A Guide To Numerical Modelling In Systems Biology

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A Guide to Numerical Modelling in Systems Biology

Author : Peter Deuflhard
Publisher : Springer
ISBN 13 : 3319200593
Total Pages : 168 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis A Guide to Numerical Modelling in Systems Biology by : Peter Deuflhard

Download or read book A Guide to Numerical Modelling in Systems Biology written by Peter Deuflhard and published by Springer. This book was released on 2015-07-06 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Author : Andreas Kremling
Publisher : CRC Press
ISBN 13 : 1466567902
Total Pages : 379 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Systems Biology by : Andreas Kremling

Download or read book Systems Biology written by Andreas Kremling and published by CRC Press. This book was released on 2013-11-12 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Introduction to Mathematical Biology

Author : Ching Shan Chou
Publisher : Springer
ISBN 13 : 3319296388
Total Pages : 172 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Introduction to Mathematical Biology by : Ching Shan Chou

Download or read book Introduction to Mathematical Biology written by Ching Shan Chou and published by Springer. This book was released on 2016-04-27 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Mathematical Modeling in Systems Biology

Author : Brian P. Ingalls
Publisher :
ISBN 13 :
Total Pages : 423 pages
Book Rating : 4.:/5 (112 download)

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Book Synopsis Mathematical Modeling in Systems Biology by : Brian P. Ingalls

Download or read book Mathematical Modeling in Systems Biology written by Brian P. Ingalls and published by . This book was released on 2010 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt:

A Biologist's Guide to Mathematical Modeling in Ecology and Evolution

Author : Sarah P. Otto
Publisher : Princeton University Press
ISBN 13 : 1400840910
Total Pages : 745 pages
Book Rating : 4.4/5 (8 download)

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Book Synopsis A Biologist's Guide to Mathematical Modeling in Ecology and Evolution by : Sarah P. Otto

Download or read book A Biologist's Guide to Mathematical Modeling in Ecology and Evolution written by Sarah P. Otto and published by Princeton University Press. This book was released on 2011-09-19 with total page 745 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thirty years ago, biologists could get by with a rudimentary grasp of mathematics and modeling. Not so today. In seeking to answer fundamental questions about how biological systems function and change over time, the modern biologist is as likely to rely on sophisticated mathematical and computer-based models as traditional fieldwork. In this book, Sarah Otto and Troy Day provide biology students with the tools necessary to both interpret models and to build their own. The book starts at an elementary level of mathematical modeling, assuming that the reader has had high school mathematics and first-year calculus. Otto and Day then gradually build in depth and complexity, from classic models in ecology and evolution to more intricate class-structured and probabilistic models. The authors provide primers with instructive exercises to introduce readers to the more advanced subjects of linear algebra and probability theory. Through examples, they describe how models have been used to understand such topics as the spread of HIV, chaos, the age structure of a country, speciation, and extinction. Ecologists and evolutionary biologists today need enough mathematical training to be able to assess the power and limits of biological models and to develop theories and models themselves. This innovative book will be an indispensable guide to the world of mathematical models for the next generation of biologists. A how-to guide for developing new mathematical models in biology Provides step-by-step recipes for constructing and analyzing models Interesting biological applications Explores classical models in ecology and evolution Questions at the end of every chapter Primers cover important mathematical topics Exercises with answers Appendixes summarize useful rules Labs and advanced material available

Dynamic Systems Biology Modeling and Simulation

Author : Joseph DiStefano III
Publisher : Academic Press
ISBN 13 : 0124104932
Total Pages : 884 pages
Book Rating : 4.1/5 (241 download)

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Book Synopsis Dynamic Systems Biology Modeling and Simulation by : Joseph DiStefano III

Download or read book Dynamic Systems Biology Modeling and Simulation written by Joseph DiStefano III and published by Academic Press. This book was released on 2015-01-10 with total page 884 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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]

Mathematical Modeling in Systems Biology

Author : Brian P. Ingalls
Publisher : MIT Press
ISBN 13 : 0262545829
Total Pages : 423 pages
Book Rating : 4.2/5 (625 download)

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Book Synopsis Mathematical Modeling in Systems Biology by : Brian P. Ingalls

Download or read book Mathematical Modeling in Systems Biology written by Brian P. Ingalls and published by MIT Press. This book was released on 2022-06-07 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Handbook of Statistical Systems Biology

Author : Michael Stumpf
Publisher : John Wiley & Sons
ISBN 13 : 1119952042
Total Pages : 624 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis Handbook of Statistical Systems Biology by : Michael Stumpf

Download or read book Handbook of Statistical Systems Biology written by Michael Stumpf and published by John Wiley & Sons. This book was released on 2011-09-09 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systems Biology is now entering a mature phase in which the key issues are characterising uncertainty and stochastic effects in mathematical models of biological systems. The area is moving towards a full statistical analysis and probabilistic reasoning over the inferences that can be made from mathematical models. This handbook presents a comprehensive guide to the discipline for practitioners and educators, in providing a full and detailed treatment of these important and emerging subjects. Leading experts in systems biology and statistics have come together to provide insight in to the major ideas in the field, and in particular methods of specifying and fitting models, and estimating the unknown parameters. This book: Provides a comprehensive account of inference techniques in systems biology. Introduces classical and Bayesian statistical methods for complex systems. Explores networks and graphical modeling as well as a wide range of statistical models for dynamical systems. Discusses various applications for statistical systems biology, such as gene regulation and signal transduction. Features statistical data analysis on numerous technologies, including metabolic and transcriptomic technologies. Presents an in-depth presentation of reverse engineering approaches. Provides colour illustrations to explain key concepts. This handbook will be a key resource for researchers practising systems biology, and those requiring a comprehensive overview of this important field.

Biological Modeling and Simulation

Author : Russell Schwartz
Publisher : MIT Press
ISBN 13 : 0262195844
Total Pages : 403 pages
Book Rating : 4.2/5 (621 download)

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Book Synopsis Biological Modeling and Simulation by : Russell Schwartz

Download or read book Biological Modeling and Simulation written by Russell Schwartz and published by MIT Press. This book was released on 2008-07-25 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Biological Modeling and Simulation

Author : Russell Schwartz
Publisher : MIT Press
ISBN 13 : 0262303396
Total Pages : 403 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Biological Modeling and Simulation by : Russell Schwartz

Modeling in Systems Biology

Author : Ina Koch
Publisher : Springer Science & Business Media
ISBN 13 : 1849964742
Total Pages : 378 pages
Book Rating : 4.8/5 (499 download)

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Book Synopsis Modeling in Systems Biology by : Ina Koch

Download or read book Modeling in Systems Biology written by Ina Koch and published by Springer Science & Business Media. This book was released on 2010-10-21 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: The emerging, multi-disciplinary field of systems biology is devoted to the study of the relationships between various parts of a biological system, and computer modeling plays a vital role in the drive to understand the processes of life from an holistic viewpoint. Advancements in experimental technologies in biology and medicine have generated an enormous amount of biological data on the dependencies and interactions of many different molecular cell processes, fueling the development of numerous computational methods for exploring this data. The mathematical formalism of Petri net theory is able to encompass many of these techniques. This essential text/reference presents a comprehensive overview of cutting-edge research in applications of Petri nets in systems biology, with contributions from an international selection of experts. Those unfamiliar with the field are also provided with a general introduction to systems biology, the foundations of biochemistry, and the basics of Petri net theory. Further chapters address Petri net modeling techniques for building and analyzing biological models, as well as network prediction approaches, before reviewing the applications to networks of different biological classification. Topics and features: investigates the modular, qualitative modeling of regulatory networks using Petri nets, and examines an Hybrid Functional Petri net simulation case study; contains a glossary of the concepts and notation used in the book, in addition to exercises at the end of each chapter; covers the topological analysis of metabolic and regulatory networks, the analysis of models of signaling networks, and the prediction of network structure; provides a biological case study on the conversion of logical networks into Petri nets; discusses discrete modeling, stochastic modeling, fuzzy modeling, dynamic pathway modeling, genetic regulatory network modeling, and quantitative analysis techniques; includes a Foreword by Professor Jens Reich, Professor of Bioinformatics at Humboldt University and Max Delbrück Center for Molecular Medicine in Berlin. This unique guide to the modeling of biochemical systems using Petri net concepts will be of real utility to researchers and students of computational biology, systems biology, bioinformatics, computer science, and biochemistry.

Systems Biology

Author : Jinzhi Lei
Publisher : Springer Nature
ISBN 13 : 3030730336
Total Pages : 308 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Systems Biology by : Jinzhi Lei

Download or read book Systems Biology written by Jinzhi Lei and published by Springer Nature. This book was released on 2021-05-13 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Systems Biology: Mathematical Modeling and Model Analysis

Author : Lynda Feidan
Publisher :
ISBN 13 : 9781641162203
Total Pages : 213 pages
Book Rating : 4.1/5 (622 download)

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Book Synopsis Systems Biology: Mathematical Modeling and Model Analysis by : Lynda Feidan

Download or read book Systems Biology: Mathematical Modeling and Model Analysis written by Lynda Feidan and published by . This book was released on 2019-06-05 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology

Author : David Holcman
Publisher : Springer
ISBN 13 : 3319626272
Total Pages : 377 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology by : David Holcman

Download or read book Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology written by David Holcman and published by Springer. This book was released on 2017-10-04 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the modeling and mathematical analysis of stochastic dynamical systems along with their simulations. The collected chapters will review fundamental and current topics and approaches to dynamical systems in cellular biology. This text aims to develop improved mathematical and computational methods with which to study biological processes. At the scale of a single cell, stochasticity becomes important due to low copy numbers of biological molecules, such as mRNA and proteins that take part in biochemical reactions driving cellular processes. When trying to describe such biological processes, the traditional deterministic models are often inadequate, precisely because of these low copy numbers. This book presents stochastic models, which are necessary to account for small particle numbers and extrinsic noise sources. The complexity of these models depend upon whether the biochemical reactions are diffusion-limited or reaction-limited. In the former case, one needs to adopt the framework of stochastic reaction-diffusion models, while in the latter, one can describe the processes by adopting the framework of Markov jump processes and stochastic differential equations. Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology will appeal to graduate students and researchers in the fields of applied mathematics, biophysics, and cellular biology.

Dynamical Modeling of Biological Systems

Author : Stilianos Louca
Publisher : Stilianos Louca
ISBN 13 :
Total Pages : 545 pages
Book Rating : 4./5 ( download)

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Book Synopsis Dynamical Modeling of Biological Systems by : Stilianos Louca

Download or read book Dynamical Modeling of Biological Systems written by Stilianos Louca and published by Stilianos Louca. This book was released on 2023-06-07 with total page 545 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces concepts and practical tools for dynamical mathematical modeling of biological systems. Dynamical models describe the behavior of a system over time as a result of internal feedback loops and external forcing, based on mathematically formulated dynamical laws, similarly to how Newton's laws describe the movement of celestial bodies. Dynamical models are increasingly popular in biology, as they tend to be more powerful than static regression models. This book is meant for undergraduate and graduate students in physics, applied mathematics and data science with an interest in biology, as well as students in biology with a strong interest in mathematical methods. The book covers deterministic models (for example differential equations), stochastic models (for example Markov chains and autoregressive models) and model-independent aspects of time series analysis. Plenty of examples and exercises are included, often taken or inspired from the scientific literature, and covering a broad range of topics such as neuroscience, cell biology, genetics, evolution, ecology, microbiology, physiology, epidemiology and conservation. The book delivers generic modeling techniques used across a wide range of situations in biology, and hence readers from other scientific disciplines will find that much of the material is also applicable in their own field. Proofs of most mathematical statements are included for the interested reader, but are not essential for a practical understanding of the material. The book introduces the popular scientific programming language MATLAB as a tool for simulating models, fitting models to data, and visualizing data and model predictions. The material taught is current as of MATLAB version 2022b. The material is taught in a sufficiently general way that also permits the use of alternative programming languages.

Multiscale Models in Mechano and Tumor Biology

Author : Alf Gerisch
Publisher : Springer
ISBN 13 : 3319733710
Total Pages : 195 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Multiscale Models in Mechano and Tumor Biology by : Alf Gerisch

Download or read book Multiscale Models in Mechano and Tumor Biology written by Alf Gerisch and published by Springer. This book was released on 2018-03-16 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents and discusses the state of the art and future perspectives in mathematical modeling and homogenization techniques with the focus on addressing key physiological issues in the context of multiphase healthy and malignant biological materials. The highly interdisciplinary content brings together contributions from scientists with complementary areas of expertise, such as pure and applied mathematicians, engineers, and biophysicists. The book also features the lecture notes from a half-day introductory course on asymptotic homogenization. These notes are suitable for undergraduate mathematics or physics students, while the other chapters are aimed at graduate students and researchers.

Stochastic Modelling for Systems Biology, Third Edition

Author : Darren J. Wilkinson
Publisher : CRC Press
ISBN 13 : 1351000896
Total Pages : 292 pages
Book Rating : 4.3/5 (51 download)

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Book Synopsis Stochastic Modelling for Systems Biology, Third Edition by : Darren J. Wilkinson

Download or read book Stochastic Modelling for Systems Biology, Third Edition written by Darren J. Wilkinson and published by CRC Press. This book was released on 2018-12-07 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Having been thoroughly updated to reflect this, this third edition covers everything necessary for a good appreciation of stochastic kinetic modelling of biological networks in the systems biology context. New methods and applications are included in the book, and the use of R for practical illustration of the algorithms has been greatly extended. There is a brand new chapter on spatially extended systems, and the statistical inference chapter has also been extended with new methods, including approximate Bayesian computation (ABC). Stochastic Modelling for Systems Biology, Third Edition is now supplemented by an additional software library, written in Scala, described in a new appendix to the book. New in the Third Edition New chapter on spatially extended systems, covering the spatial Gillespie algorithm for reaction diffusion master equation models in 1- and 2-d, along with fast approximations based on the spatial chemical Langevin equation Significantly expanded chapter on inference for stochastic kinetic models from data, covering ABC, including ABC-SMC Updated R package, including code relating to all of the new material New R package for parsing SBML models into simulatable stochastic Petri net models New open-source software library, written in Scala, replicating most of the functionality of the R packages in a fast, compiled, strongly typed, functional language Keeping with the spirit of earlier editions, 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. An effective introduction to the area of stochastic modelling in computational systems biology, this new edition adds additional detail and computational methods that will provide a stronger foundation for the development of more advanced courses in stochastic biological modelling.