Deterministic Versus Stochastic Modelling In Biochemistry And Systems Biology
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Deterministic Versus Stochastic Modelling In Biochemistry And Systems Biology
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Author : Paola Lecca
language : en
Publisher: Elsevier
Release Date : 2013-04-09
Deterministic Versus Stochastic Modelling In Biochemistry And Systems Biology written by Paola Lecca and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-09 with Mathematics categories.
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
Identifiability And Regression Analysis Of Biological Systems Models
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Author : Paola Lecca
language : en
Publisher: Springer Nature
Release Date : 2024-11-09
Identifiability And Regression Analysis Of Biological Systems Models written by Paola Lecca and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-09 with Medical categories.
This richly illustrated book presents the latest techniques for the identifiability analysis and standard and robust regression analysis of complex dynamical models, and looks at their objectives. It begins by providing a definition of complexity in dynamic systems, introducing the concepts of system size, density of interactions, stiff dynamics, and the hybrid nature of determination. The discussion then turns to the mathematical foundations of model structural and practical identifiability analysis, multilinear and non-linear regression analysis, and best predictor selection, and their algorithmic procedures. Although the featured examples mainly focus on applications to 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 determine identifiability conditions, how to search for an identifiable model, and how to conduct their own regression analysis and diagnostics without supervision. This new edition includes a concise, yet comprehensive treatment of the main artificial intelligence methods which can be used for parameter inference in models of complex dynamic biological systems. It emphasizes the most efficient solutions for generating synthetic data that augment the training data and which are indispensable for machine learning procedures. Featuring a wealth of real-world examples, exercises, and R codes, the book addresses the needs of doctoral students and researchers in bioinformatics, bioengineering, systems biology, biophysics, biochemistry, the environmental sciences and experimental physics. Familiarity with the fundamentals of probability and statistics (as provided in first-year university courses) and a basic grasp of R are assumed.
Theoretical Physics For Biological Systems
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Author : Paola Lecca
language : en
Publisher: CRC Press
Release Date : 2019-01-30
Theoretical Physics For Biological Systems written by Paola Lecca and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-30 with Medical categories.
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.
Analysis Of Biological Systems
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Author : Corrado Priami
language : en
Publisher: World Scientific
Release Date : 2015-01-29
Analysis Of Biological Systems written by Corrado Priami and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-29 with Science categories.
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.
Introduction To Modeling And Simulation With Matlab And Python
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Author : Steven I. Gordon
language : en
Publisher: CRC Press
Release Date : 2017-07-12
Introduction To Modeling And Simulation With Matlab And Python written by Steven I. Gordon and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-12 with Computers categories.
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.
Dynamic Systems Biology Modeling And Simulation
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Author : Joseph DiStefano III
language : en
Publisher: Academic Press
Release Date : 2015-01-10
Dynamic Systems Biology Modeling And Simulation written by Joseph DiStefano III and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-10 with Science categories.
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]
Stochastic Modelling For Systems Biology Third Edition
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Author : Darren J. Wilkinson
language : en
Publisher: CRC Press
Release Date : 2018-12-07
Stochastic Modelling For Systems Biology Third Edition written by Darren J. Wilkinson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-07 with Mathematics categories.
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.
Phenotypic Switching
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Author : Herbert Levine
language : en
Publisher: Academic Press
Release Date : 2020-06-10
Phenotypic Switching written by Herbert Levine and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-10 with Medical categories.
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
Bacterial Cellular Metabolic Systems
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Author : K. Shimizu
language : en
Publisher: Elsevier
Release Date : 2013-03-26
Bacterial Cellular Metabolic Systems written by K. Shimizu and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-26 with Science categories.
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
Protein Folding In Silico
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Author : Irena Roterman-Konieczna
language : en
Publisher: Elsevier
Release Date : 2012-10-04
Protein Folding In Silico written by Irena Roterman-Konieczna and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-04 with Science categories.
Protein folding is a process by which a protein structure assumes its functional shape of conformation, and has been the subject of research since the publication of the first software tool for protein structure prediction. Protein folding in silico approaches this issue by introducing an ab initio model that attempts to simulate as far as possible the folding process as it takes place in vivo, and attempts to construct a mechanistic model on the basis of the predictions made. The opening chapters discuss the early stage intermediate and late stage intermediate models, followed by a discussion of structural information that affects the interpretation of the folding process. The second half of the book covers a variety of topics including ligand binding site recognition, the "fuzzy oil drop" model and its use in simulation of the polypeptide chain, and misfolded proteins. The book ends with an overview of a number of other ab initio methods for protein structure predictions and some concluding remarks. - Discusses a range of ab initio models for protein structure prediction - Introduces a unique model based on experimental observations - Describes various methods for the quantitative assessment of the presented models from the viewpoint of information theory