Statistical Analysis Of Gene Expression Microarray Data

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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 : 53,9 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

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 : 44,7 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.

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 : 45,7 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

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 : 377 pages
File Size : 45,7 Mb
Release : 2007-05-08
Category : Science
ISBN : 9781402077883

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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.

The Analysis of Gene Expression Data

Giovanni Parmigiani,Elizabeth S. Garett,Rafael A. Irizarry,Scott L. Zeger
The Analysis of Gene Expression Data Book PDF

Author : Giovanni Parmigiani,Elizabeth S. Garett,Rafael A. Irizarry,Scott L. Zeger
Publisher : Springer Science & Business Media
Page : 456 pages
File Size : 55,7 Mb
Release : 2006-04-11
Category : Medical
ISBN : 9780387216799

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The Analysis of Gene Expression Data by Giovanni Parmigiani,Elizabeth S. Garett,Rafael A. Irizarry,Scott L. Zeger Pdf

This book presents practical approaches for the analysis of data from gene expression micro-arrays. It describes the conceptual and methodological underpinning for a statistical tool and its implementation in software. The book includes coverage of various packages that are part of the Bioconductor project and several related R tools. The materials presented cover a range of software tools designed for varied audiences.

Advanced Analysis Of Gene Expression Microarray Data

Aidong Zhang
Advanced Analysis Of Gene Expression Microarray Data Book PDF

Author : Aidong Zhang
Publisher : World Scientific Publishing Company
Page : 356 pages
File Size : 45,8 Mb
Release : 2006-06-27
Category : Science
ISBN : 9789813106642

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Advanced Analysis Of Gene Expression Microarray Data by Aidong Zhang Pdf

This book 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.Biomedical researchers will find this book invaluable for learning the cutting-edge methods for analyzing gene expression microarray data. Specifically, the coverage includes the following state-of-the-art methods:• Gene-based analysis: the latest novel clustering algorithms to identify co-expressed genes and coherent patterns in gene expression microarray data sets• Sample-based analysis: supervised and unsupervised methods for the reduction of the gene dimensionality to select significant genes. A series of approaches to disease classification and discovery are also described• Pattern-based analysis: methods for ascertaining the relationship between (subsets of) genes and (subsets of) samples. Various novel pattern-based clustering algorithms to find the coherent patterns embedded in the sub-attribute spaces are discussed• Visualization tools: various methods for gene expression data visualization. The visualization process is intended to transform the gene expression data set from high-dimensional space into a more easily understood two- or three-dimensional space.

Gene Expression Data Analysis

Pankaj Barah,Dhruba Kumar Bhattacharyya,Jugal Kumar Kalita
Gene Expression Data Analysis Book PDF

Author : Pankaj Barah,Dhruba Kumar Bhattacharyya,Jugal Kumar Kalita
Publisher : CRC Press
Page : 276 pages
File Size : 47,6 Mb
Release : 2021-11-08
Category : Computers
ISBN : 9781000425758

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Gene Expression Data Analysis by Pankaj Barah,Dhruba Kumar Bhattacharyya,Jugal Kumar Kalita Pdf

Development of high-throughput technologies in molecular biology during the last two decades has contributed to the production of tremendous amounts of data. Microarray and RNA sequencing are two such widely used high-throughput technologies for simultaneously monitoring the expression patterns of thousands of genes. Data produced from such experiments are voluminous (both in dimensionality and numbers of instances) and evolving in nature. Analysis of huge amounts of data toward the identification of interesting patterns that are relevant for a given biological question requires high-performance computational infrastructure as well as efficient machine learning algorithms. Cross-communication of ideas between biologists and computer scientists remains a big challenge. Gene Expression Data Analysis: A Statistical and Machine Learning Perspective has been written with a multidisciplinary audience in mind. The book discusses gene expression data analysis from molecular biology, machine learning, and statistical perspectives. Readers will be able to acquire both theoretical and practical knowledge of methods for identifying novel patterns of high biological significance. To measure the effectiveness of such algorithms, we discuss statistical and biological performance metrics that can be used in real life or in a simulated environment. This book discusses a large number of benchmark algorithms, tools, systems, and repositories that are commonly used in analyzing gene expression data and validating results. This book will benefit students, researchers, and practitioners in biology, medicine, and computer science by enabling them to acquire in-depth knowledge in statistical and machine-learning-based methods for analyzing gene expression data. Key Features: An introduction to the Central Dogma of molecular biology and information flow in biological systems A systematic overview of the methods for generating gene expression data Background knowledge on statistical modeling and machine learning techniques Detailed methodology of analyzing gene expression data with an example case study Clustering methods for finding co-expression patterns from microarray, bulkRNA, and scRNA data A large number of practical tools, systems, and repositories that are useful for computational biologists to create, analyze, and validate biologically relevant gene expression patterns Suitable for multidisciplinary researchers and practitioners in computer science and the biological sciences

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 : 43,5 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 Bioinformatics

Dov Stekel
Microarray Bioinformatics Book PDF

Author : Dov Stekel
Publisher : Cambridge University Press
Page : 296 pages
File Size : 51,6 Mb
Release : 2003-09-08
Category : Medical
ISBN : 052152587X

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Microarray Bioinformatics by Dov Stekel Pdf

This book is a comprehensive guide to all of the mathematics, statistics and computing you will need to successfully operate DNA microarray experiments. It is written for researchers, clinicians, laboratory heads and managers, from both biology and bioinformatics backgrounds, who work with, or who intend to work with microarrays. The book covers all aspects of microarray bioinformatics, giving you the tools to design arrays and experiments, to analyze your data, and to share your results with your organisation or with the international community. There are chapters covering sequence databases, oligonucleotide design, experimental design, image processing, normalisation, identifying differentially expressed genes, clustering, classification and data standards. The book is based on the highly successful Microarray Bioinformatics course at Oxford University, and therefore is ideally suited for teaching the subject at postgraduate or professional level.

Computational and Statistical Approaches to Genomics

Wei Zhang,Ilya Shmulevich
Computational and Statistical Approaches to Genomics Book PDF

Author : Wei Zhang,Ilya Shmulevich
Publisher : Springer Science & Business Media
Page : 329 pages
File Size : 42,5 Mb
Release : 2007-05-08
Category : Science
ISBN : 9780306478253

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Computational and Statistical Approaches to Genomics by Wei Zhang,Ilya Shmulevich Pdf

Computational and Statistical Genomics aims to help researchers deal with current genomic challenges. Topics covered include: overviews of the role of supercomputers in genomics research, the existing challenges and directions in image processing for microarray technology, and web-based tools for microarray data analysis; approaches to the global modeling and analysis of gene regulatory networks and transcriptional control, using methods, theories, and tools from signal processing, machine learning, information theory, and control theory; state-of-the-art tools in Boolean function theory, time-frequency analysis, pattern recognition, and unsupervised learning, applied to cancer classification, identification of biologically active sites, and visualization of gene expression data; crucial issues associated with statistical analysis of microarray data, statistics and stochastic analysis of gene expression levels in a single cell, statistically sound design of microarray studies and experiments; and biological and medical implications of genomics research.

Methods of Microarray Data Analysis IV

Jennifer S. Shoemaker,Simon M. Lin
Methods of Microarray Data Analysis IV Book PDF

Author : Jennifer S. Shoemaker,Simon M. Lin
Publisher : Springer Science & Business Media
Page : 266 pages
File Size : 41,9 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.

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 : 49,5 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.

Methods of Microarray Data Analysis II

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

Author : Simon M. Lin,Kimberly F. Johnson
Publisher : Springer Science & Business Media
Page : 214 pages
File Size : 53,7 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.

Statistical Methods for Microarray Data Analysis

Andrei Y. Yakovlev,Lev Klebanov,Daniel Gaile
Statistical Methods for Microarray Data Analysis Book PDF

Author : Andrei Y. Yakovlev,Lev Klebanov,Daniel Gaile
Publisher : Humana Press
Page : 212 pages
File Size : 54,6 Mb
Release : 2016-08-23
Category : Medical
ISBN : 1493950797

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Statistical Methods for Microarray Data Analysis by Andrei Y. Yakovlev,Lev Klebanov,Daniel Gaile Pdf

Microarrays for simultaneous measurement of redundancy of RNA species are used in fundamental biology as well as in medical research. Statistically,a microarray may be considered as an observation of very high dimensionality equal to the number of expression levels measured on it. In Statistical Methods for Microarray Data Analysis: Methods and Protocols, expert researchers in the field detail many methods and techniques used to study microarrays, guiding the reader from microarray technology to statistical problems of specific multivariate data analysis. Written in the highly successful Methods in Molecular BiologyTM series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results in the laboratory. Thorough and intuitive, Statistical Methods for Microarray Data Analysis: Methods and Protocols aids scientists in continuing to study microarrays and the most current statistical methods.

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 : 55,8 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.