Series:

Scientific Computation

2 total works

Cover of Molecular Dynamics Simulations in Statistical Physics: Theory and Applications

This book presents computer simulations using molecular dynamics techniques in statistical physics, with a focus on macromolecular systems. The numerical methods are introduced in the form of computer algorithms and can be implemented in computers using any desired computer programming language, such as Fortran 90, C/C++, and others. The book also explains how some of these numerical methods and their algorithms can be implemented in the existing computer programming software of macromolecular systems, such as the CHARMM program.

In addition, it examines a number of advanced concepts of computer simulation techniques used in statistical physics as well as biological and physical systems. Discussing the molecular dynamics approach in detail to enhance readers understanding of the use of this method in statistical physics problems, it also describes the equations of motion in various statistical ensembles to mimic real-world experimental conditions.

Intended for graduate students and research scientists working in the field of theoretical and computational biophysics, physics and chemistry, the book can also be used by postgraduate students of other disciplines, such as applied mathematics, computer sciences, and bioinformatics. Further, offering insights into fundamental theory, it as a valuable resource for expert practitioners and programmers and those new to the field.



Cover of Computer Simulations in Molecular Biology
This book covers a range of topics in quantum mechanics and molecular dynamics simulation, including computational modeling and machine learning approaches. The book also provides a Python GUI and tutorials for simulating molecular biological systems and presents case studies of quantum mechanics simulations for predicting electronic properties. Its pedagogical formatting makes it easy for students to understand and follow and has been praised for providing clear and detailed explanations of complex topics. This book is ideal for graduate students and researchers in theoretical and computational biophysics, physics, chemistry, and materials science, as well as postgraduates in applied mathematics, computer science, and bioinformatics.