Modeling Biology

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Mathematical Modeling In Systems Biology

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Author : Brian P. Ingalls
language : en
Publisher: MIT Press
Release Date : 2022-06-07

Mathematical Modeling In Systems Biology written by Brian P. Ingalls and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-07 with Science categories.

An introduction to the mathematical concepts and techniques needed for the construction and analysis of models in molecular systems biology. Systems techniques are integral to current research in molecular cell biology, and system-level investigations are often accompanied by mathematical models. These models serve as working hypotheses: they help us to understand and predict the behavior of complex systems. This book offers an introduction to mathematical concepts and techniques needed for the construction and interpretation of models in molecular systems biology. It is accessible to upper-level undergraduate or graduate students in life science or engineering who have some familiarity with calculus, and will be a useful reference for researchers at all levels. The first four chapters cover the basics of mathematical modeling in molecular systems biology. The last four chapters address specific biological domains, treating modeling of metabolic networks, of signal transduction pathways, of gene regulatory networks, and of electrophysiology and neuronal action potentials. Chapters 3–8 end with optional sections that address more specialized modeling topics. Exercises, solvable with pen-and-paper calculations, appear throughout the text to encourage interaction with the mathematical techniques. More involved end-of-chapter problem sets require computational software. Appendixes provide a review of basic concepts of molecular biology, additional mathematical background material, and tutorials for two computational software packages (XPPAUT and MATLAB) that can be used for model simulation and analysis.

Biological Modeling And Simulation

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Author : Russell Schwartz
language : en
Publisher: MIT Press
Release Date : 2008-07-25

Biological Modeling And Simulation written by Russell Schwartz and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-07-25 with Science categories.

A practice-oriented survey of techniques for computational modeling and simulation suitable for a broad range of biological problems. There are many excellent computational biology resources now available for learning about methods that have been developed to address specific biological systems, but comparatively little attention has been paid to training aspiring computational biologists to handle new and unanticipated problems. This text is intended to fill that gap by teaching students how to reason about developing formal mathematical models of biological systems that are amenable to computational analysis. It collects in one place a selection of broadly useful models, algorithms, and theoretical analysis tools normally found scattered among many other disciplines. It thereby gives the aspiring student a bag of tricks that will serve him or her well in modeling problems drawn from numerous subfields of biology. These techniques are taught from the perspective of what the practitioner needs to know to use them effectively, supplemented with references for further reading on more advanced use of each method covered. The text, which grew out of a class taught at Carnegie Mellon University, covers models for optimization, simulation and sampling, and parameter tuning. These topics provide a general framework for learning how to formulate mathematical models of biological systems, what techniques are available to work with these models, and how to fit the models to particular systems. Their application is illustrated by many examples drawn from a variety of biological disciplines and several extended case studies that show how the methods described have been applied to real problems in biology.

Mathematical Models In Biology

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Author : Leah Edelstein-Keshet
language : en
Publisher: SIAM
Release Date : 1988-01-01

Mathematical Models In Biology written by Leah Edelstein-Keshet and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988-01-01 with Mathematics categories.

Mathematical Models in Biology is an introductory book for readers interested in biological applications of mathematics and modeling in biology. A favorite in the mathematical biology community, it shows how relatively simple mathematics can be applied to a variety of models to draw interesting conclusions. Connections are made between diverse biological examples linked by common mathematical themes. A variety of discrete and continuous ordinary and partial differential equation models are explored. Although great advances have taken place in many of the topics covered, the simple lessons contained in this book are still important and informative. Audience: the book does not assume too much background knowledge--essentially some calculus and high-school algebra. It was originally written with third- and fourth-year undergraduate mathematical-biology majors in mind; however, it was picked up by beginning graduate students as well as researchers in math (and some in biology) who wanted to learn about this field.

A Guide To Numerical Modelling In Systems Biology

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Author : Peter Deuflhard
language : en
Publisher: Springer
Release Date : 2015-07-06

A Guide To Numerical Modelling In Systems Biology written by Peter Deuflhard and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-06 with Mathematics categories.

This book is intended for students of computational systems biology with only a limited background in mathematics. Typical books on systems biology merely mention algorithmic approaches, but without offering a deeper understanding. On the other hand, mathematical books are typically unreadable for computational biologists. The authors of the present book have worked hard to fill this gap. The result is not a book on systems biology, but on computational methods in systems biology. This book originated from courses taught by the authors at Freie Universität Berlin. The guiding idea of the courses was to convey those mathematical insights that are indispensable for systems biology, teaching the necessary mathematical prerequisites by means of many illustrative examples and without any theorems. The three chapters cover the mathematical modelling of biochemical and physiological processes, numerical simulation of the dynamics of biological networks and identification of model parameters by means of comparisons with real data. Throughout the text, the strengths and weaknesses of numerical algorithms with respect to various systems biological issues are discussed. Web addresses for downloading the corresponding software are also included.

Systems Biology

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Author : Jinzhi Lei
language : en
Publisher: Springer Nature
Release Date : 2021-05-13

Systems Biology written by Jinzhi Lei and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-13 with Mathematics categories.

This book discusses the mathematical simulation of biological systems, with a focus on the modeling of gene expression, gene regulatory networks and stem cell regeneration. The diffusion of morphogens is addressed by introducing various reaction-diffusion equations based on different hypotheses concerning the process of morphogen gradient formation. The robustness of steady-state gradients is also covered through boundary value problems. The introduction gives an overview of the relevant biological concepts (cells, DNA, organism development) and provides the requisite mathematical preliminaries on continuous dynamics and stochastic modeling. A basic understanding of calculus is assumed. The techniques described in this book encompass a wide range of mechanisms, from molecular behavior to population dynamics, and the inclusion of recent developments in the literature together with first-hand results make it an ideal reference for both new students and experienced researchers in the field of systems biology and applied mathematics.

Exploring Mathematical Modeling In Biology Through Case Studies And Experimental Activities

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Author : Rebecca Sanft
language : en
Publisher: Academic Press
Release Date : 2020-04-01

Exploring Mathematical Modeling In Biology Through Case Studies And Experimental Activities written by Rebecca Sanft and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-01 with Science categories.

Exploring Mathematical Modeling in Biology through Case Studies and Experimental Activities provides supporting materials for courses taken by students majoring in mathematics, computer science or in the life sciences. The book's cases and lab exercises focus on hypothesis testing and model development in the context of real data. The supporting mathematical, coding and biological background permit readers to explore a problem, understand assumptions, and the meaning of their results. The experiential components provide hands-on learning both in the lab and on the computer. As a beginning text in modeling, readers will learn to value the approach and apply competencies in other settings. Included case studies focus on building a model to solve a particular biological problem from concept and translation into a mathematical form, to validating the parameters, testing the quality of the model and finally interpreting the outcome in biological terms. The book also shows how particular mathematical approaches are adapted to a variety of problems at multiple biological scales. Finally, the labs bring the biological problems and the practical issues of collecting data to actually test the model and/or adapting the mathematics to the data that can be collected.

Single Cell Based Models In Biology And Medicine

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Author : Alexander Anderson
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-08-07

Single Cell Based Models In Biology And Medicine written by Alexander Anderson and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-07 with Mathematics categories.

Many different single-cell-based models have been developed and applied to biological and medical problems. Computational approaches used are Monte-Carlo simulations, energy minimisation techniques, volume conservation laws, solutions of the equations of motion for each individual cell or for each point on the cell membrane. They differ in the level of detail that defines the cell structure and subsequently in the number of individual cells that the model can incorporate. This volume presents a collection of mathematical and computational single-cell-based models and their application. The main sections cover four general model groupings: hybrid cellular automata, cellular potts, lattice-free cells, and viscoelastic cells. Each section is introduced by a discussion of the applicability of the particular modelling approach and its advantages and disadvantages, which will make the book suitable for students starting research in mathematical biology as well as scientists modelling multicellular processes.

Mathematical Modelling In Plant Biology

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Author : Richard J. Morris
language : en
Publisher: Springer
Release Date : 2018-11-13

Mathematical Modelling In Plant Biology written by Richard J. Morris and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-13 with Science categories.

Progress in plant biology relies on the quantification, analysis and mathematical modeling of data over different time and length scales. This book describes common mathematical and computational approaches as well as some carefully chosen case studies that demonstrate the use of these techniques to solve problems at the forefront of plant biology. Each chapter is written by an expert in field with the goal of conveying concepts whilst at the same time providing sufficient background and links to available software for readers to rapidly build their own models and run their own simulations. This book is aimed at postgraduate students and researchers working the field of plant systems biology and synthetic biology, but will also be a useful reference for anyone wanting to get into quantitative plant biology.

Methods And Models In Mathematical Biology

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Author : Johannes Müller
language : en
Publisher: Springer
Release Date : 2015-08-13

Methods And Models In Mathematical Biology written by Johannes Müller and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-13 with Mathematics categories.

This book developed from classes in mathematical biology taught by the authors over several years at the Technische Universität München. The main themes are modeling principles, mathematical principles for the analysis of these models and model-based analysis of data. The key topics of modern biomathematics are covered: ecology, epidemiology, biochemistry, regulatory networks, neuronal networks and population genetics. A variety of mathematical methods are introduced, ranging from ordinary and partial differential equations to stochastic graph theory and branching processes. A special emphasis is placed on the interplay between stochastic and deterministic models.

Statistical Modeling And Machine Learning For Molecular Biology

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Author : Alan Moses
language : en
Publisher: CRC Press
Release Date : 2017-01-06

Statistical Modeling And Machine Learning For Molecular Biology written by Alan Moses and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-06 with Computers categories.

• Assumes no background in statistics or computers • Covers most major types of molecular biological data • Covers the statistical and machine learning concepts of most practical utility (P-values, clustering, regression, regularization and classification) • Intended for graduate students beginning careers in molecular biology, systems biology, bioengineering and genetics