Mathematical modeling of biological processes provides deep insights into complex cellular
systems. While quantitative and continuous models such as differential equations have been …

Computational models are increasingly used to analyze the operation of complex
biochemical networks, including those involved in cell signaling networks. Here we review …

The merging of network theory and microarray data analysis techniques has spawned a new
field: gene coexpression network analysis. While network methods are increasingly used in …

Modern life sciences research increasingly relies on computational solutions, from large
scale data analyses to theoretical modeling. Within the theoretical models Boolean networks …

Dynamic molecular interactions play a central role in regulating the functioning of cells and
organisms. The availability of experimentally determined large-scale cellular networks …

Monkeypox is a viral etiological agent with hallmarks analogous to those observed in
smallpox cases in the past. The ongoing outbreak of Monkeypox viral infection is becoming …

Given the complexity and interactive nature of biological systems, constructing informative
and coherent network models of these systems and subsequently develo** efficient …

We present a novel methodology to construct a Boolean dynamic model from time series
metagenomic information and integrate this modeling with genome-scale metabolic network …

The biomolecules inside or near cells form a complex interacting system. Cellular
phenotypes and behaviors arise from the totality of interactions among the components of …

Prior work on the dynamics of Boolean networks, including analysis of the state space
attractors and the basin of attraction of each attractor, has mainly focused on synchronous …