Stochastic Modelling For Systems Biology

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Stochastic Modelling for Systems Biology

Darren J. Wilkinson
Stochastic Modelling for Systems Biology Book PDF

Author : Darren J. Wilkinson
Publisher : CRC Press
Page : 296 pages
File Size : 47,5 Mb
Release : 2006-04-18
Category : Mathematics
ISBN : 1584885408

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Stochastic Modelling for Systems Biology by Darren J. Wilkinson Pdf

Although stochastic kinetic models are increasingly accepted as the best way to represent and simulate genetic and biochemical networks, most researchers in the field have limited knowledge of stochastic process theory. The stochastic processes formalism provides a beautiful, elegant, and coherent foundation for chemical kinetics and there is a wealth of associated theory every bit as powerful and elegant as that for conventional continuous deterministic models. The time is right for an introductory text written from this perspective. Stochastic Modelling for Systems Biology presents an accessible introduction to stochastic modelling using examples that are familiar to systems biology researchers. Focusing on computer simulation, the author examines the use of stochastic processes for modelling biological systems. He provides a comprehensive understanding of stochastic kinetic modelling of biological networks in the systems biology context. The text covers the latest simulation techniques and research material, such as parameter inference, and includes many examples and figures as well as software code in R for various applications. While emphasizing the necessary probabilistic and stochastic methods, the author takes a practical approach, rooting his theoretical development in discussions of the intended application. Written with self-study in mind, the book includes technical chapters that deal with the difficult problems of inference for stochastic kinetic models from experimental data. Providing enough background information to make the subject accessible to the non-specialist, the book integrates a fairly diverse literature into a single convenient and notationally consistent source.

Stochastic Modelling for Systems Biology, Third Edition

Darren J. Wilkinson
Stochastic Modelling for Systems Biology Third Edition Book PDF

Author : Darren J. Wilkinson
Publisher : CRC Press
Page : 405 pages
File Size : 52,8 Mb
Release : 2018-12-07
Category : Mathematics
ISBN : 9781351000901

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Stochastic Modelling for Systems Biology, Third Edition by Darren J. Wilkinson Pdf

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.

Deterministic Versus Stochastic Modelling in Biochemistry and Systems Biology

Paola Lecca,Ian Laurenzi,Ferenc Jordan
Deterministic Versus Stochastic Modelling in Biochemistry and Systems Biology Book PDF

Author : Paola Lecca,Ian Laurenzi,Ferenc Jordan
Publisher : Elsevier
Page : 411 pages
File Size : 41,5 Mb
Release : 2013-04-09
Category : Mathematics
ISBN : 9781908818218

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Deterministic Versus Stochastic Modelling in Biochemistry and Systems Biology by Paola Lecca,Ian Laurenzi,Ferenc Jordan Pdf

Stochastic kinetic methods are currently considered to be the most realistic and elegant means of representing and simulating the dynamics of biochemical and biological networks. Deterministic versus stochastic modelling in biochemistry and systems biology introduces and critically reviews the deterministic and stochastic foundations of biochemical kinetics, covering applied stochastic process theory for application in the field of modelling and simulation of biological processes at the molecular scale. Following an overview of deterministic chemical kinetics and the stochastic approach to biochemical kinetics, the book goes onto discuss the specifics of stochastic simulation algorithms, modelling in systems biology and the structure of biochemical models. Later chapters cover reaction-diffusion systems, and provide an analysis of the Kinfer and BlenX software systems. The final chapter looks at simulation of ecodynamics and food web dynamics. Introduces mathematical concepts and formalisms of deterministic and stochastic modelling through clear and simple examples Presents recently developed discrete stochastic formalisms for modelling biological systems and processes Describes and applies stochastic simulation algorithms to implement a stochastic formulation of biochemical and biological kinetics

Stochastic Modelling for Systems Biology, Second Edition

Darren J. Wilkinson
Stochastic Modelling for Systems Biology Second Edition Book PDF

Author : Darren J. Wilkinson
Publisher : CRC Press
Page : 365 pages
File Size : 52,7 Mb
Release : 2011-11-09
Category : Mathematics
ISBN : 9781439837726

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Stochastic Modelling for Systems Biology, Second Edition by Darren J. Wilkinson Pdf

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.

Stochastic Modelling for Systems Biology

Darren James Wilkinson
Stochastic Modelling for Systems Biology Book PDF

Author : Darren James Wilkinson
Publisher : Unknown
Page : 360 pages
File Size : 48,5 Mb
Release : 2012
Category : Biological systems
ISBN : 0429152035

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Stochastic Modelling for Systems Biology by Darren James Wilkinson Pdf

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 accessib.

Stochastic Models in Biology

Narendra S. Goel,Nira Richter-Dyn
Stochastic Models in Biology Book PDF

Author : Narendra S. Goel,Nira Richter-Dyn
Publisher : Elsevier
Page : 282 pages
File Size : 49,7 Mb
Release : 2016-01-26
Category : Science
ISBN : 9781483278100

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Stochastic Models in Biology by Narendra S. Goel,Nira Richter-Dyn Pdf

Stochastic Models in Biology describes the usefulness of the theory of stochastic process in studying biological phenomena. The book describes analysis of biological systems and experiments though probabilistic models rather than deterministic methods. The text reviews the mathematical analyses for modeling different biological systems such as the random processes continuous in time and discrete in state space. The book also discusses population growth and extinction through Malthus' law and the work of MacArthur and Wilson. The text then explains the dynamics of a population of interacting species. The book also addresses population genetics under systematic evolutionary pressures known as deterministic equations and genetic changes in a finite population known as stochastic equations. The text then turns to stochastic modeling of biological systems at the molecular level, particularly the kinetics of biochemical reactions. The book also presents various useful equations such as the differential equation for generating functions for birth and death processes. The text can prove valuable for biochemists, cellular biologists, and researchers in the medical and chemical field who are tasked to perform data analysis.

Stochastic Approaches for Systems Biology

Mukhtar Ullah,Olaf Wolkenhauer
Stochastic Approaches for Systems Biology Book PDF

Author : Mukhtar Ullah,Olaf Wolkenhauer
Publisher : Springer Science & Business Media
Page : 290 pages
File Size : 50,7 Mb
Release : 2011-07-15
Category : Mathematics
ISBN : 9781461404781

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Stochastic Approaches for Systems Biology by Mukhtar Ullah,Olaf Wolkenhauer Pdf

This textbook focuses on stochastic analysis in systems biology containing both the theory and application. While the authors provide a review of probability and random variables, subsequent notions of biochemical reaction systems and the relevant concepts of probability theory are introduced side by side. This leads to an intuitive and easy-to-follow presentation of stochastic framework for modeling subcellular biochemical systems. In particular, the authors make an effort to show how the notion of propensity, the chemical master equation and the stochastic simulation algorithm arise as consequences of the Markov property. The text contains many illustrations, examples and exercises to illustrate the ideas and methods that are introduced. Matlab code is also provided where appropriate. Additionally, the cell cycle is introduced as a more complex case study. Senior undergraduate and graduate students in mathematics and physics as well as researchers working in the area of systems biology, bioinformatics and related areas will find this text useful.

Stochastic Dynamics for Systems Biology

Christian Mazza,Michel Benaim
Stochastic Dynamics for Systems Biology Book PDF

Author : Christian Mazza,Michel Benaim
Publisher : CRC Press
Page : 274 pages
File Size : 45,9 Mb
Release : 2016-04-19
Category : Mathematics
ISBN : 9781466514942

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Stochastic Dynamics for Systems Biology by Christian Mazza,Michel Benaim Pdf

Stochastic Dynamics for Systems Biology is one of the first books to provide a systematic study of the many stochastic models used in systems biology. The book shows how the mathematical models are used as technical tools for simulating biological processes and how the models lead to conceptual insights on the functioning of the cellular processing

Stochastic Dynamics in Computational Biology

Stefanie Winkelmann,Christof Schütte
Stochastic Dynamics in Computational Biology Book PDF

Author : Stefanie Winkelmann,Christof Schütte
Publisher : Springer Nature
Page : 284 pages
File Size : 51,9 Mb
Release : 2021-01-04
Category : Mathematics
ISBN : 9783030623876

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Stochastic Dynamics in Computational Biology by Stefanie Winkelmann,Christof Schütte Pdf

The aim of this book is to provide a well-structured and coherent overview of existing mathematical modeling approaches for biochemical reaction systems, investigating relations between both the conventional models and several types of deterministic-stochastic hybrid model recombinations. Another main objective is to illustrate and compare diverse numerical simulation schemes and their computational effort. Unlike related works, this book presents a broad scope in its applications, from offering a detailed introduction to hybrid approaches for the case of multiple population scales to discussing the setting of time-scale separation resulting from widely varying firing rates of reaction channels. Additionally, it also addresses modeling approaches for non well-mixed reaction-diffusion dynamics, including deterministic and stochastic PDEs and spatiotemporal master equations. Finally, by translating and incorporating complex theory to a level accessible to non-mathematicians, this book effectively bridges the gap between mathematical research in computational biology and its practical use in biological, biochemical, and biomedical systems.

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

David Holcman
Stochastic Processes Multiscale Modeling and Numerical Methods for Computational Cellular Biology Book PDF

Author : David Holcman
Publisher : Springer
Page : 377 pages
File Size : 49,6 Mb
Release : 2017-10-04
Category : Mathematics
ISBN : 9783319626277

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Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology by David Holcman Pdf

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.

Systems Biology

Jinzhi Lei
Systems Biology Book PDF

Author : Jinzhi Lei
Publisher : Springer Nature
Page : 308 pages
File Size : 41,7 Mb
Release : 2021-05-13
Category : Mathematics
ISBN : 9783030730338

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Systems Biology by Jinzhi Lei Pdf

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.

Stochastic Chemical Reaction Systems in Biology

Hong Qian,Hao Ge
Stochastic Chemical Reaction Systems in Biology Book PDF

Author : Hong Qian,Hao Ge
Publisher : Springer Nature
Page : 364 pages
File Size : 46,7 Mb
Release : 2021-10-18
Category : Mathematics
ISBN : 9783030862527

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Stochastic Chemical Reaction Systems in Biology by Hong Qian,Hao Ge Pdf

This book provides an introduction to the analysis of stochastic dynamic models in biology and medicine. The main aim is to offer a coherent set of probabilistic techniques and mathematical tools which can be used for the simulation and analysis of various biological phenomena. These tools are illustrated on a number of examples. For each example, the biological background is described, and mathematical models are developed following a unified set of principles. These models are then analyzed and, finally, the biological implications of the mathematical results are interpreted. The biological topics covered include gene expression, biochemistry, cellular regulation, and cancer biology. The book will be accessible to graduate students who have a strong background in differential equations, the theory of nonlinear dynamical systems, Markovian stochastic processes, and both discrete and continuous state spaces, and who are familiar with the basic concepts of probability theory.

Stochastic Processes in Cell Biology

Paul C. Bressloff
Stochastic Processes in Cell Biology Book PDF

Author : Paul C. Bressloff
Publisher : Springer Nature
Page : 773 pages
File Size : 51,6 Mb
Release : 2022-01-04
Category : Mathematics
ISBN : 9783030725150

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Stochastic Processes in Cell Biology by Paul C. Bressloff Pdf

This book develops the theory of continuous and discrete stochastic processes within the context of cell biology. In the second edition the material has been significantly expanded, particularly within the context of nonequilibrium and self-organizing systems. Given the amount of additional material, the book has been divided into two volumes, with volume I mainly covering molecular processes and volume II focusing on cellular processes. A wide range of biological topics are covered in the new edition, including stochastic ion channels and excitable systems, molecular motors, stochastic gene networks, genetic switches and oscillators, epigenetics, normal and anomalous diffusion in complex cellular environments, stochastically-gated diffusion, active intracellular transport, signal transduction, cell sensing, bacterial chemotaxis, intracellular pattern formation, cell polarization, cell mechanics, biological polymers and membranes, nuclear structure and dynamics, biological condensates, molecular aggregation and nucleation, cellular length control, cell mitosis, cell motility, cell adhesion, cytoneme-based morphogenesis, bacterial growth, and quorum sensing. The book also provides a pedagogical introduction to the theory of stochastic and nonequilibrium processes – Fokker Planck equations, stochastic differential equations, stochastic calculus, master equations and jump Markov processes, birth-death processes, Poisson processes, first passage time problems, stochastic hybrid systems, queuing and renewal theory, narrow capture and escape, extreme statistics, search processes and stochastic resetting, exclusion processes, WKB methods, large deviation theory, path integrals, martingales and branching processes, numerical methods, linear response theory, phase separation, fluctuation-dissipation theorems, age-structured models, and statistical field theory. This text is primarily aimed at graduate students and researchers working in mathematical biology, statistical and biological physicists, and applied mathematicians interested in stochastic modeling. Applied probabilists should also find it of interest. It provides significant background material in applied mathematics and statistical physics, and introduces concepts in stochastic and nonequilibrium processes via motivating biological applications. The book is highly illustrated and contains a large number of examples and exercises that further develop the models and ideas in the body of the text. It is based on a course that the author has taught at the University of Utah for many years.

Modeling in Systems Biology

Ina Koch,Wolfgang Reisig,Falk Schreiber
Modeling in Systems Biology Book PDF

Author : Ina Koch,Wolfgang Reisig,Falk Schreiber
Publisher : Springer Science & Business Media
Page : 378 pages
File Size : 46,6 Mb
Release : 2010-10-21
Category : Computers
ISBN : 9781849964746

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Modeling in Systems Biology by Ina Koch,Wolfgang Reisig,Falk Schreiber Pdf

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.

Stochastic Biomathematical Models

Mostafa Bachar,Jerry J. Batzel,Susanne Ditlevsen
Stochastic Biomathematical Models Book PDF

Author : Mostafa Bachar,Jerry J. Batzel,Susanne Ditlevsen
Publisher : Springer
Page : 206 pages
File Size : 52,9 Mb
Release : 2012-10-19
Category : Mathematics
ISBN : 9783642321573

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Stochastic Biomathematical Models by Mostafa Bachar,Jerry J. Batzel,Susanne Ditlevsen Pdf

Stochastic biomathematical models are becoming increasingly important as new light is shed on the role of noise in living systems. In certain biological systems, stochastic effects may even enhance a signal, thus providing a biological motivation for the noise observed in living systems. Recent advances in stochastic analysis and increasing computing power facilitate the analysis of more biophysically realistic models, and this book provides researchers in computational neuroscience and stochastic systems with an overview of recent developments. Key concepts are developed in chapters written by experts in their respective fields. Topics include: one-dimensional homogeneous diffusions and their boundary behavior, large deviation theory and its application in stochastic neurobiological models, a review of mathematical methods for stochastic neuronal integrate-and-fire models, stochastic partial differential equation models in neurobiology, and stochastic modeling of spreading cortical depression.