Bayesian Inference For Gene Expression And Proteomics
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Bayesian Inference For Gene Expression And Proteomics
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Author : Kim-Anh Do
language : en
Publisher: Cambridge University Press
Release Date : 2006-07-24
Bayesian Inference For Gene Expression And Proteomics written by Kim-Anh Do and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-07-24 with Mathematics categories.
Expert overviews of Bayesian methodology, tools and software for multi-platform high-throughput experimentation.
Bayesian Analysis Of Gene Expression Data
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Author : Bani K. Mallick
language : en
Publisher: John Wiley & Sons
Release Date : 2009-07-20
Bayesian Analysis Of Gene Expression Data written by Bani K. Mallick and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-07-20 with Mathematics categories.
The field of high-throughput genetic experimentation is evolving rapidly, with the advent of new technologies and new venues for data mining. Bayesian methods play a role central to the future of data and knowledge integration in the field of Bioinformatics. This book is devoted exclusively to Bayesian methods of analysis for applications to high-throughput gene expression data, exploring the relevant methods that are changing Bioinformatics. Case studies, illustrating Bayesian analyses of public gene expression data, provide the backdrop for students to develop analytical skills, while the more experienced readers will find the review of advanced methods challenging and attainable. This book: Introduces the fundamentals in Bayesian methods of analysis for applications to high-throughput gene expression data. Provides an extensive review of Bayesian analysis and advanced topics for Bioinformatics, including examples that extensively detail the necessary applications. Accompanied by website featuring datasets, exercises and solutions. Bayesian Analysis of Gene Expression Data offers a unique introduction to both Bayesian analysis and gene expression, aimed at graduate students in Statistics, Biomedical Engineers, Computer Scientists, Biostatisticians, Statistical Geneticists, Computational Biologists, applied Mathematicians and Medical consultants working in genomics. Bioinformatics researchers from many fields will find much value in this book.
Bayesian Inference For Differential Gene Expression Data
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Author : Dabao Zhang
language : en
Publisher:
Release Date : 2003
Bayesian Inference For Differential Gene Expression Data written by Dabao Zhang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with categories.
Bayesian Modeling In Bioinformatics
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Author : Dipak K. Dey
language : en
Publisher: CRC Press
Release Date : 2010-09-03
Bayesian Modeling In Bioinformatics written by Dipak K. Dey and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-03 with Mathematics categories.
Bayesian Modeling in Bioinformatics discusses the development and application of Bayesian statistical methods for the analysis of high-throughput bioinformatics data arising from problems in molecular and structural biology and disease-related medical research, such as cancer. It presents a broad overview of statistical inference, clustering, and c
Bayesian Inference On Complicated Data
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Author : Niansheng Tang
language : en
Publisher: BoD – Books on Demand
Release Date : 2020-07-15
Bayesian Inference On Complicated Data written by Niansheng Tang and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-15 with Mathematics categories.
Due to great applications in various fields, such as social science, biomedicine, genomics, and signal processing, and the improvement of computing ability, Bayesian inference has made substantial developments for analyzing complicated data. This book introduces key ideas of Bayesian sampling methods, Bayesian estimation, and selection of the prior. It is structured around topics on the impact of the choice of the prior on Bayesian statistics, some advances on Bayesian sampling methods, and Bayesian inference for complicated data including breast cancer data, cloud-based healthcare data, gene network data, and longitudinal data. This volume is designed for statisticians, engineers, doctors, and machine learning researchers.
Bioinformatics
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Author : Yu Liu
language : en
Publisher: CRC Press
Release Date : 2014-02-24
Bioinformatics written by Yu Liu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-02-24 with Mathematics categories.
The book introduces bioinformatic and statistical methodology and shows approaches to bias correction and error estimation. It also presents quantitative methods for genome and proteome analysis.
Introduction To Computational Proteomics
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Author : Golan Yona
language : en
Publisher: CRC Press
Release Date : 2010-12-09
Introduction To Computational Proteomics written by Golan Yona and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-12-09 with Mathematics categories.
Introduction to Computational Proteomics introduces the field of computational biology through a focused approach that tackles the different steps and problems involved with protein analysis, classification, and meta-organization. The book starts with the analysis of individual entities and works its way through the analysis of more complex entitie
Data Analysis And Visualization In Genomics And Proteomics
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Author : Francisco Azuaje
language : en
Publisher: John Wiley & Sons
Release Date : 2005-06-24
Data Analysis And Visualization In Genomics And Proteomics written by Francisco Azuaje and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-06-24 with Science categories.
Data Analysis and Visualization in Genomics and Proteomics is the first book addressing integrative data analysis and visualization in this field. It addresses important techniques for the interpretation of data originating from multiple sources, encoded in different formats or protocols, and processed by multiple systems. One of the first systematic overviews of the problem of biological data integration using computational approaches This book provides scientists and students with the basis for the development and application of integrative computational methods to analyse biological data on a systemic scale Places emphasis on the processing of multiple data and knowledge resources, and the combination of different models and systems
Genomics Data Analysis
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Author : David R. Bickel
language : en
Publisher: CRC Press
Release Date : 2019-09-24
Genomics Data Analysis written by David R. Bickel and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-24 with Mathematics categories.
Statisticians have met the need to test hundreds or thousands of genomics hypotheses simultaneously with novel empirical Bayes methods that combine advantages of traditional Bayesian and frequentist statistics. Techniques for estimating the local false discovery rate assign probabilities of differential gene expression, genetic association, etc. without requiring subjective prior distributions. This book brings these methods to scientists while keeping the mathematics at an elementary level. Readers will learn the fundamental concepts behind local false discovery rates, preparing them to analyze their own genomics data and to critically evaluate published genomics research. Key Features: * dice games and exercises, including one using interactive software, for teaching the concepts in the classroom * examples focusing on gene expression and on genetic association data and briefly covering metabolomics data and proteomics data * gradual introduction to the mathematical equations needed * how to choose between different methods of multiple hypothesis testing * how to convert the output of genomics hypothesis testing software to estimates of local false discovery rates * guidance through the minefield of current criticisms of p values * material on non-Bayesian prior p values and posterior p values not previously published
Handbook Of Statistical Genomics
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Author : David J. Balding
language : en
Publisher: John Wiley & Sons
Release Date : 2019-07-09
Handbook Of Statistical Genomics written by David J. Balding and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-09 with Science categories.
A timely update of a highly popular handbook on statistical genomics This new, two-volume edition of a classic text provides a thorough introduction to statistical genomics, a vital resource for advanced graduate students, early-career researchers and new entrants to the field. It introduces new and updated information on developments that have occurred since the 3rd edition. Widely regarded as the reference work in the field, it features new chapters focusing on statistical aspects of data generated by new sequencing technologies, including sequence-based functional assays. It expands on previous coverage of the many processes between genotype and phenotype, including gene expression and epigenetics, as well as metabolomics. It also examines population genetics and evolutionary models and inference, with new chapters on the multi-species coalescent, admixture and ancient DNA, as well as genetic association studies including causal analyses and variant interpretation. The Handbook of Statistical Genomics focuses on explaining the main ideas, analysis methods and algorithms, citing key recent and historic literature for further details and references. It also includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between chapters, tying the different areas together. With heavy use of up-to-date examples and references to web-based resources, this continues to be a must-have reference in a vital area of research. Provides much-needed, timely coverage of new developments in this expanding area of study Numerous, brand new chapters, for example covering bacterial genomics, microbiome and metagenomics Detailed coverage of application areas, with chapters on plant breeding, conservation and forensic genetics Extensive coverage of human genetic epidemiology, including ethical aspects Edited by one of the leading experts in the field along with rising stars as his co-editors Chapter authors are world-renowned experts in the field, and newly emerging leaders. The Handbook of Statistical Genomics is an excellent introductory text for advanced graduate students and early-career researchers involved in statistical genetics.