Bayesian Analysis Of Gene Expression Data

Author : Bani K. Mallick,David Gold,Veera Baladandayuthapani
Publisher : John Wiley & Sons
Page : 252 pages
File Size : 51,8 Mb
Release : 2009-07-20
Category : Mathematics
ISBN : 047074281X

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Bayesian Analysis of Gene Expression Data by Bani K. Mallick,David Gold,Veera Baladandayuthapani Pdf

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.

Author : Dabao Zhang
Publisher : Unknown
Page : 194 pages
File Size : 53,8 Mb
Release : 2003
Category : Electronic
ISBN : CORNELL:31924090240775

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Bayesian Inference for Differential Gene Expression Data by Dabao Zhang Pdf

Author : Kim-Anh Do,Peter Müller,Marina Vannucci
Publisher : Cambridge University Press
Page : 437 pages
File Size : 52,8 Mb
Release : 2006-07-24
Category : Mathematics
ISBN : 9780521860925

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Bayesian Inference for Gene Expression and Proteomics by Kim-Anh Do,Peter Müller,Marina Vannucci Pdf

Expert overviews of Bayesian methodology, tools and software for multi-platform high-throughput experimentation.

Author : David J. Balding,Ida Moltke,John Marioni
Publisher : John Wiley & Sons
Page : 1828 pages
File Size : 55,7 Mb
Release : 2019-07-09
Category : Science
ISBN : 9781119429258

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Handbook of Statistical Genomics by David J. Balding,Ida Moltke,John Marioni Pdf

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.

Author : Dipak K. Dey,Samiran Ghosh,Bani K. Mallick
Publisher : CRC Press
Page : 466 pages
File Size : 42,8 Mb
Release : 2010-09-03
Category : Mathematics
ISBN : 9781420070187

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Bayesian Modeling in Bioinformatics by Dipak K. Dey,Samiran Ghosh,Bani K. Mallick Pdf

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

Author : Giovanni Parmigiani,Elizabeth S. Garett,Rafael A. Irizarry,Scott L. Zeger
Publisher : Springer Science & Business Media
Page : 456 pages
File Size : 45,6 Mb
Release : 2006-04-11
Category : Medical
ISBN : 9780387216799

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The Analysis of Gene Expression Data by Giovanni Parmigiani,Elizabeth S. Garett,Rafael A. Irizarry,Scott L. Zeger Pdf

This book presents practical approaches for the analysis of data from gene expression micro-arrays. It describes the conceptual and methodological underpinning for a statistical tool and its implementation in software. The book includes coverage of various packages that are part of the Bioconductor project and several related R tools. The materials presented cover a range of software tools designed for varied audiences.

Author : Andrew Gelman,John B. Carlin,Hal S. Stern,David B. Dunson,Aki Vehtari,Donald B. Rubin
Publisher : CRC Press
Page : 677 pages
File Size : 49,8 Mb
Release : 2013-11-01
Category : Mathematics
ISBN : 9781439840955

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Bayesian Data Analysis, Third Edition by Andrew Gelman,John B. Carlin,Hal S. Stern,David B. Dunson,Aki Vehtari,Donald B. Rubin Pdf

Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.

Author : Niansheng Tang
Publisher : BoD – Books on Demand
Page : 120 pages
File Size : 48,7 Mb
Release : 2020-07-15
Category : Mathematics
ISBN : 9781838803858

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Bayesian Inference on Complicated Data by Niansheng Tang Pdf

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.

Author : Terry Speed
Publisher : CRC Press
Page : 237 pages
File Size : 49,6 Mb
Release : 2003-03-26
Category : Mathematics
ISBN : 9780203011232

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Statistical Analysis of Gene Expression Microarray Data by Terry Speed Pdf

Although less than a decade old, the field of microarray data analysis is now thriving and growing at a remarkable pace. Biologists, geneticists, and computer scientists as well as statisticians all need an accessible, systematic treatment of the techniques used for analyzing the vast amounts of data generated by large-scale gene expression studies

Author : Mohammad Saber Fallah Nezhad
Publisher : BoD – Books on Demand
Page : 142 pages
File Size : 49,8 Mb
Release : 2018-05-02
Category : Mathematics
ISBN : 9781789230925

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New Insights into Bayesian Inference by Mohammad Saber Fallah Nezhad Pdf

This book is an introduction to the mathematical analysis of Bayesian decision-making when the state of the problem is unknown but further data about it can be obtained. The objective of such analysis is to determine the optimal decision or solution that is logically consistent with the preferences of the decision-maker, that can be analyzed using numerical utilities or criteria with the probabilities assigned to the possible state of the problem, such that these probabilities are updated by gathering new information.

Author : Yuan Ji
Publisher : Unknown
Page : 134 pages
File Size : 52,7 Mb
Release : 2003
Category : Electronic
ISBN : WISC:89083395467

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On Bayesian Modeling and Design for Microarray Gene Expression Data by Yuan Ji Pdf

Author : David R. Bickel
Publisher : CRC Press
Page : 141 pages
File Size : 45,6 Mb
Release : 2019-09-24
Category : Mathematics
ISBN : 9781000706918

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Genomics Data Analysis by David R. Bickel Pdf

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

Author : Mei-Ling Ting Lee
Publisher : Springer Science & Business Media
Page : 377 pages
File Size : 46,7 Mb
Release : 2007-05-08
Category : Science
ISBN : 9781402077883

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Analysis of Microarray Gene Expression Data by Mei-Ling Ting Lee Pdf

After genomic sequencing, microarray technology has emerged as a widely used platform for genomic studies in the life sciences. Microarray technology provides a systematic way to survey DNA and RNA variation. With the abundance of data produced from microarray studies, however, the ultimate impact of the studies on biology will depend heavily on data mining and statistical analysis. The contribution of this book is to provide readers with an integrated presentation of various topics on analyzing microarray data.

Author : Geoffrey J. McLachlan,Kim-Anh Do,Christophe Ambroise
Publisher : John Wiley & Sons
Page : 366 pages
File Size : 48,9 Mb
Release : 2005-02-18
Category : Mathematics
ISBN : 9780471726128

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Analyzing Microarray Gene Expression Data by Geoffrey J. McLachlan,Kim-Anh Do,Christophe Ambroise Pdf

A multi-discipline, hands-on guide to microarray analysis of biological processes Analyzing Microarray Gene Expression Data provides a comprehensive review of available methodologies for the analysis of data derived from the latest DNA microarray technologies. Designed for biostatisticians entering the field of microarray analysis as well as biologists seeking to more effectively analyze their own experimental data, the text features a unique interdisciplinary approach and a combined academic and practical perspective that offers readers the most complete and applied coverage of the subject matter to date. Following a basic overview of the biological and technical principles behind microarray experimentation, the text provides a look at some of the most effective tools and procedures for achieving optimum reliability and reproducibility of research results, including: An in-depth account of the detection of genes that are differentially expressed across a number of classes of tissues Extensive coverage of both cluster analysis and discriminant analysis of microarray data and the growing applications of both methodologies A model-based approach to cluster analysis, with emphasis on the use of the EMMIX-GENE procedure for the clustering of tissue samples The latest data cleaning and normalization procedures The uses of microarray expression data for providing important prognostic information on the outcome of disease

Author : Simon M. Lin,Kimberly F. Johnson
Publisher : Springer Science & Business Media
Page : 192 pages
File Size : 40,9 Mb
Release : 2012-12-06
Category : Science
ISBN : 9781461508731

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Methods of Microarray Data Analysis by Simon M. Lin,Kimberly F. Johnson Pdf

Microarray technology is a major experimental tool for functional genomic explorations, and will continue to be a major tool throughout this decade and beyond. The recent explosion of this technology threatens to overwhelm the scientific community with massive quantities of data. Because microarray data analysis is an emerging field, very few analytical models currently exist. Methods of Microarray Data Analysis is one of the first books dedicated to this exciting new field. In a single reference, readers can learn about the most up-to-date methods ranging from data normalization, feature selection and discriminative analysis to machine learning techniques. Currently, there are no standard procedures for the design and analysis of microarray experiments. Methods of Microarray Data Analysis focuses on two well-known data sets, using a different method of analysis in each chapter. Real examples expose the strengths and weaknesses of each method for a given situation, aimed at helping readers choose appropriate protocols and utilize them for their own data set. In addition, web links are provided to the programs and tools discussed in several chapters. This book is an excellent reference not only for academic and industrial researchers, but also for core bioinformatics/genomics courses in undergraduate and graduate programs.