304 pages | 71 B/W Illus.
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.
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.
Part 1: Equilibrium Statistical Physics
Chapter 1. Equilbrim Statistical Mechanics
Chapter 2. Biomolecular Structure: DNA, RNA, Proteins
Chapter 3. Phase Transitions in RNA
Chapter 4. Soft Matter Electrostatics
Part 2. Nonequilibrium Statistical Mechanics
Chapter 5. Back to P: Probabilities Over Time
Chapter 6. Fluctuation Theorems
Chapter 7. Dynamics of Biological Networks
Chapter 8. Biological Networks: Space