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Modeling And Simulation Of Biological Networks
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Author :American Mathematical Society. Short Course, Modeling and Simulation of Biological Networks Publisher :American Mathematical Soc. ISBN 13 :0821839640 Total Pages :161 pages Book Rating :4.8/5 (218 download)
Book Synopsis Modeling and Simulation of Biological Networks by : American Mathematical Society. Short Course, Modeling and Simulation of Biological Networks
Download or read book Modeling and Simulation of Biological Networks written by American Mathematical Society. Short Course, Modeling and Simulation of Biological Networks and published by American Mathematical Soc.. This book was released on 2007 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this volume is to explain some of the biology and the computational and mathematical challenges with the modeling and simulation of biological networks. The different chapters provide examples of how these challenges are met, with particular emphasis on nontraditional mathematical approaches. The volume features a broad spectrum of networks across scales, ranging from biochemical networks within a single cell to epidemiological networks encompassing whole cities. Also, this volume is broad in the range of mathematical tools used in solving problems involving these networks.
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.
Author :American Mathematical Society. Short Course, Modeling and Simulation of Biological Networks Publisher :American Mathematical Society(RI) ISBN 13 :9780821892794 Total Pages :160 pages Book Rating :4.8/5 (927 download)
Book Synopsis Modeling and Simulation of Biological Networks by : American Mathematical Society. Short Course, Modeling and Simulation of Biological Networks
Download or read book Modeling and Simulation of Biological Networks written by American Mathematical Society. Short Course, Modeling and Simulation of Biological Networks and published by American Mathematical Society(RI). This book was released on 2014-05-10 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is the task of computational biology to help elucidate the unique characteristics of biological systems. This process has barely begun, and many researchers are testing computational tools that have been used successfully in other fields. Mathematical and statistical network modeling is an important step toward uncovering the organizational principles and dynamic behavior of biological networks. Undoubtedly, new mathematical tools will be needed, however, to meet this challenge. The workhorse of this effort at present comprises the standard tools from applied mathematics, which have proven to be successful for many problems. But new areas of mathematics not traditionally considered applicable are contributing other powerful tools. This volume is intended to introduce this topic to a broad mathematical audience. The aim is to explain some of the biology and the computational and mathematical challenges we are facing. The different chapters provide examples of how these challenges are met, with particular emphasis on nontraditional mathematical approaches.The volume features a broad spectrum of networks across scales, ranging from biochemical networks within a single cell to epidemiological networks encompassing whole cities. Chapter topics include phylogenetics and gene finding using tools from statistics and algebraic geometry, biochemical network inference using tools from computational algebra, control-theoretic approaches to drug delivery using differential equations, and interaction-based modeling and discrete mathematics applied to problems in population dynamics and epidemiology.
Book Synopsis Networks in Systems Biology by : Fabricio Alves Barbosa da Silva
Download or read book Networks in Systems Biology written by Fabricio Alves Barbosa da Silva and published by Springer Nature. This book was released on 2020-10-03 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a range of current research topics in biological network modeling, as well as its application in studies on human hosts, pathogens, and diseases. Systems biology is a rapidly expanding field that involves the study of biological systems through the mathematical modeling and analysis of large volumes of biological data. Gathering contributions from renowned experts in the field, some of the topics discussed in depth here include networks in systems biology, the computational modeling of multidrug-resistant bacteria, and systems biology of cancer. Given its scope, the book is intended for researchers, advanced students, and practitioners of systems biology. The chapters are research-oriented, and present some of the latest findings on their respective topics.
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.
Book Synopsis Computational Systems Biology by : Paola Lecca
Download or read book Computational Systems Biology written by Paola Lecca and published by Woodhead Publishing. This book was released on 2016-07-29 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Systems Biology: Inference and Modelling provides an introduction to, and overview of, network analysis inference approaches which form the backbone of the model of the complex behavior of biological systems. This book addresses the challenge to integrate highly diverse quantitative approaches into a unified framework by highlighting the relationships existing among network analysis, inference, and modeling. The chapters are light in jargon and technical detail so as to make them accessible to the non-specialist reader. The book is addressed at the heterogeneous public of modelers, biologists, and computer scientists. Provides a unified presentation of network inference, analysis, and modeling Explores the connection between math and systems biology, providing a framework to learn to analyze, infer, simulate, and modulate the behavior of complex biological systems Includes chapters in modular format for learning the basics quickly and in the context of questions posed by systems biology Offers a direct style and flexible formalism all through the exposition of mathematical concepts and biological applications
Book Synopsis Dynamics On and Of Complex Networks by : Niloy Ganguly
Download or read book Dynamics On and Of Complex Networks written by Niloy Ganguly and published by Springer Science & Business Media. This book was released on 2009-04-14 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: This self-contained book systematically explores the statistical dynamics on and of complex networks having relevance across a large number of scientific disciplines. The theories related to complex networks are increasingly being used by researchers for their usefulness in harnessing the most difficult problems of a particular discipline. The book is a collection of surveys and cutting-edge research contributions exploring the interdisciplinary relationship of dynamics on and of complex networks. Topics covered include complex networks found in nature—genetic pathways, ecological networks, linguistic systems, and social systems—as well as man-made systems such as the World Wide Web and peer-to-peer networks. The contributed chapters in this volume are intended to promote cross-fertilization in several research areas, and will be valuable to newcomers in the field, experienced researchers, practitioners, and graduate students interested in systems exhibiting an underlying complex network structure in disciplines such as computer science, biology, statistical physics, nonlinear dynamics, linguistics, and the social sciences.
Book Synopsis Artificial Higher Order Neural Networks for Modeling and Simulation by : Zhang, Ming
Download or read book Artificial Higher Order Neural Networks for Modeling and Simulation written by Zhang, Ming and published by IGI Global. This book was released on 2012-10-31 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book introduces Higher Order Neural Networks (HONNs) to computer scientists and computer engineers as an open box neural networks tool when compared to traditional artificial neural networks"--Provided by publisher.
Book Synopsis Computational Modeling of Biological Systems by : Nikolay V Dokholyan
Download or read book Computational Modeling of Biological Systems written by Nikolay V Dokholyan and published by Springer Science & Business Media. This book was released on 2012-02-12 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational modeling is emerging as a powerful new approach to study and manipulate biological systems. Multiple methods have been developed to model, visualize, and rationally alter systems at various length scales, starting from molecular modeling and design at atomic resolution to cellular pathways modeling and analysis. Higher time and length scale processes, such as molecular evolution, have also greatly benefited from new breeds of computational approaches. This book provides an overview of the established computational methods used for modeling biologically and medically relevant systems.
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.
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.
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.
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 405 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 Systems Biology: Simulation of Dynamic Network States by : Bernhard Ø. Palsson
Download or read book Systems Biology: Simulation of Dynamic Network States written by Bernhard Ø. Palsson and published by Cambridge University Press. This book was released on 2011-05-26 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biophysical models have been used in biology for decades, but they have been limited in scope and size. In this book, Bernhard Ø. Palsson shows how network reconstructions that are based on genomic and bibliomic data, and take the form of established stoichiometric matrices, can be converted into dynamic models using metabolomic and fluxomic data. The Mass Action Stoichiometric Simulation (MASS) procedure can be used for any cellular process for which data is available and allows a scalable step-by-step approach to the practical construction of network models. Specifically, it can treat integrated processes that need explicit accounting of small molecules and protein, which allows simulation at the molecular level. The material has been class-tested by the author at both the undergraduate and graduate level. All computations in the text are available online in MATLAB® and Mathematica® workbooks, allowing hands-on practice with the material.
Book Synopsis Network-Oriented Modeling by : Jan Treur
Download or read book Network-Oriented Modeling written by Jan Treur and published by Springer. This book was released on 2016-10-03 with total page 499 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a new approach that can be applied to complex, integrated individual and social human processes. It provides an alternative means of addressing complexity, better suited for its purpose than and effectively complementing traditional strategies involving isolation and separation assumptions. Network-oriented modeling allows high-level cognitive, affective and social models in the form of (cyclic) graphs to be constructed, which can be automatically transformed into executable simulation models. The modeling format used makes it easy to take into account theories and findings about complex cognitive and social processes, which often involve dynamics based on interrelating cycles. Accordingly, it makes it possible to address complex phenomena such as the integration of emotions within cognitive processes of all kinds, of internal simulations of the mental processes of others, and of social phenomena such as shared understandings and collective actions. A variety of sample models – including those for ownership of actions, fear and dreaming, the integration of emotions in joint decision-making based on empathic understanding, and evolving social networks – illustrate the potential of the approach. Dedicated software is available to support building models in a conceptual or graphical manner, transforming them into an executable format and performing simulation experiments. The majority of the material presented has been used and positively evaluated by undergraduate and graduate students and researchers in the cognitive, social and AI domains. Given its detailed coverage, the book is ideally suited as an introduction for graduate and undergraduate students in many different multidisciplinary fields involving cognitive, affective, social, biological, and neuroscience domains.
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]
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.
