Stochastic Processes Multiscale Modeling And Numerical Methods For Computational Cellular Biology

Download Stochastic Processes Multiscale Modeling And Numerical Methods For Computational Cellular Biology full books in PDF, epub, and Kindle. Read online Stochastic Processes Multiscale Modeling And Numerical Methods For Computational Cellular Biology ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

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)

DOWNLOAD NOW!

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.

Stochastic Processes in Cell Biology

Author : Paul C. Bressloff
Publisher : Springer Nature
ISBN 13 : 3030725197
Total Pages : 724 pages
Book Rating : 4.0/5 (37 download)

DOWNLOAD NOW!

Book Synopsis Stochastic Processes in Cell Biology by : Paul C. Bressloff

Download or read book Stochastic Processes in Cell Biology written by Paul C. Bressloff and published by Springer Nature. This book was released on 2022-01-10 with total page 724 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Stochastic Processes in Cell Biology

Author : Paul C. Bressloff
Publisher : Springer Nature
ISBN 13 : 3030725154
Total Pages : 773 pages
Book Rating : 4.0/5 (37 download)

DOWNLOAD NOW!

Book Synopsis Stochastic Processes in Cell Biology by : Paul C. Bressloff

Download or read book Stochastic Processes in Cell Biology written by Paul C. Bressloff and published by Springer Nature. This book was released on 2022-01-04 with total page 773 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Analytic Methods for Coagulation-Fragmentation Models, Volume II

Author : Jacek Banasiak
Publisher : CRC Press
ISBN 13 : 1000001318
Total Pages : 322 pages
Book Rating : 4.0/5 ( download)

DOWNLOAD NOW!

Book Synopsis Analytic Methods for Coagulation-Fragmentation Models, Volume II by : Jacek Banasiak

Download or read book Analytic Methods for Coagulation-Fragmentation Models, Volume II written by Jacek Banasiak and published by CRC Press. This book was released on 2019-09-05 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analytic Methods for Coagulation-Fragmentation Models is a two-volume set that provides a comprehensive exposition of the mathematical analysis of coagulation-fragmentation models. Initially, an in-depth survey of coagulation-fragmentation processes is presented, together with an account of relevant early results obtained on the associated model equations. These provide motivation for the subsequent detailed treatment of more up-to-date investigations which have led to significant theoretical developments on topics such as solvability and the long-term behaviour of solutions. To make the account as self-contained as possible, the mathematical tools that feature prominently in these modern treatments are introduced at appropriate places. The main theme of Volume I is the analysis of linear fragmentation models, with Volume II devoted to processes that involve the nonlinear contribution of coagulation. Features of Volume II: A primer on weak compactness in L 1 and dynamical systems A comprehensive theory of solvability of the coagulation-fragmentation equation by both the semigroup and weak compactness methods, including a thorough analysis of the gelation and shattering phenomena A detailed analysis of the long-term dynamics of the coagulation-fragmentation equations with a state-of-the-art discussion on self-similar solutions

From Data to Models and Back

Author : Juliana Bowles
Publisher : Springer Nature
ISBN 13 : 3031160118
Total Pages : 199 pages
Book Rating : 4.0/5 (311 download)

DOWNLOAD NOW!

Book Synopsis From Data to Models and Back by : Juliana Bowles

Download or read book From Data to Models and Back written by Juliana Bowles and published by Springer Nature. This book was released on 2022-10-14 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th International Symposium "From Data Models and Back", DataMod 2021, which was held virtually during December 6-7, 2021, as a satellite event of SEFM 2021. The 9 full papers and 1 short paper included in this book were carefully reviewed and selected from 12 submissions. They were organized in topical sections as follows: Model verification; data mining and processing related approaches; and other approaches.

Stochastic Narrow Escape in Molecular and Cellular Biology

Author : David Holcman
Publisher : Springer
ISBN 13 : 1493931032
Total Pages : 259 pages
Book Rating : 4.4/5 (939 download)

DOWNLOAD NOW!

Book Synopsis Stochastic Narrow Escape in Molecular and Cellular Biology by : David Holcman

Download or read book Stochastic Narrow Escape in Molecular and Cellular Biology written by David Holcman and published by Springer. This book was released on 2015-09-08 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers recent developments in the non-standard asymptotics of the mathematical narrow escape problem in stochastic theory, as well as applications of the narrow escape problem in cell biology. The first part of the book concentrates on mathematical methods, including advanced asymptotic methods in partial equations, and is aimed primarily at applied mathematicians and theoretical physicists who are interested in biological applications. The second part of the book is intended for computational biologists, theoretical chemists, biochemists, biophysicists, and physiologists. It includes a summary of output formulas from the mathematical portion of the book and concentrates on their applications in modeling specific problems in theoretical molecular and cellular biology. Critical biological processes, such as synaptic plasticity and transmission, activation of genes by transcription factors, or double-strained DNA break repair, are controlled by diffusion in structures that have both large and small spatial scales. These may be small binding sites inside or on the surface of the cell, or narrow passages between subcellular compartments. The great disparity in spatial scales is the key to controlling cell function by structure. This volume reports recent progress on resolving analytical and numerical difficulties in extracting properties from experimental data, biophysical models, and from Brownian dynamics simulations of diffusion in multi-scale structures.

Stochastic Modelling for Systems Biology, Second Edition

Author : Darren J. Wilkinson
Publisher : CRC Press
ISBN 13 : 1439837724
Total Pages : 365 pages
Book Rating : 4.4/5 (398 download)

DOWNLOAD NOW!

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.

Research in Multidisciplinary Subjects (Volume- 5)

Author : Chief Editor- Biplab Auddya, Editor- Dr. Darshanam Vijaykumar, Advitya Khurana, Dr. S.Amutha, Dr. Kavita Jaidiya, Dr. Jayesh Manjrekar, Dr. L Malleswara Rao, Mr. Sugeet Sethi
Publisher : The Hill Publication
ISBN 13 : 8196477635
Total Pages : 153 pages
Book Rating : 4.1/5 (964 download)

DOWNLOAD NOW!

Book Synopsis Research in Multidisciplinary Subjects (Volume- 5) by : Chief Editor- Biplab Auddya, Editor- Dr. Darshanam Vijaykumar, Advitya Khurana, Dr. S.Amutha, Dr. Kavita Jaidiya, Dr. Jayesh Manjrekar, Dr. L Malleswara Rao, Mr. Sugeet Sethi

Download or read book Research in Multidisciplinary Subjects (Volume- 5) written by Chief Editor- Biplab Auddya, Editor- Dr. Darshanam Vijaykumar, Advitya Khurana, Dr. S.Amutha, Dr. Kavita Jaidiya, Dr. Jayesh Manjrekar, Dr. L Malleswara Rao, Mr. Sugeet Sethi and published by The Hill Publication. This book was released on 2023-09-14 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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)

DOWNLOAD NOW!

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.

Network Bioscience, 2nd Edition

Author : Marco Pellegrini
Publisher : Frontiers Media SA
ISBN 13 : 288963650X
Total Pages : 270 pages
Book Rating : 4.8/5 (896 download)

DOWNLOAD NOW!

Book Synopsis Network Bioscience, 2nd Edition by : Marco Pellegrini

Download or read book Network Bioscience, 2nd Edition written by Marco Pellegrini and published by Frontiers Media SA. This book was released on 2020-03-27 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Network science has accelerated a deep and successful trend in research that influences a range of disciplines like mathematics, graph theory, physics, statistics, data science and computer science (just to name a few) and adapts the relevant techniques and insights to address relevant but disparate social, biological, technological questions. We are now in an era of 'big biological data' supported by cost-effective high-throughput genomic, transcriptomic, proteomic, metabolomic data collection techniques that allow one to take snapshots of the cells' molecular profiles in a systematic fashion. Moreover recently, also phenotypic data, data on diseases, symptoms, patients, etc. are being collected at nation-wide level thus giving us another source of highly related (causal) 'big data'. This wealth of data is usually modeled as networks (aka binary relations, graphs or webs) of interactions, (including protein-protein, metabolic, signaling and transcription-regulatory interactions). The network model is a key view point leading to the uncovering of mesoscale phenomena, thus providing an essential bridge between the observable phenotypes and 'omics' underlying mechanisms. Moreover, network analysis is a powerful 'hypothesis generation' tool guiding the scientific cycle of 'data gathering', 'data interpretation, 'hypothesis generation' and 'hypothesis testing'. A major challenge in contemporary research is the synthesis of deep insights coming from network science with the wealth of data (often noisy, contradictory, incomplete and difficult to replicate) so to answer meaningful biological questions, in a quantifiable way using static and dynamic properties of biological networks.

Stochastic Dynamics in Computational Biology

Author : Stefanie Winkelmann
Publisher : Springer Nature
ISBN 13 : 3030623874
Total Pages : 284 pages
Book Rating : 4.0/5 (36 download)

DOWNLOAD NOW!

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.

Multiscale Monte Carlo Methods to Cope with Separation of Scales in Stochastic Simulation of Biological Networks

Author : Asawari Samant
Publisher : ProQuest
ISBN 13 : 9780549186663
Total Pages : pages
Book Rating : 4.1/5 (866 download)

DOWNLOAD NOW!

Book Synopsis Multiscale Monte Carlo Methods to Cope with Separation of Scales in Stochastic Simulation of Biological Networks by : Asawari Samant

Download or read book Multiscale Monte Carlo Methods to Cope with Separation of Scales in Stochastic Simulation of Biological Networks written by Asawari Samant and published by ProQuest. This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The emerging paradigm of systems biology aims at gaining a quantitative understanding of the organization, dynamics and control of biological phenomena, via an iterative process of experimentation and computation. Building a close link between the system-level physiology and the underlying molecular machinery has been made possible only by the recent advances in genomic and proteomic technologies. The idea of mathematical modeling is not new to biology; however, the formal introduction of computational biology as a scientific discipline was driven by the need for an efficient and systematic way of organizing and analyzing the vast amount of information generated by high throughput experimental platforms. Currently, the field of computational biology is in its infancy and is plagued by numerous challenges. One of the key challenges facing computational biology is building and simulating hierarchical models that span multiple length and time scales. Biological systems are inherently multiscale; not only in terms of time and length scales of intracellular processes, but also in the terms of the populations of species participating in these processes. Separation of scales reduces the efficiency and speed of most dynamic and spatial simulation techniques. In this thesis, we develop a multiscale approach to circumvent the problem of numerical stiffness in stochastic simulation of well-mixed reaction networks. The focus on a stochastic framework was motivated by two factors--firstly, the presence and role of stochasticity in biological systems is a well-established experimental fact, and secondly, accelerated stochastic algorithms to deal with numerical stiffness are currently unavailable. In this work, we develop a multiscale Monte Carlo (MSMC) method to efficiently deal with computational challenges stemming from the disparity of time scales in well-mixed stochastic networks. Broadly speaking, the developed multiscale framework extends the deterministic quasi-equilibrium (QE) approximation, computational singular perturbation (CSP), and low-dimensional manifold (LDM) concepts to stochastic simulation. We address various issues to enable a seamless and probabilistically accurate algorithm. Specifically, dynamic network partitioning, on-the-fly relaxation of the fast network and numerical approximation and generation of the QE probability distribution function are some key issues addressed. Finally, incorporating the hybrid solvers enables us to deal with systems having mixed population scales in an efficient way. The modified method, called the hybrid multiscale Monte Carlo (HyMSMC) method, represents a significant improvement over the MSMC method. Especially, for stiff systems involving large populations the HyMSMC method is significantly faster than the MSMC method, as demonstrated with several examples.

Mitochondrial Genetics and Epigenetics

Author : Caterina Garone
Publisher : Frontiers Media SA
ISBN 13 : 2889662322
Total Pages : 167 pages
Book Rating : 4.8/5 (896 download)

DOWNLOAD NOW!

Book Synopsis Mitochondrial Genetics and Epigenetics by : Caterina Garone

Download or read book Mitochondrial Genetics and Epigenetics written by Caterina Garone and published by Frontiers Media SA. This book was released on 2020-12-15 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.

Transactions on Computational Systems Biology XI

Author : Ralph-Johan Back
Publisher : Springer
ISBN 13 : 3642041868
Total Pages : 335 pages
Book Rating : 4.6/5 (42 download)

DOWNLOAD NOW!

Book Synopsis Transactions on Computational Systems Biology XI by : Ralph-Johan Back

Download or read book Transactions on Computational Systems Biology XI written by Ralph-Johan Back and published by Springer. This book was released on 2009-10-01 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: This issue on Computational Models for Cell Processes is based on a workshop that took place in Turku, Finland, May 2008. The papers span a mix of approaches to systems biology, ranging from quantitative techniques to computing paradigms inspired by biology.

Dynamical Modeling of Biological Systems

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

DOWNLOAD NOW!

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.

Stochastic Modelling for Systems Biology, Third Edition

Author : Darren J. Wilkinson
Publisher : CRC Press
ISBN 13 : 135100090X
Total Pages : 384 pages
Book Rating : 4.3/5 (51 download)

DOWNLOAD NOW!

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 384 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.

Simulation Algorithms for Computational Systems Biology

Author : Luca Marchetti
Publisher : Springer
ISBN 13 : 3319631136
Total Pages : 238 pages
Book Rating : 4.3/5 (196 download)

DOWNLOAD NOW!

Book Synopsis Simulation Algorithms for Computational Systems Biology by : Luca Marchetti

Download or read book Simulation Algorithms for Computational Systems Biology written by Luca Marchetti and published by Springer. This book was released on 2017-09-27 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explains the state-of-the-art algorithms used to simulate biological dynamics. Each technique is theoretically introduced and applied to a set of modeling cases. Starting from basic simulation algorithms, the book also introduces more advanced techniques that support delays, diffusion in space, or that are based on hybrid simulation strategies. This is a valuable self-contained resource for graduate students and practitioners in computer science, biology and bioinformatics. An appendix covers the mathematical background, and the authors include further reading sections in each chapter.