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A Practical Approach to Microarray Data Analysis (Hardcover, 2003 ed.): Daniel P. Berrar, Werner Dubitzky, Martin Granzow A Practical Approach to Microarray Data Analysis (Hardcover, 2003 ed.)
Daniel P. Berrar, Werner Dubitzky, Martin Granzow
R1,585 Discovery Miles 15 850 Ships in 10 - 15 working days

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.

Fundamentals of Data Mining in Genomics and Proteomics (Hardcover, 2007 ed.): Werner Dubitzky, Martin Granzow, Daniel P. Berrar Fundamentals of Data Mining in Genomics and Proteomics (Hardcover, 2007 ed.)
Werner Dubitzky, Martin Granzow, Daniel P. Berrar
R3,048 Discovery Miles 30 480 Ships in 10 - 15 working days

This book aims to present state-of-the-art analytical methods from statistics and data mining for the analysis of high-throughput data from genomics and proteomics. Research and development in genomics and proteomics depend on the analysis and interpretation of large amounts of data generated by high-throughput techniques. To exploit data obtained from experimental and observational studies, life scientists need to understand the analytical techniques and methods from statistics and data mining. These techniques are not easily accessible to life scientists working on genomics and proteomics problems, as the available material is presented from a highly mathematical perspective, favoring formal rigor over conceptual clarity and assessment of practical relevance. This book addresses these issues by adopting an approach focusing on concepts and applications.

A Practical Approach to Microarray Data Analysis (Paperback, Softcover reprint of the original 1st ed. 2003): Daniel P. Berrar,... A Practical Approach to Microarray Data Analysis (Paperback, Softcover reprint of the original 1st ed. 2003)
Daniel P. Berrar, Werner Dubitzky, Martin Granzow
R1,549 Discovery Miles 15 490 Ships in 10 - 15 working days

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.

Fundamentals of Data Mining in Genomics and Proteomics (Paperback, Softcover reprint of hardcover 1st ed. 2007): Werner... Fundamentals of Data Mining in Genomics and Proteomics (Paperback, Softcover reprint of hardcover 1st ed. 2007)
Werner Dubitzky, Martin Granzow, Daniel P. Berrar
R2,876 Discovery Miles 28 760 Ships in 10 - 15 working days

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.

A Practical Approach to Microarray Data Analysis (Paperback, 2009 ed.): Daniel P. Berrar, Werner Dubitzky, Martin Granzow A Practical Approach to Microarray Data Analysis (Paperback, 2009 ed.)
Daniel P. Berrar, Werner Dubitzky, Martin Granzow
R1,548 Discovery Miles 15 480 Ships in 10 - 15 working days

The book addresses the requirement of scientists and researchers to gain a basic understanding of microarray analysis methodologies and tools. It is intended for students, teachers, researchers, and research managers who want to understand the state of the art and of the presented methodologies and the areas in which gaps in our knowledge demand further research and development. The book is designed to be used by the practicing professional tasked with the design and analysis of microarray experiments or as a text for a senior undergraduate- or graduate level course in analytical genetics, biology, bioinformatics, computational biology, statistics and data mining, or applied computer science.

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