It was around the period of World War II that Arturo Rosenblueth and Norbert Wiener were
taking the first steps in the direction of systems medicine. They formed an interesting pair …

Motivation: A major objective of gene regulatory network modeling, in addition to gaining a
deeper understanding of genetic regulation and control, is the development of …

Mathematical and computational modeling of genetic regulatory networks promises to
uncover the fundamental principles governing biological systems in an integrative and …

Driven by the desire to understand genomic functions through the interactions among genes
and gene products, the research in gene regulatory networks has become a heated area in …

Motivation: Our goal is to construct a model for genetic regulatory networks such that the
model class:(i) incorporates rule-based dependencies between genes;(ii) allows the …

Probabilistic Boolean Networks (PBNs) were recently introduced as models of gene
regulatory networks. The dynamical behavior of PBNs, which are probabilistic …

A significant amount of attention has recently been focused on modeling of gene regulatory
networks. Two frequently used large-scale modeling frameworks are Bayesian networks …

Boolean network models are one of the simplest models to study complex dynamic behavior
in biological systems. They can be applied to unravel the mechanisms regulating the …

This article presents a tutorial survey of some of the recent results on intervention in the
context of probabilistic gene regulatory networks, which, owing to their original binary …

Molecular genetics presents an increasingly complex picture of the genome and biological
function. Evidence is mounting for distributed function, redundancy, and combinatorial …