Computational Biology: A Statistical Mechanics Perspective, Second Edition (Chapman & Hall/CRC Computational Biology Series)

✍ Scribed by Ralf Blossey

• Publisher: CRC Press
• Year: 2019
• Tongue: English
• Leaves: 301
• Series: Chapman & Hall/CRC Computational Biology Series
• Edition: 2
• Category: Library

✦ Synopsis

Computational biology has developed rapidly during the last two decades following the genomic revolution which culminated in the sequencing of the human genome. More than ever it has developed into a field which embraces computational methods from different branches of the exact sciences: pure and applied mathematics, computer science, theoretical physics. This Second Edition provides a solid introduction to the techniques of statistical mechanics for graduate students and researchers in computational biology and biophysics.

• Material has been reorganized to clarify equilbrium and nonequilibrium aspects of biomolecular systems
• Content has been expanded, in particular in the treatment of the electrostatic interactions of biomolecules and the application of non-equilibrium statistical mechanics to biomolecules
• New network-based approaches for the study of proteins are presented.

All treated topics are put firmly in the context of the current research literature, allowing the reader to easily follow an individual path into a specific research field. Exercises and Tasks accompany the presentations of the topics with the intention of enabling the readers to test their comprehension of the developed basic concepts.

 

✦ Table of Contents

Cover
Half Title
Series Page
Title Page
Copyright Page
Dedication
Contents
Preface to the Second Edition
Preface to the First Edition
Part I: Equilibrium Statistical Mechanics
Chapter 1: Equilibrium Statistical Mechanics
1.1 Z: THE PARTITION FUNCTION
1.2 RELATION TO THERMODYNAMICS
1.3 COMPUTING Z
1.4 THE ISING MODEL
Chapter 2: Biomolecular Structure: DNA, RNA, Proteins
2.1 DNA, RNA AND PROTEINS: THE BUILDING BLOCKS
2.2 REPRESENTING RNA STRUCTURE
2.3 COMPUTING RNA SECONDARY STRUCTURE: COMBINATORICS
2.4 THE RNA PARTITION FUNCTION
2.5 PROTEIN FOLDING AND DOCKING
2.6 PULLING DNA
Chapter 3: Phase Transitions in RNA and DNA
3.1 RNA PHASE BEHAVIOUR
3.2 THE DNA MELTING TRANSITION
3.3 THE MELTING PROFILES OF GENOMIC DNA AND CDNA
Chapter 4: Soft Matter Electrostatics
4.1 THE FREE ENERGY OF ELECTROSTATIC SYSTEMS
4.2 THE POISSON-BOLTZMANN EQUATION
4.3 PROTEIN ELECTROSTATICS
4.4 CHROMATIN ELECTROSTATICS
Part II: Non-equilibrium Statistical Mechanics
Chapter 5: Back to P: Probabilities over Time
5.1 STOCHASTIC PROCESSES
5.2 THE MASTER EQUATION
5.3 THE FOKKER-PLANCK AND LANGEVIN EQUATIONS
5.4 SEQUENCE ALIGNMENT: A NON-EQUILIBRIUM PHASE TRANSITION
Chapter 6: Fluctuation Theorems
6.1 THE FLUCTUATION-DISSIPATION THEOREM
6.2 THE JARZYNSKI EQUALITY AND CROOKS' THEOREM
6.3 APPLICATIONS OF THE FLUCTUATION THEOREMS
Chapter 7: Dynamics of Biological Networks
7.1 THE λ-REPRESSOR
7.2 DYNAMICS OF GENE REGULATORY NETWORKS
7.3 INTRINSIC NOISE
Chapter 8: Biological Networks: Space
8.1 EXTRINSIC VS. INTRINSIC NOISE
8.2 THE TURING INSIGHT
8.3 NETWORKS AS GRAPHS
8.4 STATISTICAL MECHANICS OF NETWORKS
8.5 SMALL WORLDS
Index