Moises Santillan – författare
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3 produkter
3 produkter
786 kr
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This textbook introduces mathematical modelling in life sciences in an interdisciplinary setting for students whose backgrounds range from medicine to mathematics, focusing on a set of topics that introduce mathematical thinking through biological questions. Each chapter begins with a clear biological question and then introduces the mathematical tools required to analyze it. This iterative approach is a proven success in the classrom. Starting with population dynamics, because its concepts are intuitive to students from the exact sciences, the text then broadens the canvas to topics such as electrophysiology and chemical kinetics, demonstrating the wide applicability of the same mathematical techniques. This structure is intended to build intuition alongside technical skill—students learn why a model is useful before learning how to build it.Also included are short historical perspectives and vignettes about the development of key ideas. These historical contexts motivate students and help them better grasp why particular concepts matter and how they arose in response to real scientific problems.Whether you are a student seeking a first rigorous introduction to mathematical biology or an instructor looking for a compact course text, this book is designed to be accessible, adaptable, and practical: you will encounter clear problems, worked mathematical tools, and exercises aimed at building modeling confidence and insight.
433 kr
Skickas inom 10-15 vardagar
This book brings theories in nonlinear dynamics, stochastic processes, irreversible thermodynamics, physical chemistry and biochemistry together in an introductory but formal and comprehensive manner. Coupled with examples, the theories are developed stepwise, starting with the simplest concepts and building upon them into a more general framework. Furthermore, each new mathematical derivation is immediately applied to one or more biological systems. The last chapters focus on applying mathematical and physical techniques to study systems such as: gene regulatory networks and molecular motors.The target audience of this book are mainly final year undergraduate and graduate students with a solid mathematical background (physicists, mathematicians and engineers), as well as with basic notions of biochemistry and cellular biology. This book can also be useful to students with a biological background who are interested in mathematical modeling and have a working knowledge of calculus, differential equations and a basic understanding of probability theory.
555 kr
Skickas inom 10-15 vardagar
This is a short and self-contained introduction to the field of mathematical modeling of gene-networks in bacteria. As an entry point to the field, we focus on the analysis of simple gene-network dynamics. The notes commence with an introduction to the deterministic modeling of gene-networks, with extensive reference to applicable results coming from dynamical systems theory. The second part of the notes treats extensively several approaches to the study of gene-network dynamics in the presence of noise—either arising from low numbers of molecules involved, or due to noise external to the regulatory process. The third and final part of the notes gives a detailed treatment of three well studied and concrete examples of gene-network dynamics by considering the lactose operon, the tryptophan operon, and the lysis-lysogeny switch. The notes contain an index for easy location of particular topics as well as an extensive bibliography of the current literature. The target audience of these notes are mainly graduates students and young researchers with a solid mathematical background (calculus, ordinary differential equations, and probability theory at a minimum), as well as with basic notions of biochemistry, cell biology, and molecular biology. They are meant to serve as a readable and brief entry point into a field that is currently highly active, and will allow the reader to grasp the current state of research and so prepare them for defining and tackling new research problems.