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.
Table of Contents
Equilibrium Statistical Mechanics
Z: The Partition Function
Relation to Thermodynamics
Nonequilibrium Statistical Mechanics
The Master Equation
The Fokker-Planck and Langevin Equations
Sequence Alignment: A Nonequilibrium Phase Transition
Molecules, Code and Representation
DNA and RNA: The Building Blocks
Representing RNA Structure
Thermal Stability of DNA: The Melting Transition
The Melting Profiles of Genomic DNA and cDNA
Computing RNA Secondary Structure: Combinatorics
The RNA Partition Function
RNA Phase Behavior and Folding Kinetics
Bacterial Chemotaxis: Cooperativity Once More
Network Dynamics I: Deterministic
Deterministic Dynamics: ?-Repressor Expression
The Turing Insight
The Min System
Network Dynamics II: Fluctuations
Noise in Signaling
Fluctuating Gene Network Dynamics
Extrinsic vs. Intrinsic Noise
Networks as Graphs
Probability Generating Functions and Network Characteristics
Statistical Mechanics of Networks
"…The book is well written and structured in a way that allows the comprehension of the statistical mechanics approach in biology for readers with different backgrounds. … I recommend this book to researchers who work in statistics, physics and systems biology and want to gain an insight into the mechanical statistical approach for the modelling of physical and chemical properties of biomolecules and their interactions."
—Liliana López Kleine, Universidad Nacional de Colombia, Journal of the Royal Statistical Society, Series A, 2010