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Methods of Microarray Data Analysis III

2007-05-08 Science
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Release : 2007-05-08
Genre : Science
Kind : eBook
Book Rating : 548/5 ( reviews)

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Book Synopsis Methods of Microarray Data Analysis III by : Kimberly F. Johnson

Download or read book Methods of Microarray Data Analysis III written by Kimberly F. Johnson. This book was released on 2007-05-08. Available in PDF, EPUB and Kindle. Book excerpt: 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.

A Practical Approach to Microarray Data Analysis

2007-05-08 Science
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Release : 2007-05-08
Genre : Science
Kind : eBook
Book Rating : 153/5 ( reviews)

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Book Synopsis A Practical Approach to Microarray Data Analysis by : Daniel P. Berrar

Download or read book A Practical Approach to Microarray Data Analysis written by Daniel P. Berrar. This book was released on 2007-05-08. Available in PDF, EPUB and Kindle. Book excerpt: 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

2003-03-26 Mathematics
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Release : 2003-03-26
Genre : Mathematics
Kind : eBook
Book Rating : 236/5 ( reviews)

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Book Synopsis Statistical Analysis of Gene Expression Microarray Data by : Terry Speed

Download or read book Statistical Analysis of Gene Expression Microarray Data written by Terry Speed. This book was released on 2003-03-26. Available in PDF, EPUB and Kindle. Book excerpt: 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 Analysis

2008-02-03 Science
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Release : 2008-02-03
Genre : Science
Kind : eBook
Book Rating : 900/5 ( reviews)

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Book Synopsis Microarray Data Analysis by : Michael J. Korenberg

Download or read book Microarray Data Analysis written by Michael J. Korenberg. This book was released on 2008-02-03. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Methods of Microarray Data Analysis IV

2006-01-16 Medical
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Release : 2006-01-16
Genre : Medical
Kind : eBook
Book Rating : 777/5 ( reviews)

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Book Synopsis Methods of Microarray Data Analysis IV by : Jennifer S. Shoemaker

Download or read book Methods of Microarray Data Analysis IV written by Jennifer S. Shoemaker. This book was released on 2006-01-16. Available in PDF, EPUB and Kindle. Book excerpt: 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.

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