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Modeling Dynamic Biological Systems

Author : Bruce Hannon
ISBN : 9783319056159
Genre : Science
File Size : 24. 97 MB
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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

Modeling Dynamics Biological Systems

Author : Bruce Hannon
ISBN : 0387948503
Genre : Computers
File Size : 76. 9 MB
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Models help us understand the dynamics of real-world processes by using the computer to mimic the actual forces that are known or assumed to result in a system's behavior. This book does not require a substantial background in mathematics or computer science.

Dynamic Systems Biology Modeling And Simulation

Author : Joseph DiStefano III
ISBN : 9780124104938
Genre : Science
File Size : 23. 44 MB
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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 Modelling Of Dynamic Biological Systems

Author : Ludwik Finkelstein
ISBN : 0863800246
Genre : Science
File Size : 66. 47 MB
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Modeling Dynamic Climate Systems

Author : Walter A. Robinson
ISBN : 0387951342
Genre : Science
File Size : 82. 35 MB
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In the process of building and using models to comprehend the dynamics of the atmosphere, ocean and climate, the reader will learn how the different components of climate systems function, interact with each other, and vary over time. Topics include the stability of climate, Earths energy balance, parcel dynamics in the atmosphere, the mechanisms of heat transport in the climate system, and mechanisms of climate variability. Special attention is given to the effects of climate change.

Dynamic Modeling In The Health Sciences

Author : James L. Hargrove
ISBN : 9781461216445
Genre : Medical
File Size : 23. 50 MB
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This book and CD-ROM package integrates the use of STELLA software into the teaching of health, nutrition and physiology, and may be used on its own in nutrition and physiology courses, or can serve as a supplement to introduce the role that simulation modelling can play. The author presents key subjects ranging from the theory of metabolic control, through weight regulation to bone metabolism, and gives readers the tools to simulate these using the STELLA software. Topics include methods for simulation of gene expression, a multi-stage model of tumour development, theories of ageing, circadian rhythms and physiological time, as well as a model for managing weight loss and preventing obesity.

Dynamic Models In Biology

Author : Stephen P. Ellner
ISBN : 9781400840960
Genre : Science
File Size : 24. 8 MB
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From controlling disease outbreaks to predicting heart attacks, dynamic models are increasingly crucial for understanding biological processes. Many universities are starting undergraduate programs in computational biology to introduce students to this rapidly growing field. In Dynamic Models in Biology, the first text on dynamic models specifically written for undergraduate students in the biological sciences, ecologist Stephen Ellner and mathematician John Guckenheimer teach students how to understand, build, and use dynamic models in biology. Developed from a course taught by Ellner and Guckenheimer at Cornell University, the book is organized around biological applications, with mathematics and computing developed through case studies at the molecular, cellular, and population levels. The authors cover both simple analytic models--the sort usually found in mathematical biology texts--and the complex computational models now used by both biologists and mathematicians. Linked to a Web site with computer-lab materials and exercises, Dynamic Models in Biology is a major new introduction to dynamic models for students in the biological sciences, mathematics, and engineering.

Models Of Life

Author : Kim Sneppen
ISBN : 9781316061657
Genre : Science
File Size : 43. 27 MB
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Reflecting the major advances that have been made in the field over the past decade, this book provides an overview of current models of biological systems. The focus is on simple quantitative models, highlighting their role in enhancing our understanding of the strategies of gene regulation and dynamics of information transfer along signalling pathways, as well as in unravelling the interplay between function and evolution. The chapters are self-contained, each describing key methods for studying the quantitative aspects of life through the use of physical models. They focus, in particular, on connecting the dynamics of proteins and DNA with strategic decisions on the larger scale of a living cell, using E. coli and phage lambda as key examples. Encompassing fields such as quantitative molecular biology, systems biology and biophysics, this book will be a valuable tool for students from both biological and physical science backgrounds.

Modeling Nonlinear Behavior Of Dynamic Biological Systems

Author : Maryam Masnadi-Shirazi
ISBN : OCLC:1043671810
Genre :
File Size : 52. 34 MB
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With the availability of large-scale data acquired through high-throughput technologies, computational systems biology has made substantial progress towards partially modeling biological systems. In this dissertation we intend to focus on deciphering the dynamics of such systems through data-driven analysis of multivariate time-course data. We develop integrative frameworks to study the following problems: 1) time-varying causal inference when the number of samples exceeds the number of variables (overdetermined case), 2) dynamic causal network reconstruction when the number of variables exceeds the data samples (underdetermined case), 3) forecasting the dynamic behavior of complex chaotic systems from short and noisy time-series data. In the first scenario we utilize the notion of Granger causality identified by a first-order vector autoregressive (VAR) model on phosphoproteomic measurements to unravel the crosstalk between various phosphoproteins in three distinct time intervals. In scenario 2 we use a non-parametric change point detection (CPD) algorithm on transcriptional time series data from a mouse cell cycle to estimate temporal patterns that can be associated with different phases of the cell cycle. In the second scenario the problem becomes more complex as the number of variables exceeds the number of time-series data and we use a higher order VAR models to estimate causal interactions among cell cycle genes. To solve this ill-posed problem we use Least Absolute Shrinkage and Selection Operator (LASSO) and select the regularization parameters through Estimation Stability with Cross Validation (ES-CV) leading to more biologically meaningful results. LASSO + ES-CV is applied to temporal intervals associated with the G1, S and G2/M phases of the cell cycle to estimate phase-specific intracellular interactions. In problem 3, we develop a nonparametric forecasting algorithm for chaotic dynamic systems, Multiview Radial Basis Function Network (MV-RBFN) that outperforms a model-free approach, Multiview Embedding (MVE). In this algorithm, the forecast skill of all possible manifolds (views) reconstructed from a combination of variables and their time lags is assessed and ranked from best to worst. MV-RBFN uses the top k views as the inputs of a neural network to approximate a nonlinear function f(.) that maps the past events of a dynamic system as the input, to future values as the output.

Dynamic Models And Control Of Biological Systems

Author : Vadrevu Sree Hari Rao
ISBN : 9781441903594
Genre : Science
File Size : 29. 47 MB
Format : PDF
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Mathematical Biology has grown at an astonishing rate and has established itself as a distinct discipline. Mathematical modeling is now being applied in every major discipline in the biological sciences. Though the field has become increasingly large and specialized, this book remains important as a text that introduces some of the exciting problems which arise in the biological sciences and gives some indication of the wide spectrum of questions that modeling can address.

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