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Dynamic Biological Networks
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Book Synopsis Dynamic Biological Networks by : Ronald M. Harris-Warrick
Download or read book Dynamic Biological Networks written by Ronald M. Harris-Warrick and published by MIT Press. This book was released on 1992 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: This introduction to the crustacean stomatogastric nervous system (STNS) describes some of the best-understood neural networks in the animal kingdom at cellular, network, behavioural, comparative and evolutionary levels of analysis.
Book Synopsis Handbook on Biological Networks by : Stefano Boccaletti
Download or read book Handbook on Biological Networks written by Stefano Boccaletti and published by World Scientific. This book was released on 2010 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: Networked systems are all around us. The accumulated evidence of systems as complex as a cell cannot be fully understood by studying only their isolated constituents, giving rise to a new area of interest in research ? the study of complex networks. In a broad sense, biological networks have been one of the most studied networks, and the field has benefited from many important contributions. By understanding and modeling the structure of a biological network, a better perception of its dynamical and functional behavior is to be expected. This unique book compiles the most relevant results and novel insights provided by network theory in the biological sciences, ranging from the structure and dynamics of the brain to cellular and protein networks and to population-level biology.
Book Synopsis The Dynamics of Biological Systems by : Arianna Bianchi
Download or read book The Dynamics of Biological Systems written by Arianna Bianchi and published by Springer Nature. This book was released on 2019-10-02 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents nine mini-courses from a summer school, Dynamics of Biological Systems, held at the University of Alberta in 2016, as part of the prestigious seminar series: Séminaire de Mathématiques Supérieures (SMS). It includes new and significant contributions in the field of Dynamical Systems and their applications in Biology, Ecology, and Medicine. The chapters of this book cover a wide range of mathematical methods and biological applications. They - explain the process of mathematical modelling of biological systems with many examples, - introduce advanced methods from dynamical systems theory, - present many examples of the use of mathematical modelling to gain biological insight - discuss innovative methods for the analysis of biological processes, - contain extensive lists of references, which allow interested readers to continue the research on their own. Integrating the theory of dynamical systems with biological modelling, the book will appeal to researchers and graduate students in Applied Mathematics and Life Sciences.
Book Synopsis Systems Biology: Simulation of Dynamic Network States by : Bernhard Ø. Palsson
Download or read book Systems Biology: Simulation of Dynamic Network States written by Bernhard Ø. Palsson and published by Cambridge University Press. This book was released on 2011-05-26 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author :American Mathematical Society. Short Course, Modeling and Simulation of Biological Networks Publisher :American Mathematical Soc. ISBN 13 :9780821867693 Total Pages :172 pages Book Rating :4.8/5 (676 download)
Book Synopsis Modeling and Simulation of Biological Networks by : American Mathematical Society. Short Course, Modeling and Simulation of Biological Networks
Download or read book Modeling and Simulation of Biological Networks written by American Mathematical Society. Short Course, Modeling and Simulation of Biological Networks and published by American Mathematical Soc.. This book was released on 2007-08-21 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is the task of computational biology to help elucidate the unique characteristics of biological systems. This process has barely begun, and many researchers are testing computational tools that have been used successfully in other fields. Mathematical and statistical network modeling is an important step toward uncovering the organizational principles and dynamic behavior of biological networks. Undoubtedly, new mathematical tools will be needed, however, to meet this challenge. The workhorse of this effort at present comprises the standard tools from applied mathematics, which have proven to be successful for many problems. But new areas of mathematics not traditionally considered applicable are contributing other powerful tools. This volume is intended to introduce this topic to a broad mathematical audience. The aim is to explain some of the biology and the computational and mathematical challenges we are facing. The different chapters provide examples of how these challenges are met, with particular emphasis on nontraditional mathematical approaches. The volume features a broad spectrum of networks across scales, ranging from biochemical networks within a single cell to epidemiological networks encompassing whole cities. Chapter topics include phylogenetics and gene finding using tools from statistics and algebraic geometry, biochemical network inference using tools from computational algebra, control-theoretic approaches to drug delivery using differential equations, and interaction-based modeling and discrete mathematics applied to problems in population dynamics and epidemiology.
Book Synopsis Biological Networks by : Franois Kps
Download or read book Biological Networks written by Franois Kps and published by World Scientific. This book was released on 2007 with total page 531 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents a timely and comprehensive overview of biological networks at all organization levels in the spirit of the complex system approach. It discusses the transversal issues and fundamental principles as well as the overall structure, dynamics, and modeling of a wide array of biological networks at the molecular, cellular, and population levels. Anchored in both empirical data and a strong theoretical background, the book therefore lends valuable credence to the complex systems approach.
Book Synopsis Probabilistic Boolean Networks by : Ilya Shmulevich
Download or read book Probabilistic Boolean Networks written by Ilya Shmulevich and published by SIAM. This book was released on 2010-01-21 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first comprehensive treatment of probabilistic Boolean networks, unifying different strands of current research and addressing emerging issues.
Book Synopsis Network Reconstruction of Dynamic Biological Systems by : Behrang Asadi
Download or read book Network Reconstruction of Dynamic Biological Systems written by Behrang Asadi and published by . This book was released on 2013 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inference of network topology from experimental data is a central endeavor in biology, since knowledge of the underlying signaling mechanisms a requirement for understanding biological phenomena. As one of the most important tools in bioinformatics area, development of methods to reconstruct biological networks has attracted remarkable attention in the current decade. Integration of different data types can lead to remarkable improvements in our ability to identify the connectivity of different segments of networks and to predict events within a cellular system. Several recent studies used data integration to reconstruct biochemical networks and to build predictive models from large-scale datasets. In this dissertation we first prescribe directions to reconstruct biological networks based on data properties and priorities in terms of network reconstruction performance. We use experimentally measured and synthetic data sets to compare three popular methods--principal component regression (PCR), linear matrix inequalities (LMI), and Least Absolute Shrinkage and Selection Operator (LASSO)--in terms of root-mean-squared-error (RMSE), average fractional error in the value of the coefficients, accuracy, sensitivity, specificity and the geometric mean of sensitivity and specificity. This comparison enables us to establish criteria for selection of an appropriate approach for network reconstruction based on a priori properties of experimental data. Reconstruction of biological and biochemical networks from large biological datasets is challenging when the data in question are dynamic. To contribute to this challenge, we also developed a new method, called Doubly Penalized Linear Absolute Shrinkage and Selection Operator (DPLASSO), for reconstruction of dynamic biological networks. DPLASSO consists of two components, statistical significance testing of model coefficients and penalized/constrained optimization. A partial least squares with statistical significance testing acts as a supervisory-level filter to extract the most informative components of the network from a dataset (Layer 1). Then, LASSO with extra weights on the smaller parameters identified in the first layer is employed to retain the main predictors and to set the smallest coefficients to zero (Layer 2). We illustrate that DPLASSO outperforms LASSO in terms of sensitivity, specificity and accuracy. Most of biological systems are nonlinear, therefore, expressing the network model in linear form may not be able to appropriately represent the real structure of the network or to predict the response of the network as accurately as a proper nonlinear model does. Accordingly, as another contribution we have introduced a novel method to reconstruct nonlinear biological networks. In this method, we use a quadratic nonlinear model as the representation of second-order Taylor series expansion of a nonlinear system around an arbitrary point of interest. We apply LASSO to shrink some of the small coefficients to zero. A statistical significance testing (t-test) will complete the parameter (network link) selection. We demonstrate that our proposed approach will lead to considerable improvements in predicting the response of the system and fair improvement in accuracy and sensitivity of the network identified.
Book Synopsis Handbook on Biological Networks by : Stefano Boccaletti
Download or read book Handbook on Biological Networks written by Stefano Boccaletti and published by World Scientific. This book was released on 2010 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: Networked systems are all around us. The accumulated evidence of systems as complex as a cell cannot be fully understood by studying only their isolated constituents, giving rise to a new area of interest in research OCo the study of complex networks . In a broad sense, biological networks have been one of the most studied networks, and the field has benefited from many important contributions. By understanding and modeling the structure of a biological network, a better perception of its dynamical and functional behavior is to be expected. This unique book compiles the most relevant results and novel insights provided by network theory in the biological sciences, ranging from the structure and dynamics of the brain to cellular and protein networks and to population-level biology. Sample Chapter(s). Chapter 1: Introduction (61 KB). Contents: Networks at the Cellular Level: The Structural Network Properties of Biological Systems (M Brilli & P Li); Dynamics of Multicellular Synthetic Gene Networks (E Ullner et al.); Boolean Networks in Inference and Dynamic Modeling of Biological Systems at the Molecular and Physiological Level (J Thakar & R Albert); Complexity of Boolean Dynamics in Simple Models of Signaling Networks and in Real Genetic Networks (A D az-Guilera & R ulvarez-Buylla); Geometry and Topology of Folding Landscapes (L Bongini & L Casetti); Elastic Network Models for Biomolecular Dynamics: Theory and Application to Membrane Proteins and Viruses (T R Lezon et al.); Metabolic Networks (M C Palumbo et al.); Brain Networks: The Human Brain Network (O Sporns); Brain Network Analysis from High-Resolution EEG Signals (F De Vico Fallani & F Babiloni); An Optimization Approach to the Structure of the Neuronal layout of C elegans (A Arenas et al.); Cultured Neuronal Networks Express Complex Patterns of Activity and Morphological Memory (N Raichman et al.); Synchrony and Precise Timing in Complex Neural Networks (R-M Memmesheimer & M Timme); Networks at the Individual and Population Levels: Ideas for Moving Beyond Structure to Dynamics of Ecological Networks (D B Stouffer et al.); Evolutionary Models for Simple Biosystems (F Bagnoli); Evolution of Cooperation in Adaptive Social Networks (S Van Segbroeck et al.); From Animal Collectives and Complex Networks to Decentralized Motion Control Strategies (A Buscarino et al.); Interplay of Network State and Topology in Epidemic Dynamics (T Gross). Readership: Advanced undergraduates, graduate students and researchers interested in the study of complex networks in a wide range of biological processes and systems."
Book Synopsis Biological Networks by : Francois Kepes
Download or read book Biological Networks written by Francois Kepes and published by World Scientific. This book was released on 2007 with total page 531 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents a timely and comprehensive overview of biological networks at all organization levels in the spirit of the complex systems approach. It discusses the transversal issues and fundamental principles as well as the overall structure, dynamics, and modeling of a wide array of biological networks at the molecular, cellular, and population levels. Anchored in both empirical data and a strong theoretical background, the book therefore lends valuable credence to the complex systems approach. Sample Chapter(s). Chapter 1: Scale-Free Networks in Biology (821 KB). Contents: Scale-Free Networks in Biology (E Almaas et al.); Modularity in Biological Networks (R V Sol(r) et al.); Inference of Biological Regulatory Networks: Machine Learning Approaches (F d''Alch(r)-Buc); Transcriptional Networks (F K(r)p s); Protein Interaction Networks (K Tan & T Ideker); Metabolic Networks (D A Fell); Heterogeneous Molecular Networks (V Schnchter); Evolution of Regulatory Networks (A Veron et al.); Complexity in Neuronal Networks (Y Fr(r)gnac et al.); Networks of the Immune System (R E Callard & J Stark); A History of the Study of Ecological Networks (L-F Bersier); Dynamic Network Models of Ecological Diversity, Complexity, and Nonlinear Persistence (R J Williams & N D Martinez); Infection Transmission through Networks (J S Koopman). Readership: Graduate students and industry experts in systems biology and complex systems; biologists; chemists; physicists; mathematicians; computer scientists
Book Synopsis Networks of Networks in Biology by : Narsis A. Kiani
Download or read book Networks of Networks in Biology written by Narsis A. Kiani and published by Cambridge University Press. This book was released on 2021-04 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces network inspired approaches for the analysis and integration of large, heterogeneous data sets in the life sciences.
Book Synopsis Dynamics of Biological Systems by : Michael Small
Download or read book Dynamics of Biological Systems written by Michael Small and published by CRC Press. This book was released on 2011-08-25 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the spontaneous rapid firing of cortical neurons to the spatial diffusion of disease epidemics, biological systems exhibit rich dynamic behaviour over a vast range of time and space scales. Unifying many of these diverse phenomena, Dynamics of Biological Systems provides the computational and mathematical platform from which to understand the underlying processes of the phenomena. Through an extensive tour of various biological systems, the text introduces computational methods for simulating spatial diffusion processes in excitable media, such as the human heart, as well as mathematical tools for dealing with systems of nonlinear ordinary and partial differential equations, such as neuronal activation and disease diffusion. The mathematical models and computer simulations offer insight into the dynamics of temporal and spatial biological systems, including cardiac pacemakers, artificial electrical defibrillation, pandemics, pattern formation, flocking behaviour, the interaction of autonomous agents, and hierarchical and structured network topologies. Tools from complex systems and complex networks are also presented for dealing with real phenomenological systems. With exercises and projects in each chapter, this classroom-tested text shows students how to apply a variety of mathematical and computational techniques to model and analyze the temporal and spatial phenomena of biological systems. MATLAB® implementations of algorithms and case studies are available on the author’s website.
Book Synopsis Biological Network Analysis by : Pietro Hiram Guzzi
Download or read book Biological Network Analysis written by Pietro Hiram Guzzi and published by Elsevier. This book was released on 2020-05-11 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biological Network Analysis: Trends, Approaches, Graph Theory, and Algorithms considers three major biological networks, including Gene Regulatory Networks (GRN), Protein-Protein Interaction Networks (PPIN), and Human Brain Connectomes. The book's authors discuss various graph theoretic and data analytics approaches used to analyze these networks with respect to available tools, technologies, standards, algorithms and databases for generating, representing and analyzing graphical data. As a wide variety of algorithms have been developed to analyze and compare networks, this book is a timely resource. Presents recent advances in biological network analysis, combining Graph Theory, Graph Analysis, and various network models Discusses three major biological networks, including Gene Regulatory Networks (GRN), Protein-Protein Interaction Networks (PPIN) and Human Brain Connectomes Includes a discussion of various graph theoretic and data analytics approaches
Book Synopsis Dynamics On and Of Complex Networks by : Niloy Ganguly
Download or read book Dynamics On and Of Complex Networks written by Niloy Ganguly and published by Springer Science & Business Media. This book was released on 2009-04-14 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: This self-contained book systematically explores the statistical dynamics on and of complex networks having relevance across a large number of scientific disciplines. The theories related to complex networks are increasingly being used by researchers for their usefulness in harnessing the most difficult problems of a particular discipline. The book is a collection of surveys and cutting-edge research contributions exploring the interdisciplinary relationship of dynamics on and of complex networks. Topics covered include complex networks found in nature—genetic pathways, ecological networks, linguistic systems, and social systems—as well as man-made systems such as the World Wide Web and peer-to-peer networks. The contributed chapters in this volume are intended to promote cross-fertilization in several research areas, and will be valuable to newcomers in the field, experienced researchers, practitioners, and graduate students interested in systems exhibiting an underlying complex network structure in disciplines such as computer science, biology, statistical physics, nonlinear dynamics, linguistics, and the social sciences.
Book Synopsis Modeling Dynamic Biological Systems by : Bruce Hannon
Download or read book Modeling Dynamic Biological Systems written by Bruce Hannon and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Dynamical Systems on Networks by : Mason Porter
Download or read book Dynamical Systems on Networks written by Mason Porter and published by Springer. This book was released on 2016-03-31 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a tutorial for the study of dynamical systems on networks. It discusses both methodology and models, including spreading models for social and biological contagions. The authors focus especially on “simple” situations that are analytically tractable, because they are insightful and provide useful springboards for the study of more complicated scenarios. This tutorial, which also includes key pointers to the literature, should be helpful for junior and senior undergraduate students, graduate students, and researchers from mathematics, physics, and engineering who seek to study dynamical systems on networks but who may not have prior experience with graph theory or networks. Mason A. Porter is Professor of Nonlinear and Complex Systems at the Oxford Centre for Industrial and Applied Mathematics, Mathematical Institute, University of Oxford, UK. He is also a member of the CABDyN Complexity Centre and a Tutorial Fellow of Somerville College. James P. Gleeson is Professor of Industrial and Applied Mathematics, and co-Director of MACSI, at the University of Limerick, Ireland.
Author :American Mathematical Society. Short Course, Modeling and Simulation of Biological Networks Publisher :American Mathematical Society(RI) ISBN 13 :9780821892794 Total Pages :160 pages Book Rating :4.8/5 (927 download)
Book Synopsis Modeling and Simulation of Biological Networks by : American Mathematical Society. Short Course, Modeling and Simulation of Biological Networks
Download or read book Modeling and Simulation of Biological Networks written by American Mathematical Society. Short Course, Modeling and Simulation of Biological Networks and published by American Mathematical Society(RI). This book was released on 2014-05-10 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is the task of computational biology to help elucidate the unique characteristics of biological systems. This process has barely begun, and many researchers are testing computational tools that have been used successfully in other fields. Mathematical and statistical network modeling is an important step toward uncovering the organizational principles and dynamic behavior of biological networks. Undoubtedly, new mathematical tools will be needed, however, to meet this challenge. The workhorse of this effort at present comprises the standard tools from applied mathematics, which have proven to be successful for many problems. But new areas of mathematics not traditionally considered applicable are contributing other powerful tools. This volume is intended to introduce this topic to a broad mathematical audience. The aim is to explain some of the biology and the computational and mathematical challenges we are facing. The different chapters provide examples of how these challenges are met, with particular emphasis on nontraditional mathematical approaches.The volume features a broad spectrum of networks across scales, ranging from biochemical networks within a single cell to epidemiological networks encompassing whole cities. Chapter topics include phylogenetics and gene finding using tools from statistics and algebraic geometry, biochemical network inference using tools from computational algebra, control-theoretic approaches to drug delivery using differential equations, and interaction-based modeling and discrete mathematics applied to problems in population dynamics and epidemiology.
