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A Practical Approach To Microarray Data Analysis
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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.
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 . This book was released on 2007-08-01 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book DNA Microarrays written by Mark Schena and published by Practical Approach Series. This book was released on 1999 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: DNA Microarrays: A Practical Approach is the first comprehensive overview of an exciting and powerful new technology. DNA microarrays, or biochips, are small glass chips embedded with ordered rows of DNA, providing a massive parallel platform for data gathering and representing a fundamental technical advance in biomedical research. Such biochips gather data at an unprecedented rate by enabling the use of advanced fabrication, detection, and data mining technologies. Written and edited by experts in the field, this book provides fascinating insight into this remarkable advancement. It opens with an introduction to the technology of DNA microarrays, emphasizing the methodological fundamentals of biochips, and continues with descriptions of the use of confocal scanning in microarray detection and techniques for the efficient cloning and screening of differentially expressed genes. The chapters address many topics, among them assay optimization, antisense scanning arrays, the manufacture of molecular arrays, and gene expression analysis. Also addressed are the uses of expression data in bioinformatics, of active microelectronic arrays for DNA hybridization analysis, and of microarray technology in pharmacogenomics. DNA Microarrays: A Practical Approach is ideal for researchers investigating patterns of gene expression (and the relationship with disease), and it is essential for any researcher interested in the use of biochips.
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
Book Synopsis RNA-seq Data Analysis by : Eija Korpelainen
Download or read book RNA-seq Data Analysis written by Eija Korpelainen and published by CRC Press. This book was released on 2014-09-19 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: The State of the Art in Transcriptome AnalysisRNA sequencing (RNA-seq) data offers unprecedented information about the transcriptome, but harnessing this information with bioinformatics tools is typically a bottleneck. RNA-seq Data Analysis: A Practical Approach enables researchers to examine differential expression at gene, exon, and transcript le
Book Synopsis Guide to Analysis of DNA Microarray Data by : Steen Knudsen
Download or read book Guide to Analysis of DNA Microarray Data written by Steen Knudsen and published by John Wiley & Sons. This book was released on 2005-03-04 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written for biologists and medical researchers who don't have any special training in data analysis and statistics, Guide to Analysis of DNA Microarray Data, Second Edition begins where DNA array equipment leaves off: the image produced by the microarray. The text deals with the questions that arise starting at this point, providing an introduction to microarray technology, then moving on to image analysis, data analysis, cluster analysis, and beyond. With all chapters rewritten, updated, and expanded to include the latest generation of technology and methods, Guide to Analysis of DNA Microarray Data, Second Edition offers practitioners reliable information using concrete examples and a clear, comprehensible style. This Second Edition features entirely new chapters on: * Image analysis * Experiment design * Automated analysis, integrated analysis, and systems biology * Interpretation of results Intended for readers seeking practical applications, this text covers a broad spectrum of proven approaches in this rapidly growing technology. Additional features include further reading suggestions for each chapter, as well as a thorough review of available analysis software.
Book Synopsis Exploration and Analysis of DNA Microarray and Other High-Dimensional Data by : Dhammika Amaratunga
Download or read book Exploration and Analysis of DNA Microarray and Other High-Dimensional Data written by Dhammika Amaratunga and published by John Wiley & Sons. This book was released on 2014-01-27 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition “…extremely well written…a comprehensiveand up-to-date overview of this important field.” –Journal of Environmental Quality Exploration and Analysis of DNA Microarray and OtherHigh-Dimensional Data, Second Edition provides comprehensivecoverage of recent advancements in microarray data analysis. Acutting-edge guide, the Second Edition demonstrates variousmethodologies for analyzing data in biomedical research and offersan overview of the modern techniques used in microarray technologyto study patterns of gene activity. The new edition answers the need for an efficient outline of allphases of this revolutionary analytical technique, frompreprocessing to the analysis stage. Utilizing research andexperience from highly-qualified authors in fields of dataanalysis, Exploration and Analysis of DNA Microarray and OtherHigh-Dimensional Data, Second Edition features: A new chapter on the interpretation of findings that includes adiscussion of signatures and material on gene set analysis,including network analysis New topics of coverage including ABC clustering, biclustering,partial least squares, penalized methods, ensemble methods, andenriched ensemble methods Updated exercises to deepen knowledge of the presented materialand provide readers with resources for further study The book is an ideal reference for scientists in biomedical andgenomics research fields who analyze DNA microarrays and proteinarray data, as well as statisticians and bioinformaticspractitioners. Exploration and Analysis of DNA Microarray andOther High-Dimensional Data, Second Edition is also a usefultext for graduate-level courses on statistics, computationalbiology, and bioinformatics.
Book Synopsis Statistics for Microarrays by : Ernst Wit
Download or read book Statistics for Microarrays written by Ernst Wit and published by John Wiley & Sons. This book was released on 2004-11-19 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interest in microarrays has increased considerably in the last ten years. This increase in the use of microarray technology has led to the need for good standards of microarray experimental notation, data representation, and the introduction of standard experimental controls, as well as standard data normalization and analysis techniques. Statistics for Microarrays: Design, Analysis and Inference is the first book that presents a coherent and systematic overview of statistical methods in all stages in the process of analysing microarray data – from getting good data to obtaining meaningful results. Provides an overview of statistics for microarrays, including experimental design, data preparation, image analysis, normalization, quality control, and statistical inference. Features many examples throughout using real data from microarray experiments. Computational techniques are integrated into the text. Takes a very practical approach, suitable for statistically-minded biologists. Supported by a Website featuring colour images, software, and data sets. Primarily aimed at statistically-minded biologists, bioinformaticians, biostatisticians, and computer scientists working with microarray data, the book is also suitable for postgraduate students of bioinformatics.
Book Synopsis Microarray Image and Data Analysis by : Luis Rueda
Download or read book Microarray Image and Data Analysis written by Luis Rueda and published by CRC Press. This book was released on 2018-09-03 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: Microarray Image and Data Analysis: Theory and Practice is a compilation of the latest and greatest microarray image and data analysis methods from the multidisciplinary international research community. Delivering a detailed discussion of the biological aspects and applications of microarrays, the book: Describes the key stages of image processing, gridding, segmentation, compression, quantification, and normalization Features cutting-edge approaches to clustering, biclustering, and the reconstruction of regulatory networks Covers different types of microarrays such as DNA, protein, tissue, and low- and high-density oligonucleotide arrays Examines the current state of various microarray technologies, including their availability and affordability Explains how data generated by microarray experiments are analyzed to obtain meaningful biological conclusions An essential reference for academia and industry, Microarray Image and Data Analysis: Theory and Practice provides readers with valuable tools and techniques that extend to a wide range of biological studies and microarray platforms.
Book Synopsis Microarray Data Analysis by : Giuseppe Agapito
Download or read book Microarray Data Analysis written by Giuseppe Agapito and published by Humana. This book was released on 2022-12-15 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This meticulous book explores the leading methodologies, techniques, and tools for microarray data analysis, given the difficulty of harnessing the enormous amount of data. The book includes examples and code in R, requiring only an introductory computer science understanding, and the structure and the presentation of the chapters make it suitable for use in bioinformatics courses. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of key detail and expert implementation advice that ensures successful results and reproducibility. Authoritative and practical, Microarray Data Analysis is an ideal guide for students or researchers who need to learn the main research topics and practitioners who continue to work with microarray datasets.
Book Synopsis Analysis of Microarray Data by : Matthias Dehmer
Download or read book Analysis of Microarray Data written by Matthias Dehmer and published by John Wiley & Sons. This book was released on 2008-03-17 with total page 448 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 :Jennifer S. Shoemaker Publisher :Springer Science & Business Media ISBN 13 :0387230777 Total Pages :266 pages Book Rating :4.3/5 (872 download)
Book Synopsis Methods of Microarray Data Analysis IV by : Jennifer S. Shoemaker
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 2006-01-16 with total page 266 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.
Book Synopsis Methods of Microarray Data Analysis II by : Simon M. Lin
Download or read book Methods of Microarray Data Analysis II written by Simon M. Lin and published by Springer Science & Business Media. This book was released on 2007-05-08 with total page 214 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 II is the second book in this pioneering series 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 II focuses on a single data set, 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.
Book Synopsis Gene Expression Studies Using Affymetrix Microarrays by : Hinrich Gohlmann
Download or read book Gene Expression Studies Using Affymetrix Microarrays written by Hinrich Gohlmann and published by CRC Press. This book was released on 2009-07-15 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Affymetrix GeneChip® system is one of the most widely adapted microarray platforms. However, due to the overwhelming amount of information available, many Affymetrix users tend to stick to the default analysis settings and may end up drawing sub-optimal conclusions. Written by a molecular biologist and a biostatistician with a combined decade of experience in practical expression profiling experiments and data analyses, Gene Expression Studies Using Affymetrix Microarrays tears down the omnipresent language barriers among molecular biology, bioinformatics, and biostatistics by explaining the entire process of a gene expression study from conception to conclusion. Truly Multidisciplinary: Merges Molecular Biology, Bioinformatics, and Biostatistics This authoritative resource covers important technical and statistical pitfalls and problems, helping not only to explain concepts outside the domain of researchers, but to provide additional guidance in their field of expertise. The book also describes technical and statistical methods conceptually with illustrative, full-color examples, enabling those inexperienced with gene expression studies to grasp the basic principles. Gene Expression Studies Using Affymetrix Microarrays provides novices with a detailed, yet focused introductory course and practical user guide. Specialized experts will also find it useful as a translation dictionary to understand other involved disciplines or to get a broader picture of microarray gene expression studies in general. Although focusing on Affymetrix gene expression, this globally relevant guide covers topics that are equally useful for other microarray platforms and other Affymetrix applications.
Book Synopsis High-dimensional Microarray Data Analysis by : Shuichi Shinmura
Download or read book High-dimensional Microarray Data Analysis written by Shuichi Shinmura and published by Springer. This book was released on 2019-05-24 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows how to decompose high-dimensional microarrays into small subspaces (Small Matryoshkas, SMs), statistically analyze them, and perform cancer gene diagnosis. The information is useful for genetic experts, anyone who analyzes genetic data, and students to use as practical textbooks. Discriminant analysis is the best approach for microarray consisting of normal and cancer classes. Microarrays are linearly separable data (LSD, Fact 3). However, because most linear discriminant function (LDF) cannot discriminate LSD theoretically and error rates are high, no one had discovered Fact 3 until now. Hard-margin SVM (H-SVM) and Revised IP-OLDF (RIP) can find Fact3 easily. LSD has the Matryoshka structure and is easily decomposed into many SMs (Fact 4). Because all SMs are small samples and LSD, statistical methods analyze SMs easily. However, useful results cannot be obtained. On the other hand, H-SVM and RIP can discriminate two classes in SM entirely. RatioSV is the ratio of SV distance and discriminant range. The maximum RatioSVs of six microarrays is over 11.67%. This fact shows that SV separates two classes by window width (11.67%). Such easy discrimination has been unresolved since 1970. The reason is revealed by facts presented here, so this book can be read and enjoyed like a mystery novel. Many studies point out that it is difficult to separate signal and noise in a high-dimensional gene space. However, the definition of the signal is not clear. Convincing evidence is presented that LSD is a signal. Statistical analysis of the genes contained in the SM cannot provide useful information, but it shows that the discriminant score (DS) discriminated by RIP or H-SVM is easily LSD. For example, the Alon microarray has 2,000 genes which can be divided into 66 SMs. If 66 DSs are used as variables, the result is a 66-dimensional data. These signal data can be analyzed to find malignancy indicators by principal component analysis and cluster analysis.
Download or read book Biocomputing 2003 written by and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Pacific Symposium on Biocomputing 2003 by : Russ B. Altman
Download or read book Pacific Symposium on Biocomputing 2003 written by Russ B. Altman and published by World Scientific. This book was released on 2002 with total page 671 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Pacific Symposium on Biocomputing (PSB 2003) is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. The rigorously peer-reviewed papers and presentations are collected in this archival proceedings volume. PSB 2003 brings together top researchers from the US, the Asia-Pacific region and around the world to exchange research findings and address open issues in all aspects of computational biology. PSB is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology.
