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Computational and Statistical Approaches to Genomics

Includes coverage of statistical issues on single nucleotide polymorphism analysis array, CGH analysis, SAGE analysis, gene shaving and related methods for microarray data analysis, and cross-hybridization issues on oligo arrays.

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  • "Computational and Statistical Genomics aims to help researchers deal with current genomic challenges. Topics covered include: overviews of the role of supercomputers in genomics research, the existing challenges and directions in image processing for microarray technology, and web-based tools for microarray data analysis; approaches to the global modeling and analysis of gene regulatory networks and transcriptional control, using methods, theories, and tools from signal processing, machine learning, information theory, and control theory; state-of-the-art tools in Boolean function theory, time-frequency analysis, pattern recognition, and unsupervised learning, applied to cancer classification, identification of biologically active sites, and visualization of gene expression data; crucial issues associated with statistical analysis of microarray data, statistics and stochastic analysis of gene expression levels in a single cell, statistically sound design of microarray studies and experiments; and biological and medical implications of genomics research."
  • "Includes coverage of statistical issues on single nucleotide polymorphism analysis array, CGH analysis, SAGE analysis, gene shaving and related methods for microarray data analysis, and cross-hybridization issues on oligo arrays."@en
  • "Computational and Statistical Approaches to Genomics, 2nd Edition, aims to help researchers deal with current genomic challenges. During the three years after the publication of the first edition of this book, the computational and statistical research in genomics have become increasingly more important and indispensable for understanding cellular behavior under a variety of environmental conditions and for tackling challenging clinical problems. In the first edition, the organizational structure was: data à analysis à synthesis à application. In the second edition, the same structure remains, but the chapters that primarily focused on applications have been deleted. This decision was motivated by several factors. Firstly, the main focus of this book is computational and statistical approaches in genomics research. Thus, the main emphasis is on methods rather than on applications. Secondly, many of the chapters already include numerous examples of applications of the discussed methods to current problems in biology. The range of topics have been broadened to include newly contributed chapters on topics such as alternative splicing, tissue microarray image and data analysis, single nucleotide polymorphisms, serial analysis of gene expression, and gene shaving. Additionally, a number of chapters have been updated or revised. This book is for any researcher, in academia and industry, in biology, computer science, statistics, or engineering involved in genomic problems. It can also be used as an advanced level textbook in a course focusing on genomic signals, information processing, or genome biology."@en

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  • "Llibres electrònics"
  • "Aufsatzsammlung"
  • "Libros electrónicos"
  • "Electronic books"
  • "Electronic books"@en
  • "Livres électroniques"

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  • "Computational and Statistical Approaches to Genomics"
  • "Computational and Statistical Approaches to Genomics"@en
  • "Computational and statistical approaches to genomics"
  • "Computational and statistical approaches to genomics"@en

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