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Deterministic Versus Stochastic Modelling in Biochemistry and Systems Biology

Deterministic Versus Stochastic Modelling in Biochemistry and Systems Biology
  • Author : Paola Lecca,Ian Laurenzi,Ferenc Jordan
  • Publisher :Unknown
  • Release Date :2013-04-09
  • Total pages :390
  • ISBN : 9781908818218
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Summary : 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

Computational Systems Biology

Computational Systems Biology
  • Author : Andres Kriete,Roland Eils
  • Publisher :Unknown
  • Release Date :2013-11-26
  • Total pages :548
  • ISBN : 9780124059382
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Summary : This comprehensively revised second edition of Computational Systems Biology discusses the experimental and theoretical foundations of the function of biological systems at the molecular, cellular or organismal level over temporal and spatial scales, as systems biology advances to provide clinical solutions to complex medical problems. In particular the work focuses on the engineering of biological systems and network modeling. Logical information flow aids understanding of basic building blocks of life through disease phenotypes Evolved principles gives insight into underlying organizational principles of biological organizations, and systems processes, governing functions such as adaptation or response patterns Coverage of technical tools and systems helps researchers to understand and resolve specific systems biology problems using advanced computation Multi-scale modeling on disparate scales aids researchers understanding of dependencies and constraints of spatio-temporal relationships fundamental to biological organization and function.

Stochastic Modelling for Systems Biology, Third Edition

Stochastic Modelling for Systems Biology, Third Edition
  • Author : Darren J. Wilkinson
  • Publisher :Unknown
  • Release Date :2018-12-07
  • Total pages :384
  • ISBN : 9781351000901
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Summary : 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.

Computational Systems Biology

Computational Systems Biology
  • Author : Jean-Christophe Leloup,Didier Gonze,Albert Goldbeter
  • Publisher :Unknown
  • Release Date :2013-11-26
  • Total pages :548
  • ISBN : 9780128070116
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Summary : Circadian rhythms originate from intertwined feedback processes in genetic regulatory networks. Computational models of increasing complexity have been proposed for the molecular mechanism of these rhythms, which occur spontaneously with a period on the order of 24h. We show that deterministic models for circadian rhythms in Drosophila account for a variety of dynamical properties, such as phase shifting or long-term suppression by light pulses and entrainment by light/dark cycles. Stochastic versions of these models allow us to examine how molecular noise affects the emergence and robustness of circadian oscillations. Finally, we present a deterministic model for the mammalian circadian clock and use it to address the dynamical bases of physiological disorders of the sleep/wake cycle in humans.

Synthetic Biology - a Primer (revised Edition)

Synthetic Biology - a Primer (revised Edition)
  • Author : Paul S. FREEMONT,Richard I. KITNEY
  • Publisher :Unknown
  • Release Date :2015-08-24
  • Total pages :196
  • ISBN : 9781783268801
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Summary :

Computational Systems Biology

Computational Systems Biology
  • Author : Andres Kriete,Roland Eils
  • Publisher :Unknown
  • Release Date :2005-11-10
  • Total pages :424
  • ISBN : 008045934X
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Summary : Systems Biology is concerned with the quantitative study of complex biosystems at the molecular, cellular, tissue, and systems scales. Its focus is on the function of the system as a whole, rather than on individual parts. This exciting new arena applies mathematical modeling and engineering methods to the study of biological systems. This book is the first of its kind to focus on the newly emerging field of systems biology with an emphasis on computational approaches. The work covers new concepts, methods for information storage, mining and knowledge extraction, reverse engineering of gene and metabolic networks, as well as modelling and simulation of multi-cellular systems. Central themes include strategies for predicting biological properties and methods for elucidating structure-function relationships.

Analysis of Biological Systems

Analysis of Biological Systems
  • Author : Corrado Priami,Melissa J Morine
  • Publisher :Unknown
  • Release Date :2015-01-29
  • Total pages :432
  • ISBN : 9781783266890
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Summary : Modeling is fast becoming fundamental to understanding the processes that define biological systems. High-throughput technologies are producing increasing quantities of data that require an ever-expanding toolset for their effective analysis and interpretation. Analysis of high-throughput data in the context of a molecular interaction network is particularly informative as it has the potential to reveal the most relevant network modules with respect to a phenotype or biological process of interest. Analysis of Biological Systems collects classical material on analysis, modeling and simulation, thereby acting as a unique point of reference. The joint application of statistical techniques to extract knowledge from big data and map it into mechanistic models is a current challenge of the field, and the reader will learn how to build and use models even if they have no computing or math background. An in-depth analysis of the currently available technologies, and a comparison between them, is also included. Unlike other reference books, this in-depth analysis is extended even to the field of language-based modeling. The overall result is an indispensable, self-contained and systematic approach to a rapidly expanding field of science. Contents:Algorithmic Systems BiologySetting the ContextSystems and ModelsStatic Modeling TechnologiesDynamic Modeling TechnologiesLanguage-based ModelingDynamic Modeling ProcessSimulationPerspectives and ConclusionsAppendix A: Basic MathAppendix B: Probability and StatisticsAppendix C: Semantics of Modeling Languages Readership: Graduate students in computer science, physics, mathematics or engineering or biology-related fields who want to better understand how to develop and use models of biological systems. Practitioners in systems biology who want to understand algorithmic modeling and algorithmic systems biology. Key Features:The book jointly deals with static (statistical) and dynamic (simulation) technologies making it a strong reference for who wants to approach real systems biology problemsThe content of the book is the result of more than ten years application of the material in university courses and to industrial-level problems in systems pharmacology and systems nutritionThere is no reference work available for the field of language-based modeling that is studied in depth in this bookKeywords:Modeling;Simulation;Network Analysis;Systems Biology;Systems Nutrition;Systems Pharmacology;Stochastic Models;Programming Biology;Multivariate Analysis

Theoretical Physics for Biological Systems

Theoretical Physics for Biological Systems
  • Author : Paola Lecca,Angela Re
  • Publisher :Unknown
  • Release Date :2019-01-30
  • Total pages :146
  • ISBN : 9781351374323
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Summary : Quantum physics provides the concepts and their mathematical formalization that lend themselves to describe important properties of biological networks topology, such as vulnerability to external stress and their dynamic response to changing physiological conditions. A theory of networks enhanced with mathematical concepts and tools of quantum physics opens a new area of biological physics, the one of systems biological physics.

Dynamic Systems Biology Modeling and Simulation

Dynamic Systems Biology Modeling and Simulation
  • Author : Joseph DiStefano III
  • Publisher :Unknown
  • Release Date :2015-01-10
  • Total pages :884
  • ISBN : 9780124104938
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Summary : 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]

Quantitative Biology of Metabolism

Quantitative Biology of Metabolism
  • Author : Anonim
  • Publisher :Unknown
  • Release Date :1968
  • Total pages :296
  • ISBN : OCLC:962970874
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Mathematical Modeling in Systems Biology

Mathematical Modeling in Systems Biology
  • Author : Brian P. Ingalls
  • Publisher :Unknown
  • Release Date :2013-07-05
  • Total pages :408
  • ISBN : 9780262018883
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Summary : 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.

An Introduction to Stochastic Modeling

An Introduction to Stochastic Modeling
  • Author : Howard M. Taylor,Samuel Karlin
  • Publisher :Unknown
  • Release Date :2014-05-10
  • Total pages :410
  • ISBN : 9781483269276
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Summary : An Introduction to Stochastic Modeling provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich diversity of applications of stochastic processes in the sciences. Organized into nine chapters, this book begins with an overview of diverse types of stochastic models, which predicts a set of possible outcomes weighed by their likelihoods or probabilities. This text then provides exercises in the applications of simple stochastic analysis to appropriate problems. Other chapters consider the study of general functions of independent, identically distributed, nonnegative random variables representing the successive intervals between renewals. This book discusses as well the numerous examples of Markov branching processes that arise naturally in various scientific disciplines. The final chapter deals with queueing models, which aid the design process by predicting system performance. This book is a valuable resource for students of engineering and management science. Engineers will also find this book useful.

Physics of Life

Physics of Life
  • Author : Clas Blomberg
  • Publisher :Unknown
  • Release Date :2007-10-01
  • Total pages :436
  • ISBN : 0080554644
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Summary : The purpose of the book is to give a survey of the physics that is relevant for biological applications, and also to discuss what kind of biology needs physics. The book gives a broad account of basic physics, relevant for the applications and various applications from properties of proteins to processes in the cell to wider themes such as the brain, the origin of life and evolution. It also considers general questions of common interest such as reductionism, determinism and randomness, where the physics view often is misunderstood. The subtle balance between order and disorder is a repeated theme appearing in many contexts. There are descriptive parts which shall be sufficient for the comprehension of general ideas, and more detailed, formalistic parts for those who want to go deeper, and see the ideas expressed in terms of mathematical formulas. - Describes how physics is needed for understanding basic principles of biology - Discusses the delicate balance between order and disorder in living systems - Explores how physics play a role high biological functions, such as learning and thinking

Stochastic Approach to Chemical Kinetics

Stochastic Approach to Chemical Kinetics
  • Author : Donald Allan McQuarrie
  • Publisher :Unknown
  • Release Date :1968
  • Total pages :68
  • ISBN : UOM:39015016003678
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Summary :

Control Theory and Systems Biology

Control Theory and Systems Biology
  • Author : Pablo A. Iglesias,Brian P. Ingalls
  • Publisher :Unknown
  • Release Date :2010
  • Total pages :345
  • ISBN : 9780262013345
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Summary : A survey of how engineering techniques from control and systems theory can be used tohelp biologists understand the behavior of cellular systems.

Mathematical Models in Biology

Mathematical Models in Biology
  • Author : Leah Edelstein-Keshet
  • Publisher :Unknown
  • Release Date :1988
  • Total pages :586
  • ISBN : 0898719143
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Summary : Mathematical Models in Biology is an introductory book for readers interested in biological applications of mathematics and modeling in biology. A favorite in the mathematical biology community, it shows how relatively simple mathematics can be applied to a variety of models to draw interesting conclusions. Connections are made between diverse biological examples linked by common mathematical themes. A variety of discrete and continuous ordinary and partial differential equation models are explored. Although great advances have taken place in many of the topics covered, the simple lessons contained in this book are still important and informative. Audience: the book does not assume too much background knowledge--essentially some calculus and high-school algebra. It was originally written with third- and fourth-year undergraduate mathematical-biology majors in mind; however, it was picked up by beginning graduate students as well as researchers in math (and some in biology) who wanted to learn about this field.

Systemic Approaches in Bioinformatics and Computational Systems Biology: Recent Advances

Systemic Approaches in Bioinformatics and Computational Systems Biology: Recent Advances
  • Author : Lecca, Paola
  • Publisher :Unknown
  • Release Date :2011-12-31
  • Total pages :471
  • ISBN : 9781613504369
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Summary : The convergence of biology and computer science was initially motivated by the need to organize and process a growing number of biological observations resulting from rapid advances in experimental techniques. Today, however, close collaboration between biologists, biochemists, medical researchers, and computer scientists has also generated remarkable benefits for the field of computer science. Systemic Approaches in Bioinformatics and Computational Systems Biology: Recent Advances presents new techniques that have resulted from the application of computer science methods to the organization and interpretation of biological data. The book covers three subject areas: bioinformatics, computational biology, and computational systems biology. It focuses on recent, systemic approaches in computer science and mathematics that have been used to model, simulate, and more generally, experiment with biological phenomena at any scale.

Catalyzing Inquiry at the Interface of Computing and Biology

Catalyzing Inquiry at the Interface of Computing and Biology
  • Author : National Research Council,Division on Engineering and Physical Sciences,Computer Science and Telecommunications Board,Committee on Frontiers at the Interface of Computing and Biology
  • Publisher :Unknown
  • Release Date :2006-01-01
  • Total pages :468
  • ISBN : 9780309096126
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Summary : Advances in computer science and technology and in biology over the last several years have opened up the possibility for computing to help answer fundamental questions in biology and for biology to help with new approaches to computing. Making the most of the research opportunities at the interface of computing and biology requires the active participation of people from both fields. While past attempts have been made in this direction, circumstances today appear to be much more favorable for progress. To help take advantage of these opportunities, this study was requested of the NRC by the National Science Foundation, the Department of Defense, the National Institutes of Health, and the Department of Energy. The report provides the basis for establishing cross-disciplinary collaboration between biology and computing including an analysis of potential impediments and strategies for overcoming them. The report also presents a wealth of examples that should encourage students in the biological sciences to look for ways to enable them to be more effective users of computing in their studies.

Deterministic Kinetics in Chemistry and Systems Biology

Deterministic Kinetics in Chemistry and Systems Biology
  • Author : Gábor Lente
  • Publisher :Unknown
  • Release Date :2015-03-09
  • Total pages :135
  • ISBN : 9783319154824
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Summary : This book gives a concise overview of the mathematical foundations of kinetics used in chemistry and systems biology. The analytical and numerical methods used to solve complex rate equations with the widely used deterministic approach will be described, with primary focus on practical aspects important in designing experimental studies and the evaluation of data. The introduction of personal computers transformed scientific attitudes in the last two decades considerably as computational power ceased to be a limiting factor. Despite this improvement, certain time-honored approximations in solving rate equations such as the pre-equilibrium or the steady-state approach are still valid and necessary as they concern the information content of measured kinetic traces. The book shows the role of these approximations in modern kinetics and will also describe some common misconceptions in this field.

Mathematical Modeling of Random and Deterministic Phenomena

Mathematical Modeling of Random and Deterministic Phenomena
  • Author : Solym Mawaki Manou-Abi,Sophie Dabo-Niang,Jean-Jacques Salone
  • Publisher :Unknown
  • Release Date :2020-03-17
  • Total pages :350
  • ISBN : 9781786304544
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Summary : This book highlights mathematical research interests that appear in real life, such as the study and modeling of random and deterministic phenomena. As such, it provides current research in mathematics, with applications in biological and environmental sciences, ecology, epidemiology and social perspectives. The chapters can be read independently of each other, with dedicated references specific to each chapter. The book is organized in two main parts. The first is devoted to some advanced mathematical problems regarding epidemic models; predictions of biomass; space-time modeling of extreme rainfall; modeling with the piecewise deterministic Markov process; optimal control problems; evolution equations in a periodic environment; and the analysis of the heat equation. The second is devoted to a modelization with interdisciplinarity in ecological, socio-economic, epistemological, demographic and social problems. Mathematical Modeling of Random and Deterministic Phenomena is aimed at expert readers, young researchers, plus graduate and advanced undergraduate students who are interested in probability, statistics, modeling and mathematical analysis.

Feedback Control in Systems Biology

Feedback Control in Systems Biology
  • Author : Carlo Cosentino,Declan Bates
  • Publisher :Unknown
  • Release Date :2011-10-17
  • Total pages :296
  • ISBN : 9781439816905
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Summary : Like engineering systems, biological systems must also operate effectively in the presence of internal and external uncertainty—such as genetic mutations or temperature changes, for example. It is not surprising, then, that evolution has resulted in the widespread use of feedback, and research in systems biology over the past decade has shown that feedback control systems are widely found in biology. As an increasing number of researchers in the life sciences become interested in control-theoretic ideas such as feedback, stability, noise and disturbance attenuation, and robustness, there is a need for a text that explains feedback control as it applies to biological systems. Written by established researchers in both control engineering and systems biology, Feedback Control in Systems Biology explains how feedback control concepts can be applied to systems biology. Filling the need for a text on control theory for systems biologists, it provides an overview of relevant ideas and methods from control engineering and illustrates their application to the analysis of biological systems with case studies in cellular and molecular biology. Control Theory for Systems Biologists The book focuses on the fundamental concepts used to analyze the effects of feedback in biological control systems, rather than the control system design methods that form the core of most control textbooks. In addition, the authors do not assume that readers are familiar with control theory. They focus on "control applications" such as metabolic and gene-regulatory networks rather than aircraft, robots, or engines, and on mathematical models derived from classical reaction kinetics rather than classical mechanics. Another significant feature of the book is that it discusses nonlinear systems, an understanding of which is crucial for systems biologists because of the highly nonlinear nature of biological systems. The authors cover tools and techniques for the analysis of linear and nonlinear systems; negative and positive feedback; robustness analysis methods; techniques for the reverse-engineering of biological interaction networks; and the analysis of stochastic biological control systems. They also identify new research directions for control theory inspired by the dynamic characteristics of biological systems. A valuable reference for researchers, this text offers a sound starting point for scientists entering this fascinating and rapidly developing field.