In conclusion, the inferred TEM regulatory network accurately captured experimental TEM behavior and highlighted crosstalk between specific angiogenic and inflammatory signaling pathways of outstanding importance to control their pro-angiogenic activity.

1C): 1) experimental measurement of the responses of TEM differentiated in vitro to a set of ligands, 2) construction of a dynamic regulatory network based on these experimental data, 3) in silico prediction of the treatments altering TEM behavior, 4) experimental validation of computationally predicted treatments using ivdTEM and 5) validation the best predicted treatments in patient TEM (Fig.

We used TEM differentiated in vitro to derive a dynamical regulatory network from experimental data obtained with a selected number of li-gands (Fig.

Dynamical Boolean modeling was then performed by integrating the retained links into an algorithm for computing Minimal Intervention Set (MIS) of TEM regulatory network .

Given a regulatory network , MIS patterns represent a set of simultaneous perturbations (or treatments) to force the network into a desired steady state, where a subset of nodes remain at a fixed expression level of either low or high [41,42].

In a Boolean modeling approach, the nodes in a regulatory network represent the state of activation of a gene (protein, receptor or ligand) using discrete variables (On or Off).

Introducing perturbations in a biological regulatory network can change the attractors and even transition the system from one attractor to another one.

The Boolean steady state of the network has been shown to correspond to the cellular states for various regulatory networks in the past [3].

Using the regulatory network model of TEM differentiated in vitro we predicted the minimal treatments required for transitioning tumor TEM to blood TEM and vice versa.

By constructing a global energy landscape for a simplified yeast cell-cycle regulatory network , we provide a systematic study of this issue.

The cell-cycle regulatory network must also be robust and adaptive to external stresses and signal changes.

Our results demonstrate that the energy landscape of the cell cycle is globally attractive, and we show how the cell cycle regulatory network reduces fluctuations from its upstream process and enables long durations in the transition regime.

Based on the key regulatory network [17] and our previous study on budding yeast [22] , the cell cycle regulatory network can be simplified and separated into G1 /S, early M and late M modules, as shown in Fig.

The regulatory network of cell-cycle process in budding yeast.

(A) The regulatory network of key regulators in budding yeast cell-cycle process.

regulatory networks , the rank corresponds to the minimal number of input features on which the outputs depend.

A recent study, suggested that bow-ties in developmental gene regulatory network can evolve due to hierarchy in specificity [79].

Many developmental gene regulatory networks have bow-tie structures in which a single intermediate gene (‘input-output’ or ‘selector’ gene) combines information from multiple patterning genes (the input layers) and then initiates a self-contained developmental program by regulating an array of output genes [5,6] that can produce a large variety of morphologies [17—20].

In developmental gene regulatory networks , modulated expression of the ‘waist’ (‘input-output’ or ‘selector’) gene can result in markedly different phenotypes.

From such a paradigmatic example it is clear that differentiation processes are the result of the interplay of complex regulatory networks acting inside the cell and external stimuli, coming from both the adjacent cells and the environment.

These processes are highly dynamical, directed by complex regulatory networks involving cell-to-cell interactions, and often triggered by external stimuli.

In this work, we develop a simple mathematical model by incorporating the recent experimental results on the genetic regulatory network of cyanobacteria into the theoretical machinery of system biology.

First we present the main actors of the basic regulatory network and the different dynamical interactions that take place during the differentiation process.