Systems Biology Mathematical Modeling And Model Analysis


Systems Biology Mathematical Modeling And Model Analysis
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Systems Biology


Systems Biology
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Author : Andreas Kremling
language : en
Publisher: CRC Press
Release Date : 2013-11-12

Systems Biology written by Andreas Kremling and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-12 with Mathematics categories.


Drawing on the latest research in the field, Systems Biology: Mathematical Modeling and Model Analysis presents many methods for modeling and analyzing biological systems, in particular cellular systems. It shows how to use predictive mathematical models to acquire and analyze knowledge about cellular systems. It also explores how the models are sy



Mathematical Modeling In Systems Biology


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.



Systems Biology Mathematical Modeling And Model Analysis


Systems Biology Mathematical Modeling And Model Analysis
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Author : Lynda Feidan
language : en
Publisher:
Release Date : 2019-06-05

Systems Biology Mathematical Modeling And Model Analysis written by Lynda Feidan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-05 with categories.


Systems biology is the mathematical and computational modeling of complex biological systems. It is an interdisciplinary field of study concerned with complex interactions within biological systems. One of the primary objectives of systems biology is to discover and model emergent properties and explore the properties of cells, tissues and organisms functioning as a system. The foundations of systems biology are control theory and cybernetics, quantitative modeling of enzyme kinetics, synergetics, simulations for the study of neurophysiology and the mathematical modeling of population dynamics. The topics covered in this extensive book deal with the core aspects of mathematical modeling and model analysis in the discipline of systems biology. For all readers who are interested in this field, the case studies included in this book will serve as an excellent guide to develop a comprehensive understanding. It aims to equip students and experts with the advanced topics and upcoming concepts in this area of study.



Systems Biology


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.



Mathematical Modelling In Plant Biology


Mathematical Modelling In Plant Biology
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Author : Richard J. Morris
language : en
Publisher: Springer
Release Date : 2018-11-05

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 2018-11-05 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.



Mathematical Modeling Of Biological Systems Volume Ii


Mathematical Modeling Of Biological Systems Volume Ii
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Author : Andreas Deutsch
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-10-12

Mathematical Modeling Of Biological Systems Volume Ii written by Andreas Deutsch 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 2007-10-12 with Mathematics categories.


Volume II of this two-volume, interdisciplinary work is a unified presentation of a broad range of state-of-the-art topics in the rapidly growing field of mathematical modeling in the biological sciences. Highlighted throughout are mathematical and computational apporaches to examine central problems in the life sciences, ranging from the organization principles of individual cells to the dynamics of large populations. The chapters are thematically organized into the following main areas: epidemiology, evolution and ecology, immunology, neural systems and the brain, and innovative mathematical methods and education. The work will be an excellent reference text for a broad audience of researchers, practitioners, and advanced students in this rapidly growing field at the intersection of applied mathematics, experimental biology and medicine, computational biology, biochemistry, computer science, and physics.



Stochastic Modelling For Systems Biology Second Edition


Stochastic Modelling For Systems Biology Second Edition
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Author : Darren J. Wilkinson
language : en
Publisher: CRC Press
Release Date : 2011-11-09

Stochastic Modelling For Systems Biology Second Edition written by Darren J. Wilkinson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-11-09 with Mathematics categories.


Since the first edition of Stochastic Modelling for Systems Biology, there have been many interesting developments in the use of "likelihood-free" methods of Bayesian inference for complex stochastic models. Re-written to reflect this modern perspective, this second edition covers everything necessary for a good appreciation of stochastic kinetic modelling of biological networks in the systems biology context. Keeping with the spirit of the first edition, all of the new theory is presented in a very informal and intuitive manner, keeping the text as accessible as possible to the widest possible readership. New in the Second Edition All examples have been updated to Systems Biology Markup Language Level 3 All code relating to simulation, analysis, and inference for stochastic kinetic models has been re-written and re-structured in a more modular way An ancillary website provides links, resources, errata, and up-to-date information on installation and use of the associated R package More background material on the theory of Markov processes and stochastic differential equations, providing more substance for mathematically inclined readers Discussion of some of the more advanced concepts relating to stochastic kinetic models, such as random time change representations, Kolmogorov equations, Fokker-Planck equations and the linear noise approximation Simple modelling of "extrinsic" and "intrinsic" noise An effective introduction to the area of stochastic modelling in computational systems biology, this new edition adds additional mathematical detail and computational methods that will provide a stronger foundation for the development of more advanced courses in stochastic biological modelling.



Mathematical Modeling Of Biological Systems Volume I


Mathematical Modeling Of Biological Systems Volume I
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Author : Andreas Deutsch
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-06-15

Mathematical Modeling Of Biological Systems Volume I written by Andreas Deutsch 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 2007-06-15 with Mathematics categories.


Volume I of this two-volume, interdisciplinary work is a unified presentation of a broad range of state-of-the-art topics in the rapidly growing field of mathematical modeling in the biological sciences. The chapters are thematically organized into the following main areas: cellular biophysics, regulatory networks, developmental biology, biomedical applications, data analysis and model validation. The work will be an excellent reference text for a broad audience of researchers, practitioners, and advanced students in this rapidly growing field at the intersection of applied mathematics, experimental biology and medicine, computational biology, biochemistry, computer science, and physics.



Dynamic Systems Biology Modeling And Simulation


Dynamic Systems Biology Modeling And Simulation
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Author : Joseph DiStefano III
language : en
Publisher: Academic Press
Release Date : 2015-01-10

Dynamic Systems Biology Modeling And Simulation written by Joseph DiStefano III and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-10 with Science categories.


Dynamic Systems Biology Modeling and Simuation consolidates and unifies classical and contemporary multiscale methodologies for mathematical modeling and computer simulation of dynamic biological systems – from molecular/cellular, organ-system, on up to population levels. The book pedagogy is developed as a well-annotated, systematic tutorial – with clearly spelled-out and unified nomenclature – derived from the author’s own modeling efforts, publications and teaching over half a century. Ambiguities in some concepts and tools are clarified and others are rendered more accessible and practical. The latter include novel qualitative theory and methodologies for recognizing dynamical signatures in data using structural (multicompartmental and network) models and graph theory; and analyzing structural and measurement (data) models for quantification feasibility. The level is basic-to-intermediate, with much emphasis on biomodeling from real biodata, for use in real applications. Introductory coverage of core mathematical concepts such as linear and nonlinear differential and difference equations, Laplace transforms, linear algebra, probability, statistics and stochastics topics; PLUS ....... The pertinent biology, biochemistry, biophysics or pharmacology for modeling are provided, to support understanding the amalgam of “math modeling” with life sciences. Strong emphasis on quantifying as well as building and analyzing biomodels: includes methodology and computational tools for parameter identifiability and sensitivity analysis; parameter estimation from real data; model distinguishability and simplification; and practical bioexperiment design and optimization. Companion website provides solutions and program code for examples and exercises using Matlab, Simulink, VisSim, SimBiology, SAAMII, AMIGO, Copasi and SBML-coded models. A full set of PowerPoint slides are available from the author for teaching from his textbook. He uses them to teach a 10 week quarter upper division course at UCLA, which meets twice a week, so there are 20 lectures. They can easily be augmented or stretched for a 15 week semester course. Importantly, the slides are editable, so they can be readily adapted to a lecturer’s personal style and course content needs. The lectures are based on excerpts from 12 of the first 13 chapters of DSBMS. They are designed to highlight the key course material, as a study guide and structure for students following the full text content. The complete PowerPoint slide package (~25 MB) can be obtained by instructors (or prospective instructors) by emailing the author directly, at: [email protected]



Introduction To Mathematical Biology


Introduction To Mathematical Biology
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Author : Ching Shan Chou
language : en
Publisher: Springer
Release Date : 2016-04-27

Introduction To Mathematical Biology written by Ching Shan Chou and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-27 with Mathematics categories.


This book is based on a one semester course that the authors have been teaching for several years, and includes two sets of case studies. The first includes chemostat models, predator-prey interaction, competition among species, the spread of infectious diseases, and oscillations arising from bifurcations. In developing these topics, readers will also be introduced to the basic theory of ordinary differential equations, and how to work with MATLAB without having any prior programming experience. The second set of case studies were adapted from recent and current research papers to the level of the students. Topics have been selected based on public health interest. This includes the risk of atherosclerosis associated with high cholesterol levels, cancer and immune interactions, cancer therapy, and tuberculosis. Readers will experience how mathematical models and their numerical simulations can provide explanations that guide biological and biomedical research. Considered to be the undergraduate companion to the more advanced book "Mathematical Modeling of Biological Processes" (A. Friedman, C.-Y. Kao, Springer – 2014), this book is geared towards undergraduate students with little background in mathematics and no biological background.