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Microarray Gene Expression Data Integration andCancer Signatures: A Novel Statistical Method and its Applications toCancer Research - Softcover
Synopsis
Over the past decade, microarray gene expression datahas been widely used to identify cancer genesignatures that could complement conventionalhistopathologic evaluation to increase the accuracyof cancer diagnosis and prognosis. However, due tothe limited sample size of individual studies, thereis often only a small overlap between signatures forspecific cancers obtained in different studies. Withthe rapid accumulation of microarray data, it is ofgreat interest to understand how to combinemicroarray data across studies of similar cancers inorder to increase sample size, which could lead tothe identification of more reliable gene signaturesof specific cancers. This book provides a novelstatistical method, based on the top-scoring pairsclassifier family, for inter-study microarray dataintegration. By incorporating this new method intodifferent statistical models, we can identify robustgene signatures for cancer diagnosis and prognosisfrom integrated microarray data. This book isprimarily aimed at cancer researchers, especially inthe emerging field of cancer bioinformatics, butshould also be valuable to statisticians and medicalresearchers entering the field.
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About the Author
PhD in Electrical Engineering with concentration onBioinformatics at Johns Hopkins University. Statistician inbiotechnology and pharmaceutical industry.
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Microarray Gene Expression Data Integration andCancer Signatures: A Novel Statistical Method and its Applications toCancer Research
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Microarray Gene Expression Data Integration andCancer Signatures: A Novel Statistical Method and its Applications toCancer Research
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Microarray Gene Expression Data Integration and Cancer Signatures
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VDM Verlag Dr. Mueller e.K. 2008-09-25, 2008
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ISBN 13: 9783639085532
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Microarray Gene Expression Data Integration andCancer Signatures : A Novel Statistical Method and its Applications toCancer Research
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Taschenbuch. Condition: Neu. Neuware - Over the past decade, microarray gene expression datahas been widely used to identify cancer genesignatures that could complement conventionalhistopathologic evaluation to increase the accuracyof cancer diagnosis and prognosis. However, due tothe limited sample size of individual studies, thereis often only a small overlap between signatures forspecific cancers obtained in different studies. Withthe rapid accumulation of microarray data, it is ofgreat interest to understand how to combinemicroarray data across studies of similar cancers inorder to increase sample size, which could lead tothe identification of more reliable gene signaturesof specific cancers. This book provides a novelstatistical method, based on the top-scoring pairsclassifier family, for inter-study microarray dataintegration. By incorporating this new method intodifferent statistical models, we can identify robustgene signatures for cancer diagnosis and prognosisfrom integrated microarray data. This book isprimarily aimed at cancer researchers, especially inthe emerging field of cancer bioinformatics, butshould also be valuable to statisticians and medicalresearchers entering the field. Seller Inventory # 9783639085532
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Microarray Gene Expression Data Integration andCancer Signatures
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Kartoniert / Broschiert. Condition: New. Over the past decade, microarray gene expression datahas been widely used to identify cancer genesignatures that could complement conventionalhistopathologic evaluation to increase the accuracyof cancer diagnosis and prognosis. However, due tothe limited sa. Seller Inventory # 4956057
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