20 Best Books on Biomathematics

“Advanced Engineering Mathematics” Book Review: This book delves into the core of advanced mathematics, specifically Calculus, and covers an extensive range of topics including Ordinary Differential Equations (ODEs), Linear Algebra, Vector Calculus, Fourier Analysis, Partial Differential Equations (PDEs), Complex Analysis, Numeric Analysis, Optimization, Graphs, Probability, and Statistics. The author explains the concepts using straightforward examples, and offers practice problems for readers to test their understanding. Additionally, the book provides a brief review of fundamental calculus concepts, allowing readers to refresh their knowledge before delving into more complex material.

“An Invitation to Biomathematics” Book Review: This textbook presents a thorough introduction to mathematical biology in a clear and accessible style. The material is organized into two parts: the first covers fundamental principles including topics such as population growth, predator-prey interactions, epidemic models, and population genetics. The second part focuses on applying these principles to contemporary biomedical research, and provides guidance on constructing mathematical models using data sets or dynamical processes. The book includes real-life examples from the life sciences and biomedical research, as well as illustrative materials to aid understanding.

“Calculus For Biology and Medicine” Book Review: The focus of this textbook is to teach calculus to students with a biological background. The book introduces mathematical concepts through biological examples and aims to cover the topics in a neutral manner. It provides numerous practical examples, solved problems, and word problems to connect mathematical concepts to biological applications. The book covers various topics, including discrete time models, sequences and difference equations, limits and continuity, differentiation and its applications, integration techniques and computational methods, differential equations, linear algebra and analytic geometry, multivariable calculus, systems of differential equations, and probability and statistics.

“Mathematical biology (Biomathematics)” Book Review: This textbook emphasizes the practical application of mathematical modeling in the biomedical sciences, using mathematical principles to address biological problems. It covers topics such as population biology, reaction kinetics, biological oscillators and switches, the Belousov-Zhabotinskii reaction, reaction-diffusion theory, biological wave phenomena, central pattern generators, neural models, epidemic spread, mechanochemical theory of biological pattern formation, and their significance in evolution. The book provides mathematical analyses of models based on real biological problems and includes exercises to enhance understanding of the material.

“Seven Equations of Life: The Fundamental Relationships of Biomathematics” Book Review: This textbook explores the key mathematical relationships that govern the properties of living systems, examining complex systems through recurring patterns such as nonlinearity, iteration, self-similarity, feedback, autocatalysis, and hierarchical organization. It emphasizes the study of seven fundamental equations to reveal insights into the emergent properties of complex biological systems, aiming to alleviate intimidation towards biomathematics by illustrating the relationships between matter, energy, and information for a better understanding of life sciences complexities.

“Molecular Evolution (Biomathematics)” Book Review: This textbook explores the origin and evolution of self-reproducing systems of macromolecules, as well as large-scale nucleotide sequencing using computational techniques. It discusses the evolution of molecular genetic regulatory systems, providing extensive coverage of fundamental problems in molecular biology, evolution, molecular genetic organization, macromolecule structure and function, and more. Through these discussions, the book aims to develop a unified theory and covers a range of theoretical results and computational methods.

“Biomathematics: Mathematics of Biostructures and Biodynamics” Book Review: This textbook explores new mathematical concepts for cellular and molecular structures and dynamic processes, including the shapes of cells and organelles in plants and animals, and changes in the shape associated with different life processes. The book offers a geometrical description of cellular and molecular shapes that is relevant to biology, covering topics such as Nodal Surfaces, Planes, Rods and Transformation, Motion in Biology, Cubic Cell Membrane Systems, Cells, and their Divisions, RNA, and DNA Modeling, among others. The book comprises fifteen chapters in total.

“Origin and Mineralogy of Clays: Clays and the Environment (Biomathematics)” Book Review: This textbook offers a comprehensive examination of clays in the environment, drawing on the expertise of five authors to explore the diverse concepts and areas surrounding the study of clays, from soils to sediments. The book is structured into seven chapters, covering topics such as Hydrothermal Alteration by Veins, Compaction and Diagenesis, Erosion, Sedimentation and Sedimentary Origin of Clays, Origin of Clays by Rock Weathering and Soil Formation, Composition and Mineralogy of Clay Minerals, among others. Each chapter includes a reference list for further reading.

“Biomathematics: An Introduction” Book Review: This textbook provides an introduction to fundamental mathematical concepts for those in the biological sciences, using biological examples to illustrate key concepts. The book covers a range of topics, including O level mathematics, induction, algorithms, exponential and binomial expansion, differentiation, algebra, and integral calculus.

“Community Food Webs: Data and Theory (Biomathematics)” Book Review: This book explores the intricacies of food webs, including organisms and their habitats, as well as empirical regularities. It proposes new theories and empirical data to explain these regularities. The book demonstrates how community food webs conform to several phenomenological regularities, and provides theoretical analyses of these empirical regularities. Additionally, the book presents 13 community food webs, making it an essential reference for graduate students, teachers, and researchers in ecology. The theoretical aspects of the book are also valuable for teachers of applied combinatorics, particularly in random graphs, and it includes mathematical problems for researchers.

“Stochastic processes and applications in biology and medicine I: Theory (Biomathematics)” Book Review: This book provides a comprehensive understanding of stochastic processes to both mathematicians and biologists. It includes numbered chapters, sections, subsections, paragraphs, and subparagraphs, with theorems, lemmas, and propositions presented throughout. The book is divided into two parts, with the first part covering the foundational concepts and the second part covering advanced theorems and lemmas. This book provides a strong mathematical background to those studying stochastic processes, making it an essential resource for researchers, students, and professionals alike.

“Numerical Analysis Using R: Solutions to ODEs and PDEs” Book Review: This book provides practical numerical solutions to value and boundary problems in ODEs and PDEs, with a focus on high-resolution flux limiters, WENO, and meshless methods. The solutions are implemented in the open-source R language and include scattered data interpolation and PDE solution on irregular grids. The book also presents three case studies that demonstrate the use of numerical methods in tackling complex problems. Suitable for students and practitioners in all areas of science and engineering, particularly those using R.

“Introduction to Computation and Modeling for Differential Equations” Book Review: The book explains problem solving principles and applications across multiple disciplines, including engineering, physics, and chemistry. The topics include solving differential equations with mathematical, numerical, and programming tools. It covers methods for ordinary differential equations, numerical solutions for initial and boundary value problems, and partial differential equations. The “Five-M” approach is featured, which includes modeling, mathematics, methods, matlab, and multiphysics. It illustrates problem-solving using appropriate mathematical methods and new topics like the finite element method, ansatz methods, and finite volume methods. The book highlights various applications in mechanics, fluid dynamics, chemical engineering, heat conduction, electromagnetic field theory, and control theory. It serves as a guide for mathematics, science, computer science, physics, and engineering students.

“Higher Engineering Mathematics” Book Review: This is a valuable resource for engineering students. The book covers a wide range of topics from calculus to differential equations and Fourier analysis, making it a comprehensive guide for students of all levels. The author has provided clear explanations and examples, making difficult concepts easy to understand. Additionally, the book includes a large number of practice problems with solutions, allowing students to test their understanding and improve their problem-solving skills.

“An Introduction to Probability and Statistics” Book Review: This book provides comprehensive coverage of probability theory and mathematical statistics, including the fundamentals and foundations of probability as well as statistical inference. It includes chapters on regression analysis, multiple regression, logistic regression, and Poisson regression, as well as sample theories emphasizing the growing role of asymptotic statistics. The book also covers topics such as bootstrapping, estimation procedures, and resampling, and includes information on invariance, ancillary statistics, conjugate prior distributions, and invariant confidence intervals. With 550 problems and answers, 350 worked-out examples, and 200 remarks, this book is an essential reference for scientists and engineers in the fields of statistics, mathematics, physics, industrial management, and engineering, as well as for upper-undergraduate and graduate-level students in probability and statistics.