Analyzing Microarray Gene Expression Data


Analyzing Microarray Gene Expression Data
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Analyzing Microarray Gene Expression Data


Analyzing Microarray Gene Expression Data
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Author : Geoffrey J. McLachlan
language : en
Publisher: John Wiley & Sons
Release Date : 2005-02-18

Analyzing Microarray Gene Expression Data written by Geoffrey J. McLachlan and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-02-18 with Mathematics categories.


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



Analysis Of Microarray Gene Expression Data


Analysis Of Microarray Gene Expression Data
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Author : Mei-Ling Ting Lee
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-05-08

Analysis Of Microarray Gene Expression Data written by Mei-Ling Ting Lee and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-05-08 with Science categories.


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.



Microarray Gene Expression Data Analysis


Microarray Gene Expression Data Analysis
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Author : Helen Causton
language : en
Publisher: John Wiley & Sons
Release Date : 2009-04-01

Microarray Gene Expression Data Analysis written by Helen Causton and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-01 with Science categories.


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



Advanced Analysis Of Gene Expression Microarray Data


Advanced Analysis Of Gene Expression Microarray Data
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Author : Aidong Zhang
language : en
Publisher: World Scientific
Release Date : 2006

Advanced Analysis Of Gene Expression Microarray Data written by Aidong Zhang and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Science categories.


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. Describes cutting-edge methods for analyzing gene expression microarray data. Coverage includes gene-based analysis, sample-based analysis, pattern-based analysis and visualization tools.



Statistical Analysis Of Gene Expression Microarray Data


Statistical Analysis Of Gene Expression Microarray Data
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Author : Terry Speed
language : en
Publisher: CRC Press
Release Date : 2003-03-26

Statistical Analysis Of Gene Expression Microarray Data written by Terry Speed and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-03-26 with Mathematics categories.


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 Practical Approach To Microarray Data Analysis


A Practical Approach To Microarray Data Analysis
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Author : Daniel P. Berrar
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-05-08

A Practical Approach To Microarray Data Analysis written by Daniel P. Berrar and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-05-08 with Science categories.


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.



Dna Microarray Technology And Data Analysis In Cancer Research


Dna Microarray Technology And Data Analysis In Cancer Research
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Author :
language : en
Publisher:
Release Date :

Dna Microarray Technology And Data Analysis In Cancer Research written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.




Microarray Data


Microarray Data
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Author : Shailaja R. Deshmukh
language : en
Publisher: Alpha Science International, Limited
Release Date : 2007

Microarray Data written by Shailaja R. Deshmukh and has been published by Alpha Science International, Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Business & Economics categories.


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.



Methods Of Microarray Data Analysis


Methods Of Microarray Data Analysis
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Author : Simon M. Lin
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Methods Of Microarray Data Analysis written by Simon M. Lin and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Science categories.


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.



Methods Of Microarray Data Analysis Iii


Methods Of Microarray Data Analysis Iii
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Author : Kimberly F. Johnson
language : en
Publisher: Springer Science & Business Media
Release Date : 2003-09-30

Methods Of Microarray Data Analysis Iii written by Kimberly F. Johnson and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-09-30 with Science categories.


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.