Microarray Image And Data Analysis

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Microarray Image and Data Analysis

Author : Luis Rueda
Publisher : CRC Press
Page : 520 pages
File Size : 41,6 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.

Microarray Image Analysis

Author : Karl Fraser,Zidong Wang,Xiaohui Liu
Publisher : CRC Press
Page : 337 pages
File Size : 53,7 Mb
Release : 2010-01-25
Category : Mathematics
ISBN : 9781420091540

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Microarray Image Analysis by Karl Fraser,Zidong Wang,Xiaohui Liu Pdf

To harness the high-throughput potential of DNA microarray technology, it is crucial that the analysis stages of the process are decoupled from the requirements of operator assistance. Microarray Image Analysis: An Algorithmic Approach presents an automatic system for microarray image processing to make this decoupling a reality. The proposed syste

Guide to Analysis of DNA Microarray Data

Author : Steen Knudsen
Publisher : John Wiley & Sons
Page : 194 pages
File Size : 48,5 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.

Analyzing Microarray Gene Expression Data

Author : Geoffrey J. McLachlan,Kim-Anh Do,Christophe Ambroise
Publisher : John Wiley & Sons
Page : 366 pages
File Size : 42,6 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

Methods of Microarray Data Analysis III

Author : Kimberly F. Johnson,Simon M. Lin
Publisher : Springer Science & Business Media
Page : 252 pages
File Size : 55,7 Mb
Release : 2007-05-08
Category : Science
ISBN : 9780306483547

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

As microarray technology has matured, data analysis methods have advanced as well. Methods Of Microarray Data Analysis III is the third book in this pioneering series dedicated to the existing new field of microarrays. While initial techniques focused on classification exercises (volume I of this series), and later on pattern extraction (volume II of this series), this volume focuses on data quality issues. Problems such as background noise determination, analysis of variance, and errors in data handling are highlighted. Three tutorial papers are presented to assist with a basic understanding of underlying principles in microarray data analysis, and twelve new papers are highlighted analyzing the same CAMDA'02 datasets: the Project Normal data set or the Affymetrix Latin Square data set. A comparative study of these analytical methodologies brings to light problems, solutions and new ideas. This book is an excellent reference for academic and industrial researchers who want to keep abreast of the state of art of microarray data analysis.

Microarray Data Analysis

Author : Giuseppe Agapito
Publisher : Humana
Page : 0 pages
File Size : 47,5 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.

Methods of Microarray Data Analysis IV

Author : Jennifer S. Shoemaker,Simon M. Lin
Publisher : Springer Science & Business Media
Page : 266 pages
File Size : 44,7 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.

Methods of Microarray Data Analysis II

Author : Simon M. Lin,Kimberly F. Johnson
Publisher : Springer Science & Business Media
Page : 214 pages
File Size : 48,7 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.

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 : 43,6 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.

Statistics and Data Analysis for Microarrays Using R and Bioconductor

Author : Sorin Draghici
Publisher : CRC Press
Page : 1036 pages
File Size : 50,6 Mb
Release : 2016-04-19
Category : Computers
ISBN : 9781439809761

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Statistics and Data Analysis for Microarrays Using R and Bioconductor by Sorin Draghici Pdf

Richly illustrated in color, Statistics and Data Analysis for Microarrays Using R and Bioconductor, Second Edition provides a clear and rigorous description of powerful analysis techniques and algorithms for mining and interpreting biological information. Omitting tedious details, heavy formalisms, and cryptic notations, the text takes a hands-on,

Microarray Gene Expression Data Analysis

Author : Helen Causton,John Quackenbush,Alvis Brazma
Publisher : John Wiley & Sons
Page : 176 pages
File Size : 41,8 Mb
Release : 2009-04-01
Category : Science
ISBN : 9781444311563

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Microarray Gene Expression Data Analysis by Helen Causton,John Quackenbush,Alvis Brazma Pdf

This guide covers aspects of designing microarray experiments and analysing the data generated, including information on some of the tools that are available from non-commercial sources. Concepts and principles underpinning gene expression analysis are emphasised and wherever possible, the mathematics has been simplified. The guide is intended for use by graduates and researchers in bioinformatics and the life sciences and is also suitable for statisticians who are interested in the approaches currently used to study gene expression. Microarrays are an automated way of carrying out thousands of experiments at once, and allows scientists to obtain huge amounts of information very quickly Short, concise text on this difficult topic area Clear illustrations throughout Written by well-known teachers in the subject Provides insight into how to analyse the data produced from microarrays

Methods of Microarray Data Analysis

Author : Simon M. Lin,Kimberly F. Johnson
Publisher : Springer Science & Business Media
Page : 192 pages
File Size : 41,9 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.

Statistical Analysis of Gene Expression Microarray Data

Author : Terry Speed
Publisher : CRC Press
Page : 237 pages
File Size : 50,5 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

A Biologist's Guide to Analysis of DNA Microarray Data

Author : Steen Knudsen
Publisher : John Wiley & Sons
Page : 148 pages
File Size : 40,8 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.

Data Analysis Tools for DNA Microarrays

Author : Sorin Drăghici
Publisher : Chapman and Hall/CRC
Page : 552 pages
File Size : 45,5 Mb
Release : 2003-06-04
Category : Science
ISBN : 1584883154

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Data Analysis Tools for DNA Microarrays by Sorin Drăghici Pdf

Technology today allows the collection of biological information at an unprecedented level of detail and in increasingly vast quantities. To reap real knowledge from the mountains of data produced, however, requires interdisciplinary skills-a background not only in biology but also in computer science and the tools and techniques of data analysis. To help meet the challenges of DNA research, Data Analysis Tools for DNA Microarrays builds the foundation in the statistics and data analysis tools needed by biologists and provides the overview of microarrays needed by computer scientists. It first presents the basics of microarray technology and more importantly, the specific problems the technology poses from the data analysis perspective. It then introduces the fundamentals of statistics and the details of the techniques most commonly used to analyze microarray data. The final chapter focuses on commercial applications with sections exploring various software packages from BioDiscovery, Insightful, SAS, and Spotfire. The book is richly illustrated with more than 230 figures in full color and comes with a CD-ROM containing full-feature trial versions of software for image analysis (ImaGene, BioDiscovery Inc.) and data analysis (GeneSight, BioDiscovery Inc. and S-Plus Array Analyzer, Insightful Inc.). Written in simple language and illustrated in full color, Data Analysis Tools for DNA Microarrays lowers the communication barrier between life scientists and analytical scientists. It prepares those charged with analyzing microarray data to make informed choices about the techniques to use in a given situation and contribute to further advances in the field.