The following books are those I think I should read or re-read and would like to recommend to new graduates interested in computational biophysics/biochemistry, especially molecular simulations.
Statistical Mechanics, by Donald A. McQuarrie.
Statistical Mechanics, Entropy, Order Parameters, and Complexity, by James P. Sethna. [PDF]
Statistical Mechanics, by R. K. Pathria & Paul D. Beale.
Nonequilibrium Statistical Mechanics, by Robert Zwanzig.
Theoretical Concepts in Physics: An Alternative View of Theoretical Reasoning in Physics, by Malcolm S. Longair.
统计物理学 (in Chinese), by 苏汝铿.
热力学与统计物理 (in Chinese), by 汪志诚.
热力学与统计物理 (in Chinese), by 周子舫 & 曹烈兆.
Theory of Simple Liquids with Applications to Soft Matter, by Jean-Pierre Hansen and Ian R. McDonald.
Capillarity and Wetting Phenomena by Pierre-Gilles de Gennes et al.
Soft Mater Physics, by Maso Doi.
Molecular Driving Forces, by Ken A. Dill and Sarina Bromberg.
Statistical Physics of Biomolecules, by Daneil M. Zuckerman.
Protein Physics, by Alexei V. Finkelstein and Oleg B. Ptitsyn.
The Theory of Intermolecular Forces, by Anthony Stone.
Intermolecular and Surface Forces, by Jacob N. Israelachvili.
Polymer Physics, by Micheal Rubinstein and Ralph H. Colby.
Polymer Chemistry, by Paul C. Hiemenz and Timothy P. Lodge.
Scaling Concepts in Polymer Physics, by Pierre-Gilles de Gennes.
Physical Chemistry: Thermodynamic, Structure and Change, by Peter Atkins and Julio de Paula.
Modern Quantum Chemistry: Introduction to Advanced Electronic Structure Theory, by Attila Szabo and Neil S. Ostlund.
Molecular Orbitals and Organic Chemical Reactions, by Ian Fleming.
MD & MC:
Computer Simulations of Liquids, by Michael P. Allen & Dominic J. Tildesley.
Understanding Molecular Simulation: From Algorithms to Applications, by Berend Smit and Daan Frenkel.
A Guide to Monte Carlo Simulations in Statistical Physics, by David P. Landau and Kurt Binder.
Free Energy Calculations: Theory and Applications in Chemistry and Biology, Editors: Ch. Chipot and A. Pohorille.
Markov State Models:
An Introduction to Markov State Models and Their Application to Long Timescale Molecular Simulation, Editors: Gregory R. Bowman, Vijay S. Pande and Frank Noé.
Molecular Biology of the Cell, by Alberts, Johnson, Lewis, Morgan Raff, Boberts and Walter.
Cell Biology by Pollard, Earnshaw, Lippincott-Schwartz and Johnson.
Pricinples of Biochemistry, by David L. Nelson and Michael M. Cox.
Algorithms in C, by Robert Sedgewick.
Gaussian Processes for Machine Learning, by Carl Edward Rasmussen & Christopher K. I. Williams.
统计学习方法 (in Chinese), by 李航.
机器学习 (in Chinese), by 周志华.
C 语言点滴(in Chinese), by 赵岩.
Virial Expansion – A Brief Introduction, by Frank Schreiber, Fabio Zanini & Felix Roosen-Runge.
[To be updated]