Deterministic Versus Stochastic Modelling in Biochemistry and Systems Biology PDF Download

Author: Paola Lecca
Publisher: Elsevier
ISBN: 1908818212
Category : Mathematics
Languages : en
Pages : 411

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Book Description
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

Author: Paola Lecca
Publisher: Springer Nature
ISBN: 3030412555
Category : Medical
Languages : en
Pages : 90

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Book Description
This richly illustrated book presents the objectives of, and the latest techniques for, the identifiability analysis and standard and robust regression analysis of complex dynamical models. The book first provides a definition of complexity in dynamic systems by introducing readers to the concepts of system size, density of interactions, stiff dynamics, and hybrid nature of determination. In turn, it presents the mathematical foundations of and algorithmic procedures for model structural and practical identifiability analysis, multilinear and non-linear regression analysis, and best predictor selection. Although the main fields of application discussed in the book are biochemistry and systems biology, the methodologies described can also be employed in other disciplines such as physics and the environmental sciences. Readers will learn how to deal with problems such as determining the identifiability conditions, searching for an identifiable model, and conducting their own regression analysis and diagnostics without supervision. Featuring a wealth of real-world examples, exercises, and codes in R, the book addresses the needs of doctoral students and researchers in bioinformatics, bioengineering, systems biology, biophysics, biochemistry, the environmental sciences and experimental physics. Readers should be familiar with the fundamentals of probability and statistics (as provided in first-year university courses) and a basic grasp of R.

Author: Paola Lecca
Publisher: CRC Press
ISBN: 1351374311
Category : Medical
Languages : en
Pages : 105

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Book Description
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.

Author: Corrado Priami
Publisher: World Scientific
ISBN: 1783266899
Category : Science
Languages : en
Pages : 431

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Book Description
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.

Author: Johannes Müller
Publisher: Springer
ISBN: 3642272517
Category : Mathematics
Languages : en
Pages : 721

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Book Description
This book developed from classes in mathematical biology taught by the authors over several years at the Technische Universität München. The main themes are modeling principles, mathematical principles for the analysis of these models and model-based analysis of data. The key topics of modern biomathematics are covered: ecology, epidemiology, biochemistry, regulatory networks, neuronal networks and population genetics. A variety of mathematical methods are introduced, ranging from ordinary and partial differential equations to stochastic graph theory and branching processes. A special emphasis is placed on the interplay between stochastic and deterministic models.

Author: Steven I. Gordon
Publisher: CRC Press
ISBN: 1498773885
Category : Computers
Languages : en
Pages : 211

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Book Description
Introduction to Modeling and Simulation with MATLAB and Python is intended for students and professionals in science, social science, and engineering that wish to learn the principles of computer modeling, as well as basic programming skills. The book content focuses on meeting a set of basic modeling and simulation competencies that were developed as part of several National Science Foundation grants. Even though computer science students are much more expert programmers, they are not often given the opportunity to see how those skills are being applied to solve complex science and engineering problems and may also not be aware of the libraries used by scientists to create those models. The book interleaves chapters on modeling concepts and related exercises with programming concepts and exercises. The authors start with an introduction to modeling and its importance to current practices in the sciences and engineering. They introduce each of the programming environments and the syntax used to represent variables and compute mathematical equations and functions. As students gain more programming expertise, the authors return to modeling concepts, providing starting code for a variety of exercises where students add additional code to solve the problem and provide an analysis of the outcomes. In this way, the book builds both modeling and programming expertise with a "just-in-time" approach so that by the end of the book, students can take on relatively simple modeling example on their own. Each chapter is supplemented with references to additional reading, tutorials, and exercises that guide students to additional help and allows them to practice both their programming and analytical modeling skills. In addition, each of the programming related chapters is divided into two parts – one for MATLAB and one for Python. In these chapters, the authors also refer to additional online tutorials that students can use if they are having difficulty with any of the topics. The book culminates with a set of final project exercise suggestions that incorporate both the modeling and programming skills provided in the rest of the volume. Those projects could be undertaken by individuals or small groups of students. The companion website at http://www.intromodeling.com provides updates to instructions when there are substantial changes in software versions, as well as electronic copies of exercises and the related code. The website also offers a space where people can suggest additional projects they are willing to share as well as comments on the existing projects and exercises throughout the book. Solutions and lecture notes will also be available for qualifying instructors.

Author: Joseph DiStefano III
Publisher: Academic Press
ISBN: 0124104932
Category : Science
Languages : en
Pages : 886

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Book Description
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 - 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]

Author: Domitilla Del Vecchio
Publisher: Princeton University Press
ISBN: 1400850509
Category : Science
Languages : en
Pages : 287

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Book Description
This book provides an accessible introduction to the principles and tools for modeling, analyzing, and synthesizing biomolecular systems. It begins with modeling tools such as reaction-rate equations, reduced-order models, stochastic models, and specific models of important core processes. It then describes in detail the control and dynamical systems tools used to analyze these models. These include tools for analyzing stability of equilibria, limit cycles, robustness, and parameter uncertainty. Modeling and analysis techniques are then applied to design examples from both natural systems and synthetic biomolecular circuits. In addition, this comprehensive book addresses the problem of modular composition of synthetic circuits, the tools for analyzing the extent of modularity, and the design techniques for ensuring modular behavior. It also looks at design trade-offs, focusing on perturbations due to noise and competition for shared cellular resources. Featuring numerous exercises and illustrations throughout, Biomolecular Feedback Systems is the ideal textbook for advanced undergraduates and graduate students. For researchers, it can also serve as a self-contained reference on the feedback control techniques that can be applied to biomolecular systems. Provides a user-friendly introduction to essential concepts, tools, and applications Covers the most commonly used modeling methods Addresses the modular design problem for biomolecular systems Uses design examples from both natural systems and synthetic circuits Solutions manual (available only to professors at press.princeton.edu) An online illustration package is available to professors at press.princeton.edu

Author: K. Shimizu
Publisher: Elsevier
ISBN: 1908818204
Category : Science
Languages : en
Pages : 497

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Book Description
The metabolic regulation of a cell system is of critical importance in systems biology, and a robust model of these mechanisms is essential in predicting the effects on the metabolism of both the culture environment and the knockout of specific genes. Bacterial cellular metabolic systems focuses on this highly topical subject in relation to culture environment and provides a detailed analysis from gene level to metabolic level regulation, as well as offering a discussion of the most recent modelling approaches. The book begins with an introduction to metabolic mechanisms and to the metabolic regulation of a cell, before moving on to discussing the action of global regulators in response to a specific culture environment. The second half of the book examines conventional flux balance analysis and its applications, 13C-metabolic flux analysis, and the effect of a specific gene knockout on the metabolism. - Comprehensive account of metabolic regulation via global regulators in response to changes in the culture environment - Basic formulation of 13C-metabolic flux analysis based on 13C-labelling experiments - Systems biology approach for the modelling and computer simulation of the main metabolic pathways of a cell system

Author: Herbert Levine
Publisher: Academic Press
ISBN: 012817997X
Category : Medical
Languages : en
Pages : 773

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Book Description
Phenotypic Switching: Implications in Biology and Medicine provides a comprehensive examination of phenotypic switching across biological systems, including underlying mechanisms, evolutionary significance, and its role in biomedical science. Contributions from international leaders discuss conceptual and theoretical aspects of phenotypic plasticity, its influence over biological development, differentiation, biodiversity, and potential applications in cancer therapy, regenerative medicine and stem cell therapy, among other treatments. Chapters discuss fundamental mechanisms of phenotypic switching, including transition states, cell fate decisions, epigenetic factors, stochasticity, protein-based inheritance, specific areas of human development and disease relevance, phenotypic plasticity in melanoma, prostate cancer, breast cancer, non-genetic heterogeneity in cancer, hepatitis C, and more. This book is essential for active researchers, basic and translational scientists, clinicians, postgraduates and students in genetics, human genomics, pathology, bioinformatics, developmental biology, evolutionary biology and adaptive opportunities in yeast. - Thoroughly addresses the conceptual, experimental and translational aspects that underlie phenotypic plasticity - Emphasizes quantitative approaches, nonlinear dynamics, mechanistic insights and key methodologies to advance phenotypic plasticity studies - Features a diverse range of chapter contributions from international leaders in the field