Computational Biology: A Statistical Mechanics Perspective, 1st Edition (Hardback) book cover

Computational Biology

A Statistical Mechanics Perspective, 1st Edition

By Ralf Blossey, Ralf Blossey

Chapman and Hall/CRC

276 pages | 8 Color Illus. | 60 B/W Illus.

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pub: 2006-05-25
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Description

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.

Reviews

"…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

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

INDEX

About the Series

Chapman & Hall/CRC Mathematical and Computational Biology

Learn more…

Subject Categories

BISAC Subject Codes/Headings:
MAT003000
MATHEMATICS / Applied
SCI010000
SCIENCE / Biotechnology
SCI055000
SCIENCE / Physics