
This book is the first to focus on the application of mathematical networks for analyzing microarray data. This method goes well beyond the standard clustering methods traditionally used. From the contents: * Understanding and Preprocessing Microarray Data * Clustering of Microarray Data *
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Mathematical problems such as graph theory problems are of increasing importance for the analysis of modelling data in biomedical research such as in systems biology, neuronal network modelling etc. This book follows a new approach of including graph theory from a mathematical perspective with
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Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph
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This comprehensive introduction to computational network theory as a branch of network theory builds on the understanding that such networks are a tool to derive or verify hypotheses by applying computational techniques to large scale network data. The highly experienced team of editors and
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Written for biologists and medical researchers who don't have any special training in data analysis and statistics, Guide to Analysis of DNA Microarray Data, Second Edition begins where DNA array equipment leaves off: the image produced by the microarray. The text deals with the questions that
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A collection of highly valuable statistical and computational approaches designed for developing powerful methods to analyze large-scale high-throughput data derived from studies of complex diseases. Such diseases include cancer and cardiovascular disease, and constitute the major health challenges
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A great introductory book that details reliable approaches to problems met in standard microarray data analyses. It provides examples of established approaches such as cluster analysis, function prediction, and principle component analysis. Discover real examples to illustrate the key concepts of
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This ready reference discusses different methods for statistically analyzing and validating data created with high-throughput methods. As opposed to other titles, this book focusses on systems approaches, meaning that no single gene or protein forms the basis of the analysis but rather a more or
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Praise for the First Edition “…extremely well written…a comprehensive and up-to-date overview of this important field.” – Journal of Environmental Quality Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition provides comprehensive coverage of recent
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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
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Microarray technology provides researchers in the life sciences with a revolutionary tool for measuring gene expression. However, this highly developed process involves multiple steps, from sample selection to data analysis, each susceptible to potentially costly errors. Without sound quality
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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
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