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.
Ilya Shmulevich & Wei Zhang
Computational and Statistical Approaches to Genomics [PDF ebook]
Computational and Statistical Approaches to Genomics [PDF ebook]
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Language English ● Format PDF ● ISBN 9780306478253 ● Editor Ilya Shmulevich & Wei Zhang ● Publisher Springer US ● Published 2007 ● Downloadable 3 times ● Currency EUR ● ID 4658331 ● Copy protection Adobe DRM
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