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Stochastic And Spatio Temporal Modeling In Systems Biology
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Book Synopsis Stochastic and Spatio-temporal Modeling in Systems Biology by : Aditya P. Singh
Download or read book Stochastic and Spatio-temporal Modeling in Systems Biology written by Aditya P. Singh and published by . This book was released on 2007 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: The post genome era of systems biology is marked by the need to develop models that explain the emergent behavior of biological systems different from the functioning of the individual parts of their constituents. Models should not only explain the observed experimental findings but should also be able to predict under outcomes that are not currently experimentally amenable.
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.
Book Synopsis Stochastic Modelling for Systems Biology, Second Edition by : Darren J. Wilkinson
Download or read book Stochastic Modelling for Systems Biology, Second Edition written by Darren J. Wilkinson and published by CRC Press. This book was released on 2011-11-09 with total page 365 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. 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.
Book Synopsis Stochastic Dynamics in Computational Biology by : Stefanie Winkelmann
Download or read book Stochastic Dynamics in Computational Biology written by Stefanie Winkelmann and published by Springer Nature. This book was released on 2021-01-04 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Statistical Methods for Spatio-Temporal Systems by : Barbel Finkenstadt
Download or read book Statistical Methods for Spatio-Temporal Systems written by Barbel Finkenstadt and published by CRC Press. This book was released on 2006-10-20 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Methods for Spatio-Temporal Systems presents current statistical research issues on spatio-temporal data modeling and will promote advances in research and a greater understanding between the mechanistic and the statistical modeling communities. Contributed by leading researchers in the field, each self-contained chapter starts w
Book Synopsis Stochastic Approaches for Systems Biology by : Mukhtar Ullah
Download or read book Stochastic Approaches for Systems Biology written by Mukhtar Ullah and published by Springer Science & Business Media. This book was released on 2011-07-12 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Classical and Spatial Stochastic Processes by : Rinaldo B. Schinazi
Download or read book Classical and Spatial Stochastic Processes written by Rinaldo B. Schinazi and published by Springer. This book was released on 2014-09-27 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: The revised and expanded edition of this textbook presents the concepts and applications of random processes with the same illuminating simplicity as its first edition, but with the notable addition of substantial modern material on biological modeling. While still treating many important problems in fields such as engineering and mathematical physics, the book also focuses on the highly relevant topics of cancerous mutations, influenza evolution, drug resistance, and immune response. The models used elegantly apply various classical stochastic models presented earlier in the text, and exercises are included throughout to reinforce essential concepts. The second edition of Classical and Spatial Stochastic Processes is suitable as a textbook for courses in stochastic processes at the advanced-undergraduate and graduate levels, or as a self-study resource for researchers and practitioners in mathematics, engineering, physics, and mathematical biology. Reviews of the first edition: An appetizing textbook for a first course in stochastic processes. It guides the reader in a very clever manner from classical ideas to some of the most interesting modern results. ... All essential facts are presented with clear proofs, illustrated by beautiful examples. ... The book is well organized, has informative chapter summaries, and presents interesting exercises. The clear proofs are concentrated at the ends of the chapters making it easy to find the results. The style is a good balance of mathematical rigorosity and user-friendly explanation. —Biometric Journal This small book is well-written and well-organized. ... Only simple results are treated ... but at the same time many ideas needed for more complicated cases are hidden and in fact very close. The second part is a really elementary introduction to the area of spatial processes. ... All sections are easily readable and it is rather tentative for the reviewer to learn them more deeply by organizing a course based on this book. The reader can be really surprised seeing how simple the lectures on these complicated topics can be. At the same time such important questions as phase transitions and their properties for some models and the estimates for certain critical values are discussed rigorously. ... This is indeed a first course on stochastic processes and also a masterful introduction to some modern chapters of the theory. —Zentralblatt Math
Book Synopsis Stochastic Dynamics for Systems Biology by : Christian Mazza
Download or read book Stochastic Dynamics for Systems Biology written by Christian Mazza and published by CRC Press. This book was released on 2016-04-19 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Deterministic Versus Stochastic Modelling in Biochemistry and Systems Biology by : Paola Lecca
Download or read book Deterministic Versus Stochastic Modelling in Biochemistry and Systems Biology written by Paola Lecca and published by Elsevier. This book was released on 2013-04-09 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Stochastic Modelling for Systems Biology by : Darren James Wilkinson
Download or read book Stochastic Modelling for Systems Biology written by Darren James Wilkinson and published by . This book was released on 2012 with total page 360 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. 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.
Book Synopsis Stochastic Models in Biology by : Narendra S. Goel
Download or read book Stochastic Models in Biology written by Narendra S. Goel and published by Elsevier. This book was released on 2013-10-22 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Spatiotemporal Models in Biological and Artificial Systems by : Fernando L. Silva
Download or read book Spatiotemporal Models in Biological and Artificial Systems written by Fernando L. Silva and published by IOS Press. This book was released on 1997 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatiotemporal models are emerging as a very important topic in several disciplines, including neurobiology and artificial neural networks. Many hard problems exist in this area. Examples include understanding the capabilities of nonlinear dynamical systems on a lattice and of networks of spiking neurons (both natural and artificial), training such systems, implementing them in hardware, understanding biological signals like the EEG, etc. Besides the state-of-the-art in the area of spatiotemporal models, the book also covers the neurobiological, and the artificial systems communities.
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.
Book Synopsis Stochastic Biomathematical Models by : Mostafa Bachar
Download or read book Stochastic Biomathematical Models written by Mostafa Bachar and published by Springer. This book was released on 2012-10-19 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Spatial Dynamics and Pattern Formation in Biological Populations by : Ranjit Kumar Upadhyay
Download or read book Spatial Dynamics and Pattern Formation in Biological Populations written by Ranjit Kumar Upadhyay and published by Chapman & Hall/CRC. This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides an introduction to deterministic (and some stochastic) modeling of spatiotemporal phenomena in ecology, epidemiology, and neural systems. A survey of the classical models in the fields with up to date applications is given. The book begins with detailed description of how spatial dynamics/diffusive processes influence the dynamics of biological populations. These processes play a key role in understanding the outbreak and spread of pandemics which help us in designing the control strategies from the public health perspective. A brief discussion on the functional mechanism of the brain (single neuron models and network level) with classical models of neuronal dynamics in space and time is given. Relevant phenomena and existing modeling approaches in ecology, epidemiology and neuroscience are introduced, which provide examples of pattern formation in these models. The analysis of patterns enables us to study the dynamics of macroscopic and microscopic behaviour of underlying systems and travelling wave type patterns observed in dispersive systems. Moving on to virus dynamics, authors present a detailed analysis of different types models of infectious diseases including two models for influenza, five models for Ebola virus and seven models for Zika virus with diffusion and time delay. A Chapter is devoted for the study of Brain Dynamics (Neural systems in space and time). Significant advances made in modeling the reaction-diffusion systems are presented and spatiotemporal patterning in the systems is reviewed. Development of appropriate mathematical models and detailed analysis (such as linear stability, weakly nonlinear analysis, bifurcation analysis, control theory, numerical simulation) are presented. Key Features Covers the fundamental concepts and mathematical skills required to analyse reaction-diffusion models for biological populations. Concepts are introduced in such a way that readers with a basic knowledge of differential equations and numerical methods can understand the analysis. The results are also illustrated with figures. Focuses on mathematical modeling and numerical simulations using basic conceptual and classic models of population dynamics, Virus and Brain dynamics. Covers wide range of models using spatial and non-spatial approaches. Covers single, two and multispecies reaction-diffusion models from ecology and models from bio-chemistry. Models are analysed for stability of equilibrium points, Turing instability, Hopf bifurcation and pattern formations. Uses Mathematica for problem solving and MATLAB for pattern formations. Contains solved Examples and Problems in Exercises. The Book is suitable for advanced undergraduate, graduate and research students. For those who are working in the above areas, it provides information from most of the recent works. The text presents all the fundamental concepts and mathematical skills needed to build models and perform analyses.
Book Synopsis Handbook of Systems Biology by : Marian Walhout
Download or read book Handbook of Systems Biology written by Marian Walhout and published by Academic Press. This book was released on 2012-12-31 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an entry point into Systems Biology for researchers in genetics, molecular biology, cell biology, microbiology and biomedical science to understand the key concepts to expanding their work. Chapters organized around broader themes of Organelles and Organisms, Systems Properties of Biological Processes, Cellular Networks, and Systems Biology and Disease discuss the development of concepts, the current applications, and the future prospects. Emphasis is placed on concepts and insights into the multi-disciplinary nature of the field as well as the importance of systems biology in human biological research. Technology, being an extremely important aspect of scientific progress overall, and in the creation of new fields in particular, is discussed in 'boxes' within each chapter to relate to appropriate topics. 2013 Honorable Mention for Single Volume Reference in Science from the Association of American Publishers' PROSE Awards Emphasizes the interdisciplinary nature of systems biology with contributions from leaders in a variety of disciplines Includes the latest research developments in human and animal models to assist with translational research Presents biological and computational aspects of the science side-by-side to facilitate collaboration between computational and biological researchers
Book Synopsis Spatiotemporal Patterns in Ecology and Epidemiology by : Horst Malchow
Download or read book Spatiotemporal Patterns in Ecology and Epidemiology written by Horst Malchow and published by Chapman & Hall/CRC. This book was released on 2019-12-18 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although the spatial dimension of ecosystem dynamics is now widely recognized, the specific mechanisms behind species patterning in space are still poorly understood and the corresponding theoretical framework is underdeveloped. Going beyond the classical Turing scenario of pattern formation, Spatiotemporal Patterns in Ecology and Epidemiology: Theory, Models, and Simulation illustrates how mathematical modeling and numerical simulations can lead to greater understanding of these issues. It takes a unified approach to population dynamics and epidemiology by presenting several ecoepidemiological models where both the basic interspecies interactions of population dynamics and the impact of an infectious disease are explicitly considered. The book first describes relevant phenomena in ecology and epidemiology, provides examples of pattern formation in natural systems, and summarizes existing modeling approaches. The authors then explore nonspatial models of population dynamics and epidemiology. They present the main scenarios of spatial and spatiotemporal pattern formation in deterministic models of population dynamics. The book also addresses the interaction between deterministic and stochastic processes in ecosystem and epidemic dynamics, discusses the corresponding modeling approaches, and examines how noise and stochasticity affect pattern formation. Reviewing the significant progress made in understanding spatiotemporal patterning in ecological and epidemiological systems, this resource shows that mathematical modeling and numerical simulations are effective tools in the study of population ecology and epidemiology.
