Computational Modeling And Simulations Of Biomolecular Systems
This textbook originated from the course 'Simulation, Modeling, and Computations in Biophysics' that I have taught at the University of Chicago since 2011. The students typically came from a wide range of backgrounds, including biology, physics, chemistry, biochemistry, and mathematics, and the course was intentionally adapted for senior undergraduate students and graduate students. This is not a highly technical book dedicated to specialists. The objective is to provide a broad survey from the physical description of a complex molecular system at the most fundamental level, to the type of phenomenological models commonly used to represent the function of large biological macromolecular machines.The key conceptual elements serving as building blocks in the formulation of different levels of approximations are introduced along the way, aiming to clarify as much as possible how they are interrelated. The only assumption is a basic familiarity with simple mathematics (calculus and integrals, ordinary differential equations, matrix linear algebra, and Fourier-Laplace transforms).
1140144912
Computational Modeling And Simulations Of Biomolecular Systems
This textbook originated from the course 'Simulation, Modeling, and Computations in Biophysics' that I have taught at the University of Chicago since 2011. The students typically came from a wide range of backgrounds, including biology, physics, chemistry, biochemistry, and mathematics, and the course was intentionally adapted for senior undergraduate students and graduate students. This is not a highly technical book dedicated to specialists. The objective is to provide a broad survey from the physical description of a complex molecular system at the most fundamental level, to the type of phenomenological models commonly used to represent the function of large biological macromolecular machines.The key conceptual elements serving as building blocks in the formulation of different levels of approximations are introduced along the way, aiming to clarify as much as possible how they are interrelated. The only assumption is a basic familiarity with simple mathematics (calculus and integrals, ordinary differential equations, matrix linear algebra, and Fourier-Laplace transforms).
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Computational Modeling And Simulations Of Biomolecular Systems

Computational Modeling And Simulations Of Biomolecular Systems

by Benoit Roux
Computational Modeling And Simulations Of Biomolecular Systems

Computational Modeling And Simulations Of Biomolecular Systems

by Benoit Roux

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Overview

This textbook originated from the course 'Simulation, Modeling, and Computations in Biophysics' that I have taught at the University of Chicago since 2011. The students typically came from a wide range of backgrounds, including biology, physics, chemistry, biochemistry, and mathematics, and the course was intentionally adapted for senior undergraduate students and graduate students. This is not a highly technical book dedicated to specialists. The objective is to provide a broad survey from the physical description of a complex molecular system at the most fundamental level, to the type of phenomenological models commonly used to represent the function of large biological macromolecular machines.The key conceptual elements serving as building blocks in the formulation of different levels of approximations are introduced along the way, aiming to clarify as much as possible how they are interrelated. The only assumption is a basic familiarity with simple mathematics (calculus and integrals, ordinary differential equations, matrix linear algebra, and Fourier-Laplace transforms).

Product Details

ISBN-13: 9789811232756
Publisher: World Scientific Publishing Company, Incorporated
Publication date: 09/14/2021
Pages: 208
Product dimensions: 6.00(w) x 9.00(h) x 0.50(d)

Table of Contents

Preface vii

Acknowledgments ix

Chapter 1 Representation of molecular systems 1

Chapter 2 Equilibrium statistical mechanics 15

Chapter 3 Solvation free energy 27

Chapter 4 Implicit solvent and continuum models 39

Chapter 5 Binding equilibrium 55

Chapter 6 Dynamics and time correlation functions 67

Chapter 7 Effective dynamics of reduced models 87

Chapter 8 Diffusion and time evolution of probability distribution 107

Chapter 9 Transition rates 117

Chapter 10 Dynamics of discrete state models 133

Chapter 11 Stochastic simulations 147

Chapter 12 Molecular machines 167

Bibliography 185

Further reading 193

Index 195

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