Dynamic Systems Biology Modeling and Simulation

Author: Joseph DiStefano III
Publisher: Academic Press
ISBN: 9780124104938
Release Date: 2015-01-10
Genre: Science

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]

Mathematical Modeling in Systems Biology

Author: Brian P. Ingalls
Publisher: MIT Press
ISBN: 9780262018883
Release Date: 2013-07-05
Genre: Science

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.

Systems Biology Simulation of Dynamic Network States

Author: Bernhard Ø. Palsson
Publisher: Cambridge University Press
ISBN: 9781139495424
Release Date: 2011-05-26
Genre: Science

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.

Measurements Modelling and Simulation of Dynamic Systems

Author: Edward Layer
Publisher: Springer Science & Business Media
ISBN: 364204588X
Release Date: 2009-12-30
Genre: Mathematics

The development and use of models of various objects is becoming a more common practice in recent days. This is due to the ease with which models can be developed and examined through the use of computers and appropriate software. Of those two, the former - high-speed computers - are easily accessible nowadays, and the latter - existing programs - are being updated almost continuously, and at the same time new powerful software is being developed. Usually a model represents correlations between some processes and their interactions, with better or worse quality of representation. It details and characterizes a part of the real world taking into account a structure of phenomena, as well as quantitative and qualitative relations. There are a great variety of models. Modelling is carried out in many diverse fields. All types of natural phenomena in the area of biology, ecology and medicine are possible subjects for modelling. Models stand for and represent technical objects in physics, chemistry, engineering, social events and behaviours in sociology, financial matters, investments and stock markets in economy, strategy and tactics, defence, security and safety in military fields. There is one common point for all models. We expect them to fulfil the validity of prediction. It means that through the analysis of models it is possible to predict phenomena, which may occur in a fragment of the real world represented by a given model. We also expect to be able to predict future reactions to signals from the outside world.

A First Course in Systems Biology

Author: Eberhard Voit
Publisher: Garland Science
ISBN: 9781351332941
Release Date: 2017-09-05
Genre: Computers

A First Course in Systems Biology is an introduction for advanced undergraduate and graduate students to the growing field of systems biology. Its main focus is the development of computational models and their applications to diverse biological systems. The book begins with the fundamentals of modeling, then reviews features of the molecular inventories that bring biological systems to life and discusses case studies that represent some of the frontiers in systems biology and synthetic biology. In this way, it provides the reader with a comprehensive background and access to methods for executing standard systems biology tasks, understanding the modern literature, and launching into specialized courses or projects that address biological questions using theoretical and computational means. New topics in this edition include: default modules for model design, limit cycles and chaos, parameter estimation in Excel, model representations of gene regulation through transcription factors, derivation of the Michaelis-Menten rate law from the original conceptual model, different types of inhibition, hysteresis, a model of differentiation, system adaptation to persistent signals, nonlinear nullclines, PBPK models, and elementary modes. The format is a combination of instructional text and references to primary literature, complemented by sets of small-scale exercises that enable hands-on experience, and large-scale, often open-ended questions for further reflection.

Systems Biology

Author: Edda Klipp
Publisher: John Wiley & Sons
ISBN: 9783527336364
Release Date: 2016-06-27
Genre: Medical

This advanced textbook is tailored for an introductory course in Systems Biology and is well-suited for biologists as well as engineers and computer scientists. It comes with student-friendly reading lists and a companion website featuring a short exam prep version of the book and educational modeling programs. The text is written in an easily accessible style and includes numerous worked examples and study questions in each chapter. For this edition, a section on medical systems biology has been included.

Computational Systems Biology

Author: Paola Lecca
Publisher: Woodhead Publishing
ISBN: 9780081001158
Release Date: 2016-07-29
Genre: Science

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

Computational Systems Biology

Author: Andres Kriete
Publisher: Academic Press
ISBN: 9780124059382
Release Date: 2013-11-26
Genre: Computers

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.

Kinetic Modelling in Systems Biology

Author: Oleg Demin
Publisher: CRC Press
ISBN: 1420011669
Release Date: 2008-10-24
Genre: Mathematics

With more and more interest in how components of biological systems interact, it is important to understand the various aspects of systems biology. Kinetic Modelling in Systems Biology focuses on one of the main pillars in the future development of systems biology. It explores both the methods and applications of kinetic modeling in this emerging field. The book introduces the basic biological cellular network concepts in the context of cellular functioning, explains the main aspects of the Edinburgh Pathway Editor (EPE) software package, and discusses the process of constructing and verifying kinetic models. It presents the features, user interface, and examples of DBSolve as well as the principles of modeling individual enzymes and transporters. The authors describe how to construct kinetic models of intracellular systems on the basis of models of individual enzymes. They also illustrate how to apply the principles of kinetic modeling to collect all available information on the energy metabolism of whole organelles, construct a kinetic model, and predict the response of the organelle to changes in external conditions. The final chapter focuses on applications of kinetic modeling in biotechnology and biomedicine. Encouraging readers to think about future challenges, this book will help them understand the kinetic modeling approach and how to apply it to solve real-life problems. CD-ROM Features Extensively used throughout the text for pathway visualization and illustration, the EPE software is available on the accompanying CD-ROM. The CD also includes pathway diagrams in several graphical formats, DBSolve installation with examples, and all models from the book with dynamic visualization of simulation results, allowing readers to perform in silico simulations and use the models as templates for further applications.

Systems Biology

Author: Andreas Kremling
Publisher: CRC Press
ISBN: 9781466567894
Release Date: 2013-11-12
Genre: Mathematics

Drawing on the latest research in the field, Systems Biology: Mathematical Modeling and Model Analysis presents many methods for modeling and analyzing biological systems, in particular cellular systems. It shows how to use predictive mathematical models to acquire and analyze knowledge about cellular systems. It also explores how the models are systematically applied in biotechnology. The first part of the book introduces biological basics, such as metabolism, signaling, gene expression, and control as well as mathematical modeling fundamentals, including deterministic models and thermodynamics. The text also discusses linear regression methods, explains the differences between linear and nonlinear regression, and illustrates how to determine input variables to improve estimation accuracy during experimental design. The second part covers intracellular processes, including enzymatic reactions, polymerization processes, and signal transduction. The author highlights the process–function–behavior sequence in cells and shows how modeling and analysis of signal transduction units play a mediating role between process and function. The third part presents theoretical methods that address the dynamics of subsystems and the behavior near a steady state. It covers techniques for determining different time scales, sensitivity analysis, structural kinetic modeling, and theoretical control engineering aspects, including a method for robust control. It also explores frequent patterns (motifs) in biochemical networks, such as the feed-forward loop in the transcriptional network of E. coli. Moving on to models that describe a large number of individual reactions, the last part looks at how these cellular models are used in biotechnology. The book also explains how graphs can illustrate the link between two components in large networks with several interactions.

Models of Life

Author: Kim Sneppen
Publisher: Cambridge University Press
ISBN: 9781107061903
Release Date: 2014-10-02
Genre: Science

An overview of current models of biological systems, reflecting the major advances that have been made over the past decade.

Discrete Event Modeling and Simulation

Author: Gabriel A. Wainer
Publisher: CRC Press
ISBN: 142007234X
Release Date: 2016-04-19
Genre: Technology & Engineering

Collecting the work of the foremost scientists in the field, Discrete-Event Modeling and Simulation: Theory and Applications presents the state of the art in modeling discrete-event systems using the discrete-event system specification (DEVS) approach. It introduces the latest advances, recent extensions of formal techniques, and real-world examples of various applications. The book covers many topics that pertain to several layers of the modeling and simulation architecture. It discusses DEVS model development support and the interaction of DEVS with other methodologies. It describes different forms of simulation supported by DEVS, the use of real-time DEVS simulation, the relationship between DEVS and graph transformation, the influence of DEVS variants on simulation performance, and interoperability and composability with emphasis on DEVS standardization. The text also examines extensions to DEVS, new formalisms, and abstractions of DEVS models as well as the theory and analysis behind real-world system identification and control. To support the generation and search of optimal models of a system, a framework is developed based on the system entity structure and its transformation to DEVS simulation models. In addition, the book explores numerous interesting examples that illustrate the use of DEVS to build successful applications, including optical network-on-chip, construction/building design, process control, workflow systems, and environmental models. A one-stop resource on advances in DEVS theory, applications, and methodology, this volume offers a sampling of the best research in the area, a broad picture of the DEVS landscape, and trend-setting applications enabled by the DEVS approach. It provides the basis for future research discoveries and encourages the development of new applications.

Fundamentals of Systems Biology

Author: Markus W. Covert
Publisher: CRC Press
ISBN: 9781498728478
Release Date: 2014-12-19
Genre: Technology & Engineering

For decades biology has focused on decoding cellular processes one gene at a time, but many of the most pressing biological questions, as well as diseases such as cancer and heart disease, are related to complex systems involving the interaction of hundreds, or even thousands, of gene products and other factors. How do we begin to understand this complexity? Fundamentals of Systems Biology: From Synthetic Circuits to Whole-cell Models introduces students to methods they can use to tackle complex systems head-on, carefully walking them through studies that comprise the foundation and frontier of systems biology. The first section of the book focuses on bringing students quickly up to speed with a variety of modeling methods in the context of a synthetic biological circuit. This innovative approach builds intuition about the strengths and weaknesses of each method and becomes critical in the book’s second half, where much more complicated network models are addressed—including transcriptional, signaling, metabolic, and even integrated multi-network models. The approach makes the work much more accessible to novices (undergraduates, medical students, and biologists new to mathematical modeling) while still having much to offer experienced modelers--whether their interests are microbes, organs, whole organisms, diseases, synthetic biology, or just about any field that investigates living systems.

Biological Modeling and Simulation

Author: Russell Schwartz
Publisher: MIT Press
ISBN: 9780262303392
Release Date: 2008-07-25
Genre: Science

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.

Analysis of Biological Systems

Author: Corrado Priami
Publisher: World Scientific
ISBN: 9781783266890
Release Date: 2015-01-29
Genre: Science

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