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Author : Raphael Gottardo
Publisher :
ISBN 13 :
Total Pages : 135 pages
Book Rating : 4.:/5 (623 download)
Download or read book Robust Bayesian Analysis of Gene Expression Microarray Data written by Raphael Gottardo and published by . This book was released on 2005 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :
Publisher :
ISBN 13 :
Total Pages : 26 pages
Book Rating : 4.:/5 (318 download)
Download or read book Bayesian Robust Inference for Differential Gene Expression in CDNA Microarrays with Multiple Samples written by and published by . This book was released on 2004 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider the problem of identifying differentially expressed genes under different conditions using cDNA microarrays. Standard statistical methods cannot be used because typically there are thousands of genes and few replicates. Because of the many steps involved in the experimental process, from hybridization to image analysis, cDNA microarray data often contain outliers. For example, an outlying data value could occur because of scratches or dust on the surface, imperfections in the glass, or imperfections in the array production. We develop a robust Bayesian hierarchical model for testing for differential expression. Outliers are modeled explicitly using a t-distribution. The model includes an exchangeable prior for the variances which allow different variances for the genes but still shrink extreme empirical variances. Our model can be used for testing for differentially expressed genes among multiple samples, and can distinguish between the different possible patterns of differential expression when there are three or more samples. Parameter estimation is carried out using a novel version of Markov Chain Monte Carlo that is appropriate when the model puts mass on subspaces of the full parameter space. The method is illustrated using two publicly available gene expression data sets. We compare our method to five other commonly used techniques, namely the one-sample t-test, the Bonferroni-adjusted t-test, Significance Analysis of Microarrays (SAM), and EBarrays in both its Lognormal-Normal and Gamma-Gamma forms. In an experiment with HIV data, our method performed better than these alternatives, on the basis of between-replicate agreement and disagreement.
Author : Bani K. Mallick
Publisher : John Wiley & Sons
ISBN 13 : 9780470742815
Total Pages : 252 pages
Book Rating : 4.7/5 (428 download)
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.
Author : Jennifer S. Shoemaker
Publisher : Springer Science & Business Media
ISBN 13 : 9780387230740
Total Pages : 276 pages
Book Rating : 4.2/5 (37 download)
Download or read book Methods of Microarray Data Analysis IV written by Jennifer S. Shoemaker and published by Springer Science & Business Media. This book was released on 2004-10-29 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: As studies using microarray technology have evolved, so have the data analysis methods used to analyze these experiments. The CAMDA conference plays a role in this evolving field by providing a forum in which investors can analyze the same data sets using different methods. Methods of Microarray Data Analysis IV is the fourth book in this series, and focuses on the important issue of associating array data with a survival endpoint. Previous books in this series focused on classification (Volume I), pattern recognition (Volume II), and quality control issues (Volume III). In this volume, four lung cancer data sets are the focus of analysis. We highlight three tutorial papers, including one to assist with a basic understanding of lung cancer, a review of survival analysis in the gene expression literature, and a paper on replication. In addition, 14 papers presented at the conference are included. This book is an excellent reference for academic and industrial researchers who want to keep abreast of the state of the art of microarray data analysis. Jennifer Shoemaker is a faculty member in the Department of Biostatistics and Bioinformatics and the Director of the Bioinformatics Unit for the Cancer and Leukemia Group B Statistical Center, Duke University Medical Center. Simon Lin is a faculty member in the Department of Biostatistics and Bioinformatics and the Manager of the Duke Bioinformatics Shared Resource, Duke University Medical Center.
Author : Kim-Anh Do
Publisher : Cambridge University Press
ISBN 13 : 052186092X
Total Pages : 437 pages
Book Rating : 4.5/5 (218 download)
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.
Author : Omer Berkman
Publisher :
ISBN 13 :
Total Pages : 170 pages
Book Rating : 4.:/5 (495 download)
Download or read book Robust Inference in Bayesian Networks with Application to Gene Expression Time-series Data written by Omer Berkman and published by . This book was released on 2008 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Giovanni Parmigiani
Publisher : Springer Science & Business Media
ISBN 13 : 0387216790
Total Pages : 511 pages
Book Rating : 4.3/5 (872 download)
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 511 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.
Author : Terry Speed
Publisher : CRC Press
ISBN 13 : 0203011236
Total Pages : 237 pages
Book Rating : 4.2/5 (3 download)
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
Author : Mei-Ling Ting Lee
Publisher : Springer Science & Business Media
ISBN 13 : 1402077882
Total Pages : 378 pages
Book Rating : 4.4/5 (2 download)
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 2007-05-08 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.
Author : Dhammika Amaratunga
Publisher : John Wiley & Sons
ISBN 13 : 0470317965
Total Pages : 270 pages
Book Rating : 4.4/5 (73 download)
Download or read book Exploration and Analysis of DNA Microarray and Protein Array Data written by Dhammika Amaratunga and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: A cutting-edge guide to the analysis of DNA microarray data Genomics is one of the major scientific revolutions of this century, and the use of microarrays to rapidly analyze numerous DNA samples has enabled scientists to make sense of mountains of genomic data through statistical analysis. Today, microarrays are being used in biomedical research to study such vital areas as a drug’s therapeutic value–or toxicity–and cancer-spreading patterns of gene activity. Exploration and Analysis of DNA Microarray and Protein Array Data answers the need for a comprehensive, cutting-edge overview of this important and emerging field. The authors, seasoned researchers with extensive experience in both industry and academia, effectively outline all phases of this revolutionary analytical technique, from the preprocessing to the analysis stage. Highlights of the text include: A review of basic molecular biology, followed by an introduction to microarrays and their preparation Chapters on processing scanned images and preprocessing microarray data Methods for identifying differentially expressed genes in comparative microarray experiments Discussions of gene and sample clustering and class prediction Extension of analysis methods to protein array data Numerous exercises for self-study as well as data sets and a useful collection of computational tools on the authors’ Web site make this important text a valuable resource for both students and professionals in the field.
Author : Geoffrey J. McLachlan
Publisher : John Wiley & Sons
ISBN 13 : 0471726125
Total Pages : 366 pages
Book Rating : 4.4/5 (717 download)
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
Author : Dabao Zhang
Publisher :
ISBN 13 :
Total Pages : 194 pages
Book Rating : 4.E/5 ( download)
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:
Author : Ning Tang
Publisher :
ISBN 13 :
Total Pages : 113 pages
Book Rating : 4.:/5 (889 download)
Download or read book Robust Gene Set Analysis and Robust Gene Expression written by Ning Tang and published by . This book was released on 2014 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Matthias Dehmer
Publisher : John Wiley & Sons
ISBN 13 : 3527622829
Total Pages : 438 pages
Book Rating : 4.5/5 (276 download)
Download or read book Analysis of Microarray Data written by Matthias Dehmer and published by John Wiley & Sons. This book was released on 2008-09-08 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first to focus on the application of mathematical networks for analyzing microarray data. This method goes well beyond the standard clustering methods traditionally used. From the contents: * Understanding and Preprocessing Microarray Data * Clustering of Microarray Data * Reconstruction of the Yeast Cell Cycle by Partial Correlations of Higher Order * Bilayer Verification Algorithm * Probabilistic Boolean Networks as Models for Gene Regulation * Estimating Transcriptional Regulatory Networks by a Bayesian Network * Analysis of Therapeutic Compound Effects * Statistical Methods for Inference of Genetic Networks and Regulatory Modules * Identification of Genetic Networks by Structural Equations * Predicting Functional Modules Using Microarray and Protein Interaction Data * Integrating Results from Literature Mining and Microarray Experiments to Infer Gene Networks The book is for both, scientists using the technique as well as those developing new analysis techniques.
Author : Aidong Zhang
Publisher : World Scientific Publishing Company
ISBN 13 : 9813106646
Total Pages : 356 pages
Book Rating : 4.8/5 (131 download)
Download or read book Advanced Analysis Of Gene Expression Microarray Data written by Aidong Zhang and published by World Scientific Publishing Company. This book was released on 2006-06-27 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the development and application of the latest advanced data mining, machine learning, and visualization techniques for the identification of interesting, significant, and novel patterns in gene expression microarray data.Biomedical researchers will find this book invaluable for learning the cutting-edge methods for analyzing gene expression microarray data. Specifically, the coverage includes the following state-of-the-art methods:• Gene-based analysis: the latest novel clustering algorithms to identify co-expressed genes and coherent patterns in gene expression microarray data sets• Sample-based analysis: supervised and unsupervised methods for the reduction of the gene dimensionality to select significant genes. A series of approaches to disease classification and discovery are also described• Pattern-based analysis: methods for ascertaining the relationship between (subsets of) genes and (subsets of) samples. Various novel pattern-based clustering algorithms to find the coherent patterns embedded in the sub-attribute spaces are discussed• Visualization tools: various methods for gene expression data visualization. The visualization process is intended to transform the gene expression data set from high-dimensional space into a more easily understood two- or three-dimensional space.
Author : Daniel P. Berrar
Publisher : Springer Science & Business Media
ISBN 13 : 0306478153
Total Pages : 382 pages
Book Rating : 4.3/5 (64 download)
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.
Author : Yuanzhang Li
Publisher :
ISBN 13 :
Total Pages : 368 pages
Book Rating : 4.:/5 (229 download)
Download or read book Robust Bayesian Analysis written by Yuanzhang Li and published by . This book was released on 1990 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt:
