by covering basic and intermediate statistics that are useful for classical molecular biology settings and advanced statistical techniques that can be used to help solve problems commonly encountered in modern molecular biology studies, such as supervised and unsupervised learning, hidden Markov models, methods for manipulation and analysis of high-throughput microarray and proteomic data, and methods for the synthesis of the available evidences. This detailed volume offers molecular biologists a book in a progressive style where basic statistical methods are introduced and gradually elevated to an intermediate level, while providing statisticians knowledge of various biological data generated from the field of molecular biology, the types of questions of interest to molecular biologists, and the state-of-the-art statistical approaches to analyzing the data. As a volume in the highly successful Methods in Molecular Biology? series, this work provides the kind of meticulous descriptions and implementation advice for diverse topics that are crucial for getting optimal results.

Comprehensive but convenient, Statistical Methods in Molecular Biology will aid students, scientists, and researchers along the pathway from beginning strategies to a deeper understanding of these vital systems of data analysis and interpretation within one concise volume.

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Bibliographic Details

Title: Statistical Methods in Molecular Biology

Publisher: Humana Press

Binding: Hardcover

Book Condition: New

Book Type: Hardcover

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