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.
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.
Includes comprehensive summary of quantum mechanical molecular dynamics and computational techniques related to it Provides pedagogical tutorials and sample algorithms for performing simulations and analyzing the data Targets broad range of fields from biophysics to material science
Hiqmet Kamberaj
Quantum Mechanics Simulations Coarse-Grained Models Semi-Empirical Models Software Trends Molecular Dynamics Molecular Mechanics Molecular Orbitals Machine Learning Laboratory Case Studies Slater-type Orbitals