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Analysis of Deterministic Cyclic Gene Regulatory Network Models with Delays

This brief examines a deterministic, ODE-based model for gene regulatory networks (GRN) that incorporates nonlinearities and time-delayed;

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Simple Mathematical Models of Gene Regulatory Dynamics

the field, we focus on the analysis of simple gene-network dynamics. The notes commence with an introduction to the deterministic modeling;

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Biological Network Analysis

Analysis, and various network models Discusses three major biological networks, including Gene Regulatory Networks (GRN), Protein-Protein;

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Gene Regulatory Networks (GRNs)

Gene Regulatory Networks, Volume 139 in the Current Topics in Developmental Biology series, highlights new advances in the field, with this;

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Analysis of Microarray Data: A Network-Based Approach

for Gene Regulation* Estimating Transcriptional Regulatory Networks by a Bayesian Network* Analysis of Therapeutic Compound Effects;

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Evolutionary Computation in Gene Regulatory Network Research

Introducing a handbook for gene regulatory network research using evolutionary computation, with applications for computer scientists;

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Cyclic Plasticity of Engineering Materials

fundamentals of cyclic plasticity or to one of the major classes of materials, thereby providing a wide coverage of the field. The book deals with;

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Deterministic, Stochastic and Thermodynamic Modelling of some Interacting Species

deterministic environments of two interacting species, stochastic analysis of a demographic model of urbanization and stability behaviour of a social;

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Piecewise Deterministic Processes in Biological Models

This book presents a concise introduction to piecewise deterministic Markov processes (PDMPs), with particular emphasis on their;

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Troubleshooting with Wireshark

Chappell in her 20+ years of network analysis experience. Learn insider tips and tricks to quickly detect the cause of poor network performance;

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Computational Neurogenetic Modeling

interactions between genes. These include neural network models and their integration with gene network models. This new area brings together knowledge;

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Biological Networks

Any system with sub-units linked into a whole is known as a network. A biological network is a network of biological systems. It provides a;

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Introduction to Synthetic Biology

, drive the circuit implementation in the lab. Concepts such as kinetics, circuit dynamics and equilibria, stochastic and deterministic;

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Hybrid Systems Biology

reviewed and selected from 13 submissions. They cover topics such as: modeling and analysis of metabolic, signaling, and genetic regulatory;

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Stochastic Dynamics for Systems Biology

levels. The last chapter provides up-to-date results on stochastic and deterministic mass action kinetics with applications to enzymatic;

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Gene Regulatory Networks

Gene regulatory networks play a vital role in organismal development and function by controlling gene expression. With the availability;

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Evolution after Gene Duplication

. Key Features: * Explores comparative genomics, genome evolution studies and analysis of multi-gene families such as Hox, globins, olfactory;

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Systems Biology

components in large networks with several interactions.;

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Sensitivity Analysis of Damage Models for Epoxy Resins

with cyclic tension-compression tests, and the parameters of the model are identified by the matching between experiment and simulation;

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An Introduction to Mathematical Epidemiology

model building, fitting to data, local and global analysis techniques. Various types of deterministic dynamical models are considered: ordinary;

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Regulation of European Banks and Business Models

, which overlaps with those subjected to the European Banking Authorities' 2011 stress tests, this report emphasizes the key regulatory gaps that;

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Communication Networks

accessible to students for the first time. Taking a top-down approach to network protocol design, the authors begin with the deterministic model and;

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Cis/Transgene Optimization

computational biology in design, analysis, or regulatory reviews of key gene expression elements for the production of recombinant proteins experiments.;

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Cambridge Studies in Mathematical Biology

, mathematicians and biologists are provided with a framework within which population dynamics can be fully explored and understood. Aspects of population;

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Information Theory

in gravity cascade separation; the role of information theory in gene regulatory network inference; Quantum Information Processing (QIP) and the link;

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Nutrigenomics and Proteomics in Health and Disease

and peptidomics in nutrition; gene selection for nutrigenomic studies; gene-nutrient network analysis, and nutrigenomics to nutritional;

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Network Models in Economics and Finance

. Readers are provided with an understanding of the latest advances in network analysis as applied to economics, finance, corporate governance, and;

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