MODELING GENETIC REGULATORY NETWORKS: CONTINUOUS OR DISCRETE?

DOI10.1142/S0218339006001763zbMath1105.92015OpenAlexW1989415498MaRDI QIDQ5483867

No author found.

Publication date: 23 August 2006

Published in: Journal of Biological Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s0218339006001763

zbMATH Keywords

stochastic differential equationsMarkov processdiscrete modelsgenetic regulatory networkcontinuous models

Mathematics Subject Classification ID

Continuous-time Markov processes on general state spaces (60J25) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Circuits, networks (94C99) Genetics and epigenetics (92D10)

Related Items (5)

Design of nonfragile state estimator for discrete-time genetic regulatory networks subject to randomly occurring uncertainties and time-varying delays ⋮ State estimation for Markov-type genetic regulatory networks with delays and uncertain mode transition rates ⋮ Stability analysis for genetic regulatory networks with delays: the continuous-time case and the discrete-time case ⋮ \(H_{\infty }\) filtering for discrete-time genetic regulatory networks with random delays ⋮ New stability criterion for discrete-time genetic regulatory networks with time-varying delays and stochastic disturbances

Cites Work

• Construction of genomic networks using mutual-information clustering and reversible-jump Markov-chain-Monte-Carlo predictor design
• External control in Markovian genetic regulatory networks
• Statistical mechanics of complex networks
• The Structure and Function of Complex Networks
• Exploring complex networks

This page was built for publication: MODELING GENETIC REGULATORY NETWORKS: CONTINUOUS OR DISCRETE?