A Practical Approach To Microarray Data Analysis

Author : Daniel P. Berrar,Werner Dubitzky,Martin Granzow
Publisher : Springer Science & Business Media
Page : 382 pages
File Size : 54,7 Mb
Release : 2007-05-08
Category : Science
ISBN : 9780306478154

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A Practical Approach to Microarray Data Analysis by Daniel P. Berrar,Werner Dubitzky,Martin Granzow Pdf

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 : Daniel P. Berrar
Publisher : Unknown
Page : 384 pages
File Size : 48,5 Mb
Release : 2007-08-01
Category : DNA microarrays
ISBN : 8181287312

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A Practical Approach To Microarray Data Analysis by Daniel P. Berrar Pdf

Author : Geoffrey J. McLachlan,Kim-Anh Do,Christophe Ambroise
Publisher : John Wiley & Sons
Page : 366 pages
File Size : 49,5 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 : Eija Korpelainen,Jarno Tuimala,Panu Somervuo,Mikael Huss,Garry Wong
Publisher : CRC Press
Page : 322 pages
File Size : 40,8 Mb
Release : 2014-09-19
Category : Mathematics
ISBN : 9781466595019

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RNA-seq Data Analysis by Eija Korpelainen,Jarno Tuimala,Panu Somervuo,Mikael Huss,Garry Wong Pdf

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

Author : Steen Knudsen
Publisher : John Wiley & Sons
Page : 194 pages
File Size : 41,8 Mb
Release : 2005-03-04
Category : Science
ISBN : 9780471670261

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Guide to Analysis of DNA Microarray Data by Steen Knudsen Pdf

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.

Author : Mark Schena
Publisher : Practical Approach Series
Page : 236 pages
File Size : 41,8 Mb
Release : 1999
Category : Medical
ISBN : 0199637768

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DNA Microarrays by Mark Schena Pdf

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.

Author : Luis Rueda
Publisher : CRC Press
Page : 520 pages
File Size : 42,6 Mb
Release : 2018-09-03
Category : Science
ISBN : 9781466586871

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Microarray Image and Data Analysis by Luis Rueda Pdf

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.

Author : Simon M. Lin,Kimberly F. Johnson
Publisher : Springer Science & Business Media
Page : 214 pages
File Size : 55,9 Mb
Release : 2007-05-08
Category : Science
ISBN : 9780306475986

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Methods of Microarray Data Analysis II 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 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.

Author : Jennifer S. Shoemaker,Simon M. Lin
Publisher : Springer Science & Business Media
Page : 266 pages
File Size : 52,9 Mb
Release : 2006-01-16
Category : Medical
ISBN : 9780387230771

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Methods of Microarray Data Analysis IV by Jennifer S. Shoemaker,Simon M. Lin Pdf

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 : Ernst Wit,John McClure
Publisher : John Wiley & Sons
Page : 286 pages
File Size : 52,9 Mb
Release : 2004-07-23
Category : Mathematics
ISBN : 0470849932

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Statistics for Microarrays by Ernst Wit,John McClure Pdf

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.

Author : Giuseppe Agapito
Publisher : Humana
Page : 0 pages
File Size : 41,7 Mb
Release : 2022-12-15
Category : Science
ISBN : 1071618415

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Microarray Data Analysis by Giuseppe Agapito Pdf

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.

Author : Matthias Dehmer,Frank Emmert-Streib
Publisher : John Wiley & Sons
Page : 448 pages
File Size : 54,6 Mb
Release : 2008-03-17
Category : Medical
ISBN : 3527318224

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Analysis of Microarray Data by Matthias Dehmer,Frank Emmert-Streib Pdf

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 : Steen Knudsen
Publisher : John Wiley & Sons
Page : 148 pages
File Size : 40,6 Mb
Release : 2011-09-23
Category : Science
ISBN : 9780471461180

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A Biologist's Guide to Analysis of DNA Microarray Data by Steen Knudsen Pdf

A great introductory book that details reliable approaches to problems met in standard microarray data analyses. It provides examples of established approaches such as cluster analysis, function prediction, and principle component analysis. Discover real examples to illustrate the key concepts of data analysis. Written for those without any advanced background in math, statistics, or computer sciences, this book is essential for anyone interested in harnessing the immense potential of microarrays in biology and medicine.

Author : Shuichi Shinmura
Publisher : Springer
Page : 419 pages
File Size : 43,6 Mb
Release : 2019-05-14
Category : Medical
ISBN : 9789811359989

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High-dimensional Microarray Data Analysis by Shuichi Shinmura Pdf

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.

Author : Anonim
Publisher : Unknown
Page : 128 pages
File Size : 45,9 Mb
Release : 2024-06-27
Category : Electronic
ISBN : 9789814487108

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Biocomputing 2003 by Anonim Pdf