Microarray Data

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Analyzing Microarray Gene Expression Data

Geoffrey J. McLachlan,Kim-Anh Do,Christophe Ambroise
Analyzing Microarray Gene Expression Data Book PDF

Author : Geoffrey J. McLachlan,Kim-Anh Do,Christophe Ambroise
Publisher : John Wiley & Sons
Page : 366 pages
File Size : 44,7 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

A Practical Approach to Microarray Data Analysis

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

Author : Daniel P. Berrar,Werner Dubitzky,Martin Granzow
Publisher : Springer Science & Business Media
Page : 382 pages
File Size : 52,5 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.

Statistical Analysis of Gene Expression Microarray Data

Terry Speed
Statistical Analysis of Gene Expression Microarray Data Book PDF

Author : Terry Speed
Publisher : CRC Press
Page : 237 pages
File Size : 49,8 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

Methods of Microarray Data Analysis III

Kimberly F. Johnson,Simon M. Lin
Methods of Microarray Data Analysis III Book PDF

Author : Kimberly F. Johnson,Simon M. Lin
Publisher : Springer Science & Business Media
Page : 247 pages
File Size : 44,6 Mb
Release : 2003-09-30
Category : Science
ISBN : 9781402075827

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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.

Bioinformatics and Computational Biology Solutions Using R and Bioconductor

Robert Gentleman,Vincent Carey,Wolfgang Huber,Rafael Irizarry,Sandrine Dudoit
Bioinformatics and Computational Biology Solutions Using R and Bioconductor Book PDF

Author : Robert Gentleman,Vincent Carey,Wolfgang Huber,Rafael Irizarry,Sandrine Dudoit
Publisher : Springer Science & Business Media
Page : 478 pages
File Size : 45,6 Mb
Release : 2005-12-29
Category : Computers
ISBN : 9780387293622

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Bioinformatics and Computational Biology Solutions Using R and Bioconductor by Robert Gentleman,Vincent Carey,Wolfgang Huber,Rafael Irizarry,Sandrine Dudoit Pdf

Full four-color book. Some of the editors created the Bioconductor project and Robert Gentleman is one of the two originators of R. All methods are illustrated with publicly available data, and a major section of the book is devoted to fully worked case studies. Code underlying all of the computations that are shown is made available on a companion website, and readers can reproduce every number, figure, and table on their own computers.

Microarray Gene Expression Data Analysis

Helen Causton,John Quackenbush,Alvis Brazma
Microarray Gene Expression Data Analysis Book PDF

Author : Helen Causton,John Quackenbush,Alvis Brazma
Publisher : John Wiley & Sons
Page : 176 pages
File Size : 40,9 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

Microarray Data Analysis

Giuseppe Agapito
Microarray Data Analysis Book PDF

Author : Giuseppe Agapito
Publisher : Humana
Page : 0 pages
File Size : 41,6 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.

Analysis of Microarray Gene Expression Data

Mei-Ling Ting Lee
Analysis of Microarray Gene Expression Data Book PDF

Author : Mei-Ling Ting Lee
Publisher : Springer Science & Business Media
Page : 378 pages
File Size : 49,9 Mb
Release : 2004-04-30
Category : Mathematics
ISBN : 9780792370871

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Analysis of Microarray Gene Expression Data by Mei-Ling Ting Lee Pdf

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.

Methods of Microarray Data Analysis

Simon M. Lin,Kimberly F. Johnson
Methods of Microarray Data Analysis Book PDF

Author : Simon M. Lin,Kimberly F. Johnson
Publisher : Springer Science & Business Media
Page : 192 pages
File Size : 46,5 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.

Microarray Data

Shailaja R. Deshmukh,Sudha G. Purohit
Microarray Data Book PDF

Author : Shailaja R. Deshmukh,Sudha G. Purohit
Publisher : Alpha Science International, Limited
Page : 354 pages
File Size : 51,6 Mb
Release : 2007
Category : Business & Economics
ISBN : STANFORD:36105131675089

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Microarray Data by Shailaja R. Deshmukh,Sudha G. Purohit Pdf

Functional Genomics, a branch of bioinformatics, is essentially an interdisciplinary subject in which biologists, statisticians and computer experts interact to analyze the microarray data. This book caters to the needs of all the three disciplines. For biologists and computer scientists, it explains concepts of statistics and statistical inference. For Biologists and Statisticians, it provides annotated R programs to analyze microarray data. For Statisticians and Computer scientists, it explains basics of biology relevant to microarray experiment. Thus, the book will be useful to scientists from all the three disciplines, with not much knowledge of other disciplines, to analyze microarray data and interpret the results.

Analysis of Microarray Data

Matthias Dehmer,Frank Emmert-Streib
Analysis of Microarray Data Book PDF

Author : Matthias Dehmer,Frank Emmert-Streib
Publisher : John Wiley & Sons
Page : 438 pages
File Size : 45,5 Mb
Release : 2008-09-08
Category : Medical
ISBN : 9783527622825

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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.

Microarray Data Analysis

Michael J. Korenberg
Microarray Data Analysis Book PDF

Author : Michael J. Korenberg
Publisher : Springer Science & Business Media
Page : 569 pages
File Size : 48,9 Mb
Release : 2008-02-03
Category : Science
ISBN : 9781597453905

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Microarray Data Analysis by Michael J. Korenberg Pdf

In this new volume, renowned authors contribute fascinating, cutting-edge insights into microarray data analysis. Information on an array of topics is included in this innovative book including in-depth insights into presentations of genomic signal processing. Also detailed is the use of tiling arrays for large genomes analysis. The protocols follow the successful Methods in Molecular BiologyTM series format, offering step-by-step instructions, an introduction outlining the principles behind the technique, lists of the necessary equipment and reagents, and tips on troubleshooting and avoiding pitfalls.

A Beginner’s Guide to Microarrays

Eric M. Blalock
A Beginner s Guide to Microarrays Book PDF

Author : Eric M. Blalock
Publisher : Springer Science & Business Media
Page : 356 pages
File Size : 41,5 Mb
Release : 2011-06-27
Category : Science
ISBN : 9781441987600

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A Beginner’s Guide to Microarrays by Eric M. Blalock Pdf

A Beginner's Guide to Microarrays addresses two audiences - the core facility manager who produces, hybridizes, and scans arrays, and the basic research scientist who will be performing the analysis and interpreting the results. User friendly coverage and detailed protocols are provided for the technical steps and procedures involved in many facets of microarray technology, including: -Cleaning and coating glass slides, -Designing oligonucleotide probes, -Constructing arrays for the detection and quantification of different bacterial species, -Preparing spotting solutions, -Troubleshooting spotting problems, -Setting up and running a core facility, -Normalizing background signal and controlling for systematic variance, -Designing experiments for maximum effect, -Analyzing data with statistical procedures, -Clustering data with machine-learning protocols.

Design and Analysis of DNA Microarray Investigations

Richard M. Simon,Edward L. Korn,Lisa M. McShane,Michael D. Radmacher,George W. Wright,Yingdong Zhao
Design and Analysis of DNA Microarray Investigations Book PDF

Author : Richard M. Simon,Edward L. Korn,Lisa M. McShane,Michael D. Radmacher,George W. Wright,Yingdong Zhao
Publisher : Springer Science & Business Media
Page : 200 pages
File Size : 46,7 Mb
Release : 2006-05-09
Category : Medical
ISBN : 9780387218663

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Design and Analysis of DNA Microarray Investigations by Richard M. Simon,Edward L. Korn,Lisa M. McShane,Michael D. Radmacher,George W. Wright,Yingdong Zhao Pdf

The analysis of gene expression profile data from DNA micorarray studies are discussed in this book. It provides a review of available methods and presents it in a manner that is intelligible to biologists. It offers an understanding of the design and analysis of experiments utilizing microarrays to benefit scientists. It includes an Appendix tutorial on the use of BRB-ArrayTools and step by step analyses of several major datasets using this software which is available from the National Cancer Institute.

Statistical Analysis of Gene Expression Microarray Data

Terry Speed
Statistical Analysis of Gene Expression Microarray Data Book PDF

Author : Terry Speed
Publisher : CRC Press
Page : 332 pages
File Size : 49,6 Mb
Release : 2003-03-26
Category : Mathematics
ISBN : 9781135441364

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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