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portada Computational Biology: A Statistical Mechanics Perspective (Chapman & Hall
Type
Physical Book
Publisher
Language
English
Pages
276
Format
Paperback
ISBN13
9780367390822
Edition No.
1

Computational Biology: A Statistical Mechanics Perspective (Chapman & Hall

Ralf Blossey (Author) · Crc Pr Inc · Paperback

Computational Biology: A Statistical Mechanics Perspective (Chapman & Hall - Ralf Blossey

Physical Book

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Synopsis "Computational Biology: A Statistical Mechanics Perspective (Chapman & Hall"

Quantitative methods have a particular knack for improving any field they touch. For biology, computational techniques have led to enormous strides in our understanding of biological systems, but there is still vast territory to cover. Statistical physics especially holds great potential for elucidating the structural-functional relationships in biomolecules, as well as their static and dynamic properties. Breaking New GroundComputational Biology: A Statistical Mechanics Perspective is the first book dedicated to the interface between statistical physics and bioinformatics. Introducing both equilibrium and nonequilibrium statistical mechanics in a manner tailored to computational biologists, the author applies these methods to understand and model the properties of various biomolecules and biological networks at the systems level. Unique Vision, Novel ApproachBlossey combines his enthusiasm for uniting the fields of physics and computational biology with his considerable experience, knowledge, and gift for teaching. He uses numerous examples and tasks to illustrate and test understanding of the concepts, and he supplies a detailed keyword list for easy navigation and comprehension. His approach takes full advantage of the latest tools in statistical physics and computer science to build a strong set of tools for confronting new challenges in computational biology. Making the concepts crystal clear without sacrificing mathematical rigor, Computational Biology: A Statistical Mechanics Perspective is the perfect tool to broaden your skills in computational biology.

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