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Many biological systems and objects are intrinsically fuzzy as their properties and behaviors contain randomness or uncertainty. This book addresses several important bioinformatics topics using fuzzy concepts and approaches, including measurement of ontological similarity, protein structure prediction/analysis, and microarray data analysis.
Presents the important skills for those who want to do quantitative analysis on biological data, especially for high-throughput omics data. This book covers: essential knowledge and skills necessary to use a Linux computer; write programs in Perl, and the use of BioPerl to write bioinformatics Perl programs; and write programs in R.
Includes a collection of chapters on prokaryotic genomes, their organization and evolution, the information they encode, and the computational approaches needed to derive such information. This book presents a comparative view of bacterial and archaeal genomes, and how information is encoded differently in them.
This book demonstrates the power of mathematical thinking in understanding the biological complexity that exists within the brain. It looks at the latest research on modelling of biochemical pathways within synapses, and provides a clear background for the study of mathematical models related to systems biology. Discussion then focusses on developments in computational models based on networks linked to synaptic plasticity. The models are used to understand memory formation and impairment and they provide a mathematical basis for memory research.Computational Systems Biology of Synaptic Plasticity is a valuable source of knowledge to postgraduate students and researchers in computational systems biology, and as a reference book for various techniques that are needed in modelling biological processes.
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