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Dynamic Systems Biology Modeling and Simulation de Joseph DiStefano III

Dynamic Systems Biology Modeling and Simulation

Autor Joseph DiStefano III
en Limba Engleză Hardback – 10 ian 2015

Evoluția biologiei sistemelor în ultimele decenii a transformat disciplina dintr-o știință descriptivă într-una riguros cantitativă, o tranziție pe care Dynamic Systems Biology Modeling and Simulation o documentează și o facilitează magistral. Observăm cum autorul Joseph DiStefano III reușește să sintetizeze jumătate de secol de cercetare la UCLA într-un manual care unifică metodologiile clasice cu cele contemporane. Lucrarea nu se rezumă la teorie, ci ancorează modelarea matematică în realitatea datelor experimentale, oferind claritate unor concepte adesea ambigue în literatura de specialitate.

Structura volumului este una progresivă, de tip tutorial sistematic. Primele capitole pun bazele nomenclaturii și ale modelării compartimentale, trecând ulterior prin cinetica biochimică și sisteme celulare, pentru ca în final să abordeze subiecte avansate de analiză de senzitivitate și optimizarea designului experimental. Această organizare reflectă o viziune didactică maturizată, unde matematica (ecuații diferențiale, algebră liniară) este prezentată mereu în dialog cu biologia sau farmacologia pertinentă. Subliniem relevanța practică a capitolelor dedicate identifiabilității și estimării parametrilor, esențiale pentru validarea oricărui model în contextul cercetării aplicate.

În peisajul editorial actual, această lucrare completează perspectiva oferită de A Guide to Numerical Modelling in Systems Biology de Peter Deuflhard. În timp ce textul lui Deuflhard se concentrează strict pe metode numerice și algoritmi pentru cei cu background matematic limitat, volumul de față oferă o viziune mult mai integrată, legând strâns execuția computațională de interpretarea biologică multiscală. De asemenea, spre deosebire de A First Course in Systems Biology, care servește ca o introducere generală, manualul lui DiStefano oferă instrumente software concrete (Matlab, Simulink, SAAMII) și un suport pedagogic extins, fiind o resursă superioară pentru nivelul graduate și cercetare.

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Specificații

ISBN-13: 9780124104112
ISBN-10: 0124104118
Pagini: 884
Dimensiuni: 210 x 279 x 48 mm
Greutate: 2.79 kg
Editura: ELSEVIER SCIENCE

Public țintă

upper-division undergraduate, graduate level, and research level students systems biology, computational biology, biomathematics, biomedical engineering (bioengineering), pharmacology and areas using contemporary dynamical biosystem modeling and simulation methodology.

De ce să citești această carte

Este resursa definitivă pentru studenții de la bioinginerești și cercetătorii care doresc să stăpânească modelarea sistemelor dinamice. Cititorul câștigă nu doar rigoare matematică, ci și competențe practice de simulare pe calculator, susținute de resurse digitale și cod sursă. Este o investiție pe termen lung pentru oricine lucrează cu date biologice complexe și are nevoie de modele computaționale valide și testabile.

Descriere scurtă

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: joed@cs.ucla.edu

Cuprins

1. Biosystem Modeling and Simulation: Nomenclature and Philosophy2. Math Models of Systems: Biomodeling 1013. Computer Simulation Methods4. Structural Biomodeling from Theory & Data: Compartmentalizations5. Structural Biomodeling from Theory & Data: Sizing, Distinguishing & Simplifying Multicompartmental Models6. Nonlinear Mass Action & Biochemical Kinetic Interaction Modeling7. Cellular Systems Biology Modeling: Deterministic & Stochastic8. Physiologically Based, Whole-Organism Kinetics & Noncompartmental Modeling9. Biosystem Stability & Oscillations10. Structural Identifiability11. Parameter Sensitivity Methods12. Parameter Estimation & Numerical Identifiability13. Parameter Estimation Methods II: Facilitating, Simplifying & Working With Data14. Biocontrol System Modeling, Simulation, and Analysis15. Data-Driven Modeling and Alternative Hypothesis Testing16. Experiment Design and Optimization17. Model Reduction and Network Inference in Dynamic Systems Biology

Recenzii

"This very satisfying book has multiple strengths. The text has marvelous clarity, as do the mathematical demonstrations. All are synoptic, while simultaneously explaining the underlying, fine details. The useful organization is enhanced by superb graphics. Although the author has many technical capabilities, with both range and depth, below I’ll give just one illustrative example of the excellent result. Major themes of modern computation and modeling, as applied to biology, include issues of nonlinearities, chaotic dynamics, emergent properties, and instabilities. For example, consider the problems attendant on complex dynamic systems with multiple scales of time and space so typical of living systems. The scientific literature in this domain is rich and immense. When I looked into DiStefano’s book for entries dealing with these topics, I found as early as Chapter One a heading: ”Multiscale Modeling”. Elsewhere were other treatments of these aspects of complexity and modeling difficulties such as the famous problem of “stiff ODEs”, here brilliantly examined and explained, with remedies. The many authoritative tutorials by DiStefano amazed me for so effectively distilling the technical essences. They confirm that DiStefano is a great teacher and guide through various profound, classical difficulties. This book is a masterwork." --F. Eugene Yates
"This book provides a systematic review of the concepts of mathematical modeling in various fields. With its simple language, varied practical examples, quick references, appendixes, and clear basic concepts, it provides a thorough explanation of the subject. The well-organized chapters, along with the use of different notations and typescripts, make it a user-friendly book." Rating: 5 Stars--Doody.com, March 7, 2014
"DiStefano presents this interdisciplinary text merging mathematics, modeling, systems science, and biology. The first chapter introduces the philosophy and nomenclature of modeling and simulation. Chapter two covers mathematics including algebraic models, differential equations, linear and nonlinear modeling, and chapter three describes the use of Taylor series and algorithmic treatment of differential equations in computer simulation methods."--ProtoView.com, February 2014
“I am just in awe of your ability to start with simple ideas and use them to explain sophisticated concepts and methodologies in modeling biochemical and cellular systems (Chapters 6 and 7). This is a great new contribution to the textbook offerings in systems biology.”--Alex Hoffmann, Director of the San Diego Center for Systems Biology and the UCSD Graduate Program in Bioinformatics and Systems Biology
"I found Chapter 1 to be a marvel of heavy-lifting, done so smoothly there was no detectable sweat. Heavy-lifting because you laid out the big load of essential vocabulary and concepts a reader has to have to enter the world of biomodeling confidently. In that chapter you generously acknowledge some us who tried to accomplish this earlier but, compared to your Chapter 1, we were clumsy and boring. For me, now, Chapter 1 was a "page-turner" to be enjoyed straight through. You have the gift of a master athlete who does impossible performances and makes them seem easy.
Your Chapter 9 – on oscillations and stability – is a true jewel. I have a shelf full of books etc on nonlinear mechanics and system analyses and modeling, but nothing to match the clarity and deep understanding you offer the reader. You are a great explainer and teacher." --F. Eugene Yates, Emeritus Professor of Medicine, Chemical Engineering and Ralph and Marjorie Crump Professor of Biomedical Engineering, UCLA