We interrogated diet-induced epigenomic, transcriptomic, proteomic, and metabolomic alterations using high-throughput omic methods and used a network modeling approach to integrate these diverse molecular signals.
In this regard, we propose that our system approaches using a network model could potentially be useful to characterize the perturbation in xenobiotic metabolism upon CS exposure.
Alternatively, they can be organized using a network model with people and actions geographically dispersed.
Here we propose a mechanism for such flexible routing of information flow in a complex brain network (pathway-specific gating), tested using a network model of pyramidal neurons and three classes of interneurons with connection probabilities constrained by data.
We propose that these findings are tightly linked: using a network model, we show that slower synapses are essential to counterbalance hyperconnectivity in order to maintain a dynamic range of excitatory activity.
The porous space of these structures has been simulated using a network model named Pore-Cor, whicreatestes network structures with percolation behaviour and porosity matching those of the experimental sample.
These results show that the calculation of azimuthal instabilities using a network model and finite element method may lead to severe prediction errors when the mean flow is considered.
Representing construction supply chains using a network model can help understand the complexity, support re-configuration, identify the bottlenecks, and prioritize company's resources, as well as add values to the management of construction projects.
Similarly, Jackson et al. (2003) studied the effect of wettability on water flooding at the reservoir scale using a network model in conjunction with reservoir scale conventional simulations.
There are studies using a network model simulating the cortex of the brain [35], [36].
