Methods Of Microarray Data Analysis Iv
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Methods Of Microarray Data Analysis Iv
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Author : Jennifer S. Shoemaker
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-01-16
Methods Of Microarray Data Analysis Iv written by Jennifer S. Shoemaker 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 2006-01-16 with Medical categories.
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 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.
Methods Of Microarray Data Analysis Iv
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Author : Jennifer S. Shoemaker
language : en
Publisher: Springer Science & Business Media
Release Date : 2004-10-29
Methods Of Microarray Data Analysis Iv written by Jennifer S. Shoemaker 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 2004-10-29 with Medical categories.
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.
Microarray Data Analysis
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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.
A Practical Approach To Microarray Data Analysis
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Author : Daniel P. Berrar
language : en
Publisher: Springer Science & Business Media
Release Date : 2002-12-31
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 2002-12-31 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.
Resampling Based Multiple Testing
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Author : Peter H. Westfall
language : en
Publisher: John Wiley & Sons
Release Date : 1993-01-12
Resampling Based Multiple Testing written by Peter H. Westfall 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 1993-01-12 with Mathematics categories.
Combines recent developments in resampling technology (including the bootstrap) with new methods for multiple testing that are easy to use, convenient to report and widely applicable. Software from SAS Institute is available to execute many of the methods and programming is straightforward for other applications. Explains how to summarize results using adjusted p-values which do not necessitate cumbersome table look-ups. Demonstrates how to incorporate logical constraints among hypotheses, further improving power.
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
Statistics And Data Analysis For Microarrays Using R And Bioconductor
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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.
Gene Expression Data Analysis
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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
Fundamentals Of Data Mining In Genomics And Proteomics
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Author : Werner Dubitzky
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-04-13
Fundamentals Of Data Mining In Genomics And Proteomics written by Werner Dubitzky 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 2007-04-13 with Science categories.
This book presents state-of-the-art analytical methods from statistics and data mining for the analysis of high-throughput data from genomics and proteomics. It adopts an approach focusing on concepts and applications and presents key analytical techniques for the analysis of genomics and proteomics data by detailing their underlying principles, merits and limitations.