**Best Reference Books on Modeling of Biological Systems**, which are used by students of top universities, and colleges. This will help you choose the right book depending on if you are a beginner or an expert. Here is the complete list of

**Modeling of Biological Systems Books**with their authors, publishers, and an unbiased review of them as well as links to the Amazon website to directly purchase them. If permissible, you can also download the free PDF books on Modeling of Biological Systems below.

1."Computational Modeling of Biological Systems: From Molecules to Pathways (Biological and Medical Physics, Biomedical Engineering)" by Nikolay V Dokholyan
“Computational Modeling of Biological Systems: From Molecules to Pathways (Biological and Medical Physics, Biomedical Engineering)” Book Review: This book is a valuable resource for those interested in biological and medical physics, biomedical engineering and related fields. The book provides a comprehensive overview of the latest computational modeling techniques used to understand biological systems, from the molecular level to complex pathways. The book is well-organized and clearly written, making it accessible to both experts and those new to the field. It also includes numerous examples and case studies to illustrate the concepts discussed.
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2."Modeling Biological Systems:: Principles and Applications" by James W Haefner | |

3."Mathematical Modeling of Biological Systems, Volume I" by Andreas Deutsch and Lutz Brusch
“Mathematical Modeling of Biological Systems, Volume I” Book Review: This book is aimed at advanced students, researchers, and practitioners in the rapidly growing field of mathematical modeling in the biological sciences. It covers various topics such as cellular biophysics, regulatory networks, developmental biology, biomedical applications, data analysis, and model validation. The book’s interdisciplinary approach is ideal for those interested in the intersection of applied mathematics, experimental biology and medicine, computational biology, biochemistry, computer science, and physics.
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4."Mathematical Modeling of Biological Systems, Volume II" by Andreas Deutsch and Rafael Bravo de la Parra
“Mathematical Modeling of Biological Systems, Volume II” Book Review: This book is a valuable resource for researchers, professionals, and students in the interdisciplinary field of applied mathematics, computational biology, biochemistry, and medicine. The book provides a comprehensive guide to the mathematical modeling of complex biological systems, including cellular biophysics, gene regulatory networks, metabolic pathways, neural networks, and epidemiology. The authors use a range of mathematical and computational tools to develop and validate models that can be applied to real-world problems in the life sciences. This second volume includes updated and expanded coverage of topics such as cancer modeling, systems biology, and multi-scale modeling.
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5."Modeling Dynamic Biological Systems (Modeling Dynamic Systems)" by Bruce Hannon and Matthias Ruth
“Modeling Dynamic Biological Systems (Modeling Dynamic Systems)” Book Review: The book provides a thorough introduction to mathematical modeling and its applications in biological systems, ranging from single-cell models to population dynamics. The authors emphasize the importance of dynamical systems theory in understanding biological phenomena and provide numerous examples and exercises to help readers develop their modeling skills. This book is a must-read for anyone interested in applying mathematical modeling to study biological systems.
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6."Dynamics of Complex Interconnected Biological Systems (Mathematical Modeling)" by Vincent and Leslie Jennings
“Dynamics of Complex Interconnected Biological Systems (Mathematical Modeling)” Book Review: The book focuses on mathematical modeling to help researchers understand the behavior of interconnected biological systems. The authors provide an overview of basic principles of modeling and simulation, as well as practical applications of these concepts. They address topics such as biochemical networks, gene regulation, signaling pathways, and the immune system. The book also covers more complex systems, including multicellular organisms and ecosystems. This resource is an essential guide for advanced students, researchers, and practitioners in the field of mathematical modeling in biological systems.
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7."Dynamical Systems for Biological Modeling: An Introduction (Advances in Applied Mathematics)" by Fred Brauer and Christopher Kribs
“Dynamical Systems for Biological Modeling: An Introduction (Advances in Applied Mathematics)” Book Review: The book is designed for students of biology and mathematics, focusing on several biological modeling topics such as population biology, epidemiology, immunology, intraspecies competition, harvesting, predator-prey systems, and structured populations. The chapters include solved problems, exercises, and examples with additional problems that delve deeper into mathematical analysis and the development of mathematical models for biological problems. The book aims to encourage a better understanding and enthusiasm for mathematics in biology.
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8."Structuring Biological Systems: A Computer Modeling Approach (Neurocomputing for Modeling Complex Biological Systems Series)" by S Sitharama Iyengar
“Structuring Biological Systems: A Computer Modeling Approach (Neurocomputing for Modeling Complex Biological Systems Series)” Book Review: The book is aimed at students, researchers, and professionals in the fields of biology, chemistry, engineering, research medicine, and computer science. It focuses on key components of biological systems and develops genetic algorithms for modeling purposes. The book approaches biological systems from an artificial intelligence perspective, providing modeling examples of complex systems such as molecular modeling, renal hemodynamics, and cognitive modeling. It describes the use of entropy-based probability distribution for modeling environmental and biological systems, and offers a detailed analysis of modeling cancer phenomena.
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9."Introduction to Modeling Biological Cellular Control Systems" by Weijiu Liu
“Introduction to Modeling Biological Cellular Control Systems” Book Review: This book explains the concepts of modeling, simulation, analysis, and applications in biological cellular control systems. It describes how to derive an enzyme kinetic model using the law of mass balance and the law of mass action, and how to model an ionic channel or pump using a current-voltage relation, Nernst potential equilibrium equation, and Hodgkin and Huxley’s models. The book also covers how to integrate these models into a complete feedback control system, how to estimate parameters using data, and how to solve models numerically using MATLAB. Additionally, it discusses computer simulations and provides model predictions. This book is suitable for students, researchers, and professionals in the field of biology and biotechnology.
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10."Low–Frequency Electromagnetic Modeling for Electrical and Biological Systems Using MATLAB" by Sergey N Makarov and Gregory M Noetscher
“Low–Frequency Electromagnetic Modeling for Electrical and Biological Systems Using MATLAB” Book Review: The book provides a comprehensive guide to low-frequency electromagnetic modeling using MATLAB. It covers the basics of electromagnetic theory, such as Maxwell’s equations, and explains how to use MATLAB to solve practical problems in electrical and biological systems. The authors also introduce numerical methods for solving partial differential equations and demonstrate how to apply them to simulate electromagnetic fields. This book is useful for students and researchers interested in modeling electromagnetic systems using MATLAB.
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11."Charge Transfer Complexes in Biological Systems" by Felix Gutmann and C Johnson
“Charge Transfer Complexes in Biological Systems” Book Review: This book provides a theoretical foundation for the physics and chemistry of charge transfer complex formation, with a particular focus on the role of excited states. It explores drug interactions and the interactions between different types of antibiotics and outlines methods for synthesizing pharmaceutical products with reduced side effects. Additionally, it investigates the role of partial charge transfer in biological systems.
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