Bayesian Analysis Of Gene Expression Data

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Bayesian Analysis of Gene Expression Data

Author : Bani K. Mallick
Publisher : John Wiley & Sons
ISBN 13 : 9780470742815
Total Pages : 252 pages
Book Rating : 4.7/5 (428 download)

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Book Synopsis Bayesian Analysis of Gene Expression Data by : Bani K. Mallick

Download or read book Bayesian Analysis of Gene Expression Data written by Bani K. Mallick and published by John Wiley & Sons. This book was released on 2009-07-20 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Gene Expression and Proteomics

Author : Kim-Anh Do
Publisher : Cambridge University Press
ISBN 13 : 052186092X
Total Pages : 437 pages
Book Rating : 4.5/5 (218 download)

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Book Synopsis Bayesian Inference for Gene Expression and Proteomics by : Kim-Anh Do

Download or read book Bayesian Inference for Gene Expression and Proteomics written by Kim-Anh Do and published by Cambridge University Press. This book was released on 2006-07-24 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: Expert overviews of Bayesian methodology, tools and software for multi-platform high-throughput experimentation.

Bayesian Inference for Differential Gene Expression Data

Author : Dabao Zhang
Publisher :
ISBN 13 :
Total Pages : 194 pages
Book Rating : 4.E/5 ( download)

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Book Synopsis Bayesian Inference for Differential Gene Expression Data by : Dabao Zhang

Download or read book Bayesian Inference for Differential Gene Expression Data written by Dabao Zhang and published by . This book was released on 2003 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Handbook of Statistical Genomics

Author : David J. Balding
Publisher : John Wiley & Sons
ISBN 13 : 1119429250
Total Pages : 1828 pages
Book Rating : 4.1/5 (194 download)

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Book Synopsis Handbook of Statistical Genomics by : David J. Balding

Download or read book Handbook of Statistical Genomics written by David J. Balding and published by John Wiley & Sons. This book was released on 2019-07-09 with total page 1828 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Statistical Analysis of Gene Expression Microarray Data

Author : Terry Speed
Publisher : CRC Press
ISBN 13 : 0203011236
Total Pages : 237 pages
Book Rating : 4.2/5 (3 download)

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Book Synopsis Statistical Analysis of Gene Expression Microarray Data by : Terry Speed

Download or read book Statistical Analysis of Gene Expression Microarray Data written by Terry Speed and published by CRC Press. This book was released on 2003-03-26 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Bayesian Modeling in Bioinformatics

Author : Dipak K. Dey
Publisher : CRC Press
ISBN 13 : 1420070185
Total Pages : 466 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Bayesian Modeling in Bioinformatics by : Dipak K. Dey

Download or read book Bayesian Modeling in Bioinformatics written by Dipak K. Dey and published by CRC Press. This book was released on 2010-09-03 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Data Analysis, Third Edition

Author : Andrew Gelman
Publisher : CRC Press
ISBN 13 : 1439840954
Total Pages : 677 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Bayesian Data Analysis, Third Edition by : Andrew Gelman

Download or read book Bayesian Data Analysis, Third Edition written by Andrew Gelman and published by CRC Press. This book was released on 2013-11-01 with total page 677 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

The Analysis of Gene Expression Data

Author : Giovanni Parmigiani
Publisher : Springer Science & Business Media
ISBN 13 : 0387216790
Total Pages : 456 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis The Analysis of Gene Expression Data by : Giovanni Parmigiani

Download or read book The Analysis of Gene Expression Data written by Giovanni Parmigiani and published by Springer Science & Business Media. This book was released on 2006-04-11 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

New Insights into Bayesian Inference

Author : Mohammad Saber Fallah Nezhad
Publisher : BoD – Books on Demand
ISBN 13 : 1789230926
Total Pages : 142 pages
Book Rating : 4.7/5 (892 download)

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Book Synopsis New Insights into Bayesian Inference by : Mohammad Saber Fallah Nezhad

Download or read book New Insights into Bayesian Inference written by Mohammad Saber Fallah Nezhad and published by BoD – Books on Demand. This book was released on 2018-05-02 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Analyzing Microarray Gene Expression Data

Author : Geoffrey J. McLachlan
Publisher : John Wiley & Sons
ISBN 13 : 0471726125
Total Pages : 366 pages
Book Rating : 4.4/5 (717 download)

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Book Synopsis Analyzing Microarray Gene Expression Data by : Geoffrey J. McLachlan

Download or read book Analyzing Microarray Gene Expression Data written by Geoffrey J. McLachlan and published by John Wiley & Sons. This book was released on 2005-02-18 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

On Bayesian Modeling and Design for Microarray Gene Expression Data

Author : Yuan Ji
Publisher :
ISBN 13 :
Total Pages : 134 pages
Book Rating : 4.:/5 (89 download)

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Book Synopsis On Bayesian Modeling and Design for Microarray Gene Expression Data by : Yuan Ji

Download or read book On Bayesian Modeling and Design for Microarray Gene Expression Data written by Yuan Ji and published by . This book was released on 2003 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Bayesian Inference on Complicated Data

Author : Niansheng Tang
Publisher : BoD – Books on Demand
ISBN 13 : 1838803858
Total Pages : 120 pages
Book Rating : 4.8/5 (388 download)

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Book Synopsis Bayesian Inference on Complicated Data by : Niansheng Tang

Download or read book Bayesian Inference on Complicated Data written by Niansheng Tang and published by BoD – Books on Demand. This book was released on 2020-07-15 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Genomics Data Analysis

Author : David R. Bickel
Publisher : CRC Press
ISBN 13 : 1000706915
Total Pages : 141 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Genomics Data Analysis by : David R. Bickel

Download or read book Genomics Data Analysis written by David R. Bickel and published by CRC Press. This book was released on 2019-09-24 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Methods of Microarray Data Analysis

Author : Simon M. Lin
Publisher : Springer Science & Business Media
ISBN 13 : 1461508738
Total Pages : 192 pages
Book Rating : 4.4/5 (615 download)

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Book Synopsis Methods of Microarray Data Analysis by : Simon M. Lin

Download or read book Methods of Microarray Data Analysis written by Simon M. Lin and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Analysis of Microarray Gene Expression Data

Author : Mei-Ling Ting Lee
Publisher : Springer Science & Business Media
ISBN 13 : 0792370872
Total Pages : 378 pages
Book Rating : 4.7/5 (923 download)

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Book Synopsis Analysis of Microarray Gene Expression Data by : Mei-Ling Ting Lee

Download or read book Analysis of Microarray Gene Expression Data written by Mei-Ling Ting Lee and published by Springer Science & Business Media. This book was released on 2004-04-30 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

A Practical Approach to Microarray Data Analysis

Author : Daniel P. Berrar
Publisher : Springer Science & Business Media
ISBN 13 : 0306478153
Total Pages : 382 pages
Book Rating : 4.3/5 (64 download)

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Book Synopsis A Practical Approach to Microarray Data Analysis by : Daniel P. Berrar

Download or read book A Practical Approach to Microarray Data Analysis written by Daniel P. Berrar and published by Springer Science & Business Media. This book was released on 2007-05-08 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past several years, DNA microarray technology has attracted tremendous interest in both the scientific community and in industry. With its ability to simultaneously measure the activity and interactions of thousands of genes, this modern technology promises unprecedented new insights into mechanisms of living systems. Currently, the primary applications of microarrays include gene discovery, disease diagnosis and prognosis, drug discovery (pharmacogenomics), and toxicological research (toxicogenomics). Typical scientific tasks addressed by microarray experiments include the identification of coexpressed genes, discovery of sample or gene groups with similar expression patterns, identification of genes whose expression patterns are highly differentiating with respect to a set of discerned biological entities (e.g., tumor types), and the study of gene activity patterns under various stress conditions (e.g., chemical treatment). More recently, the discovery, modeling, and simulation of regulatory gene networks, and the mapping of expression data to metabolic pathways and chromosome locations have been added to the list of scientific tasks that are being tackled by microarray technology. Each scientific task corresponds to one or more so-called data analysis tasks. Different types of scientific questions require different sets of data analytical techniques. Broadly speaking, there are two classes of elementary data analysis tasks, predictive modeling and pattern-detection. Predictive modeling tasks are concerned with learning a classification or estimation function, whereas pattern-detection methods screen the available data for interesting, previously unknown regularities or relationships.

Optimal Bayesian Classification

Author : Lori A. Dalton
Publisher :
ISBN 13 : 9781510630697
Total Pages : pages
Book Rating : 4.6/5 (36 download)

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Book Synopsis Optimal Bayesian Classification by : Lori A. Dalton

Download or read book Optimal Bayesian Classification written by Lori A. Dalton and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "The most basic problem of engineering is the design of optimal operators. Design takes different forms depending on the random process constituting the scientific model and the operator class of interest. This book treats classification, where the underlying random process is a feature-label distribution, and an optimal operator is a Bayes classifier, which is a classifier minimizing the classification error. With sufficient knowledge we can construct the feature-label distribution and thereby find a Bayes classifier. Rarely, do we possess such knowledge. On the other hand, if we had unlimited data, we could accurately estimate the feature-label distribution and obtain a Bayes classifier. Rarely do we possess sufficient data. The aim of this book is to best use whatever knowledge and data are available to design a classifier. The book takes a Bayesian approach to modeling the feature-label distribution and designs an optimal classifier relative to a posterior distribution governing an uncertainty class of feature-label distributions. In this way it takes full advantage of knowledge regarding the underlying system and the available data. Its origins lie in the need to estimate classifier error when there is insufficient data to hold out test data, in which case an optimal error estimate can be obtained relative to the uncertainty class. A natural next step is to forgo classical ad hoc classifier design and simply find an optimal classifier relative to the posterior distribution over the uncertainty class-this being an optimal Bayesian classifier"--