Devoted to the interface between statistical physics and bioinformatics, Computational Biology: A Statistical Mechanics Perspective focuses on how knowledge of physical properties of biological systems can be used to derive biologically relevant information. The book offers a concise introduction to physical mechanisms underlying biological functions on molecular and system levels. It integrates knowledge and tools from statistical physics and computer science to provide mathematical tools for meeting challenges in computational biology. With summaries of biological information, this is ideal for students, researchers, and practitioners in bioinformatics and computational biology.
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 Ground
Computational 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 Approach
Blossey 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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