Computational Biology

Computational Biology : A Statistical Mechanics Perspective

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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 more

Product details

  • Hardback | 276 pages
  • 157.5 x 236.2 x 20.3mm | 476.28g
  • Taylor & Francis Ltd
  • Chapman & Hall/CRC
  • Boca Raton, FL, United States
  • English
  • 60 black & white illustrations, 8 colour illustrations, 4 black & white tables
  • 1584885564
  • 9781584885566
  • 2,412,998

Table of contents

STATISTICAL MECHANICS Equilibrium Statistical Mechanics Z: The Partition Function Relation to Thermodynamics Computing Z Nonequilibrium Statistical Mechanics Stochastic Processes The Master Equation Fluctuation Theorems The Fokker-Planck and Langevin Equations Sequence Alignment: A Nonequilibrium Phase Transition BIOMOLECULES Molecules, Code and Representation DNA and RNA: The Building Blocks Representing RNA Structure Proteins DNA Thermal Stability of DNA: The Melting Transition The Melting Profiles of Genomic DNA and cDNA Hybridizing DNA RNA Computing RNA Secondary Structure: Combinatorics The RNA Partition Function RNA Phase Behavior and Folding Kinetics Proteins Proteins: Folding Proteins: Docking Electrostatics Chromatin Bacterial Chemotaxis: Cooperativity Once More NETWORKS Network Dynamics I: Deterministic Deterministic Dynamics: ?-Repressor Expression The Turing Insight The Min System Network Dynamics II: Fluctuations Noise in Signaling Stochastic Cascades Stochastic Focusing Fluctuating Gene Network Dynamics Extrinsic vs. Intrinsic Noise Networks: Structure Networks as Graphs Probability Generating Functions and Network Characteristics Statistical Mechanics of Networks Network Growth INDEXshow more

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