Statistical Methods For Microarray Data Analysis

DOWNLOAD

Download Statistical Methods For Microarray Data Analysis PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Statistical Methods For Microarray Data Analysis book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page

Statistical Analysis Of Gene Expression Microarray Data

DOWNLOAD
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

Gene Expression Data Analysis

DOWNLOAD
Author : Pankaj Barah
language : en
Publisher: CRC Press
Release Date : 2021-11-08

Gene Expression Data Analysis written by Pankaj Barah and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-08 with Computers categories.

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

Statistics And Data Analysis For Microarrays Using R And Bioconductor

DOWNLOAD
Author : Sorin Draghici
language : en
Publisher: CRC Press
Release Date : 2016-04-19

Statistics And Data Analysis For Microarrays Using R And Bioconductor written by Sorin Draghici and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-19 with Computers categories.

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, example-based approach that teaches students the basics of R and microarray technology as well as how to choose and apply the proper data analysis tool to specific problems. New to the Second EditionCompletely updated and double the size of its predecessor, this timely second edition replaces the commercial software with the open source R and Bioconductor environments. Fourteen new chapters cover such topics as the basic mechanisms of the cell, reliability and reproducibility issues in DNA microarrays, basic statistics and linear models in R, experiment design, multiple comparisons, quality control, data pre-processing and normalization, Gene Ontology analysis, pathway analysis, and machine learning techniques. Methods are illustrated with toy examples and real data and the R code for all routines is available on an accompanying downloadable resource. With all the necessary prerequisites included, this best-selling book guides students from very basic notions to advanced analysis techniques in R and Bioconductor. The first half of the text presents an overview of microarrays and the statistical elements that form the building blocks of any data analysis. The second half introduces the techniques most commonly used in the analysis of microarray data.

Statistical Methods For Microarray Data Analysis

DOWNLOAD
Author : Andrei Y. Yakovlev
language : en
Publisher: Humana Press
Release Date : 2013-02-06

Statistical Methods For Microarray Data Analysis written by Andrei Y. Yakovlev and has been published by Humana Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-02-06 with Medical categories.

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.

Microarray Data Analysis

DOWNLOAD
Author : Giuseppe Agapito
language : en
Publisher: Humana
Release Date : 2022-12-15

Microarray Data Analysis written by Giuseppe Agapito and has been published by Humana this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-15 with Science categories.

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.

Dna Methylation Microarrays

DOWNLOAD
Author : Sun-Chong Wang
language : en
Publisher: CRC Press
Release Date : 2008-04-24

Dna Methylation Microarrays written by Sun-Chong Wang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-24 with Mathematics categories.

Providing an interface between dry-bench bioinformaticians and wet-lab biologists, DNA Methylation Microarrays: Experimental Design and Statistical Analysis presents the statistical methods and tools to analyze high-throughput epigenomic data, in particular, DNA methylation microarray data. Since these microarrays share the same under

Methods Of Microarray Data Analysis Iii

DOWNLOAD
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.

Statistics For Microarrays

DOWNLOAD
Author : Ernst Wit
language : en
Publisher: John Wiley & Sons
Release Date : 2004-11-19

Statistics For Microarrays written by Ernst Wit 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 2004-11-19 with Mathematics categories.

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.

Microarray Gene Expression Data Analysis

DOWNLOAD
Author : Helen Causton
language : en
Publisher: Wiley-Blackwell
Release Date : 2003-04-18

Microarray Gene Expression Data Analysis written by Helen Causton and has been published by Wiley-Blackwell this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-04-18 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

Methods Of Microarray Data Analysis

DOWNLOAD
Author : Simon M. Lin
language : en
Publisher: Springer Science & Business Media
Release Date : 2002

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 2002 with Mathematics categories.

Papers from CAMDA 2000, December 18-19, 2000, Duke University, Durham, NC, USA