Computational Biology: A Statistical Mechanics Perspective

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Provides the first detailed application of statistical physics concepts to problems in computational biology Illustrates the concepts with simple applications focused exclusively on biological systems Focuses on the properties of biomolecules, their stability, and the structures that they form Includes a detailed discussion of chromatin and its role in gene regulation, a topic unique among statistical mechanics books Uses statistical mechanics models to describe the dynamics and structure of complex gene and protein networks 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. Subjects of the book : Mathematics Life Sciences Molecular Biology Contents of the book : STATISTICAL MECHANICSEquilibrium Statistical MechanicsZ: The Partition FunctionRelation to ThermodynamicsComputing ZNonequilibrium Statistical MechanicsStochastic ProcessesThe Master EquationFluctuation TheoremsThe Fokker-Planck and Langevin EquationsSequence Alignment: A Nonequilibrium Phase TransitionBIOMOLECULESMolecules, Code and RepresentationDNA and RNA: The Building BlocksRepresenting RNA StructureProteinsDNAThermal Stability of DNA: The Melting TransitionThe Melting Profiles of Genomic DNA and cDNAHybridizing DNARNAComputing RNA Secondary Structure: CombinatoricsThe RNA Partition FunctionRNA Phase Behavior and Folding KineticsProteinsProteins: FoldingProteins: DockingElectrostaticsChromatinBacterial Chemotaxis: Cooperativity Once MoreNETWORKSNetwork Dynamics I: DeterministicDeterministic Dynamics: ?-Repressor ExpressionThe Turing InsightThe Min SystemNetwork Dynamics II: FluctuationsNoise in SignalingStochastic CascadesStochastic FocusingFluctuating Gene Network DynamicsExtrinsic vs. Intrinsic NoiseNetworks: StructureNetworks as GraphsProbability Generating Functions and Network CharacteristicsStatistical Mechanics of NetworksNetwork GrowthINDEX