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Author: Joseph DiStefano III Publisher: Academic Press ISBN: 0124104932 Category : Science Languages : en Pages : 884
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; 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]
Author: Joseph DiStefano III Publisher: Academic Press ISBN: 0124104932 Category : Science Languages : en Pages : 884
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; 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]
Author: Jinzhi Lei Publisher: Springer Nature ISBN: 3030730336 Category : Mathematics Languages : en Pages : 308
Book Description
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.
Author: Joseph Distefano, 3rd Publisher: ISBN: 9781733495004 Category : Languages : en Pages : 354
Book Description
This textbook is uniquely crafted for use in teaching undergraduate students in the life, math, computer and other sciences and engineering. It is INTRODUCTORY LEVEL, for students who have taken or are currently completing their undergraduate math requirements, and are acquiring analytical-thinking and doing skills, along with introductory biology, chemistry and physics subject matter. It's about learning HOW to model and simulate dynamic biological systems, which also makes it useful for graduate students and professional researchers who want a more rigorous treatment of introductory life science math modeling, integrated with the biology. It brings together the multidisciplinary pedagogy of these subjects into a SINGLE INTRODUCTORY MODELING METHODOLOGY COURSE, crystalizing the experience of an author who has been teaching dynamic biosystems modeling and simulation methodology for the life sciences for more than 50 years. DiStefano maximizes accessibility and "systems-math-biology" integration - without diminishing conceptual rigor. Minimally essential applied math and SYSTEMS ENGINEERING METHODS are included, along with a synopsis of the biology and physiology underlying dynamic biosystem modeling, all in a modeling pedagogy context. This textbook fills a major need in the training of contemporary biology students.Dynamic biosystems modeling methodology is presented over 12 distinctive chapters, primarily with systems diagrams and simple differential equations and algebra for expressing them quantitatively, integrated with the biology. Solving and analyzing (quantifying) the biomodels are then accomplished by simulation, using a facile control system simulation language Simulink, a GUI/Matlab toolbox that emulates control systems diagramming, rather than by "coding" the model in a standard computer programming language. Students see and work with the system model - not the code - a big plus. Higher math and complex analytical solutions are avoided.Each chapter begins with a list of LEARNING GOALS, to help with both perspective for the chapter material, and retrospective, to measure learning. EXERCISES for the student at the end of each chapter are designed to test and reinforce learning. A SOLUTIONS MANUAL for chapter exercises is available to qualified instructors from the author, as are LECTURE SLIDES and LAB ASSIGNMENTS AND SOLUTIONS, for courses that adopt the textbook for student use.
Author: Russell Schwartz Publisher: MIT Press ISBN: 0262303396 Category : Science Languages : en Pages : 403
Book Description
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: Bruce Hannon Publisher: Springer ISBN: 3319056158 Category : Science Languages : en Pages : 434
Book Description
Many biologists and ecologists have developed models that find widespread use in theoretical investigations and in applications to organism behavior, disease control, population and metapopulation theory, ecosystem dynamics, and environmental management. This book captures and extends the process of model development by concentrating on the dynamic aspects of these processes and by providing the tools such that virtually anyone with basic knowledge in the Life Sciences can develop meaningful dynamic models. Examples of the systems modeled in the book range from models of cell development, the beating heart, the growth and spread of insects, spatial competition and extinction, to the spread and control of epidemics, including the conditions for the development of chaos. Key features: - easy-to-learn and easy-to-use software - examples from many subdisciplines of biology, covering models of cells, organisms, populations, and metapopulations - no prior computer or programming experience required Key benefits: - learn how to develop modeling skills and system thinking on your own rather than use models developed by others - be able to easily run models under alternative assumptions and investigate the implications of these assumptions for the dynamics of the biological system being modeled - develop skills to assess the dynamics of biological systems
Author: Andres Kriete Publisher: Academic Press ISBN: 0124059384 Category : Computers Languages : en Pages : 548
Book Description
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.
Author: Edward Layer Publisher: Springer Science & Business Media ISBN: 364204588X Category : Technology & Engineering Languages : en Pages : 156
Book Description
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.
Author: Joseph Distefano, 3rd Publisher: Biomodeling ISBN: 9781733495028 Category : Languages : en Pages : 354
Book Description
This textbook is uniquely crafted for use in teaching undergraduate students in the life, math, computer and other sciences and engineering. It is INTRODUCTORY LEVEL, for students who have taken or are currently completing their undergraduate math requirements, and are acquiring analytical-thinking and doing skills, along with introductory biology, chemistry and physics subject matter. It's about learning HOW to model and simulate dynamic biological systems, which also makes it useful for graduate students and professional researchers who want a more rigorous treatment of introductory life science math modeling, integrated with the biology. It brings together the multidisciplinary pedagogy of these subjects into a SINGLE INTRODUCTORY MODELING METHODOLOGY COURSE, crystalizing the experience of an author who has been teaching dynamic biosystems modeling and simulation methodology for the life sciences for more than 50 years. DiStefano maximizes accessibility and "systems-math-biology" integration - without diminishing conceptual rigor. Minimally essential applied math and SYSTEMS ENGINEERING METHODS are included, along with a synopsis of the biology and physiology underlying dynamic biosystem modeling, all in a modeling pedagogy context. This textbook fills a major need in the training of contemporary biology students.Dynamic biosystems modeling methodology is presented over 12 distinctive chapters, primarily with systems diagrams and simple differential equations and algebra for expressing them quantitatively, integrated with the biology. Solving and analyzing (quantifying) the biomodels are then accomplished by simulation, using a facile control system simulation language Simulink, a GUI/Matlab toolbox that emulates control systems diagramming, rather than by "coding" the model in a standard computer programming language. Students see and work with the system model - not the code - a big plus. Higher math and complex analytical solutions are avoided.Each chapter begins with a list of LEARNING GOALS, to help with both perspective for the chapter material, and retrospective, to measure learning. EXERCISES for the student at the end of each chapter are designed to test and reinforce learning. A SOLUTIONS MANUAL for chapter exercises is available to qualified instructors from the author, as are LECTURE SLIDES and LAB ASSIGNMENTS AND SOLUTIONS, for courses that adopt the textbook for student use.
Author: Harold Klee Publisher: CRC Press ISBN: 1498787789 Category : Mathematics Languages : en Pages : 852
Book Description
Continuous-system simulation is an increasingly important tool for optimizing the performance of real-world systems. The book presents an integrated treatment of continuous simulation with all the background and essential prerequisites in one setting. It features updated chapters and two new sections on Black Swan and the Stochastic Information Packet (SIP) and Stochastic Library Units with Relationships Preserved (SLURP) Standard. The new edition includes basic concepts, mathematical tools, and the common principles of various simulation models for different phenomena, as well as an abundance of case studies, real-world examples, homework problems, and equations to develop a practical understanding of concepts.
Author: Lennart Ljung Publisher: Prentice Hall ISBN: 9780135970973 Category : Computer simulation Languages : en Pages : 0
Book Description
Written by a recognized authority in the field of identification and control, this book draws together into a single volume the important aspects of system identification AND physical modelling. KEY TOPICS: Explores techniques used to construct mathematical models of systems based on knowledge from physics, chemistry, biology, etc. (e.g., techniques with so called bond-graphs, as well those which use computer algebra for the modeling work). Explains system identification techniques used to infer knowledge about the behavior of dynamic systems based on observations of the various input and output signals that are available for measurement. Shows how both types of techniques need to be applied in any given practical modeling situation. Considers applications, primarily simulation. MARKET: For practicing engineers who are faced with problems of modeling.
Author: Joseph DiStefano III
Author: Joseph DiStefano III
Author: Jinzhi Lei
Author: Joseph Distefano, 3rd
Author: Russell Schwartz
Author: Bruce Hannon
Author: Andres Kriete
Author: Edward Layer
Author: Joseph Distefano, 3rd
Author: Harold Klee
Author: Lennart Ljung