Computing minimal all perturbations sets in ivdTEM regulatory network | The MIS algorithm proposed in [43,44] was then applied to compute all possible minimal perturbation sets to force the network into desired steady state or phenotype. |
Computing minimal all perturbations sets in ivdTEM regulatory network | either high or low) in the desired final steady state . |
Construction of dynamical models from the experimental data using TEM differentiated in vitro | 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]. |
Construction of dynamical models from the experimental data using TEM differentiated in vitro | The term minimal implies that no other subset of an M18 pattern can lead to the desired steady state behavior. |
Construction of dynamical models from the experimental data using TEM differentiated in vitro | However, for a given network, there can be more than one MIS patterns to generate the same steady state . |
Discussion | The physiologically relevant combinations of ligands were discovered by applying the recently proposed MIS algorithm [43,44] to predict all minimal perturbations in the inferred regulatory network that can transition TEM into desired steady states (Table 4). |
Introduction | The state of the network at a given instant can change depending on the state of the other nodes and can ultimately stabilize into attractors of either a single state ( steady state ) or an oscillating set of states (cycling attractors) [2]. |
Introduction | The Boolean steady state of the network has been shown to correspond to the cellular states for various regulatory networks in the past [3]. |
Introduction | Boolean modeling of steady state transitions helps in understanding the influence of perturbations on system wide behavior and has been used to identify the key molecular mechanisms controlling gene expression [4,5,6] and regulation [7,8], cell differentiation [9] and signal transduction [10,11,12,13,14,15,16,17,18,19,20]. |
The plasticity of TEM predicted computationally was validated experimentally using TEM differentiated in vitro | Therefore blood and tumor TEM can be viewed as two distinct cell steady state behaviors and ivdTEM as an intermediate state (Tables 2 and 3). |
The plasticity of TEM predicted computationally was validated experimentally using TEM differentiated in vitro | blood TEM) steady states respectively. |
Modeling | For the computation of the PRC, we evolved the model until it reached a steady state and then applied pulses of current (0.5 ms duration and 0.5 nA amplitude) at random times with a mean period between perturbations of 2.5 HZ. |
Modeling | In both cases, the algorithm employed to compute the PRC differed from that used in the single compartment model and resembled the one adopted in [42, 43]: briefly, after evolving the model until it reached a steady state , we identified two spike times to and t1 such that the 181 1‘1 — to was of the appropriate duration. |
Results | Similarly, it is often necessary to wait until PCs reach a steady state firing rate before initiating the repeated stimulation protocol. |
Results | 1A), employed to speedup convergence to the firing rate steady state and reduce very slow fluctuations. |
by | Additionally, we set the simulation temperature to 28°C, in order to span a broader range of steady state firing frequencies, particularly in the low end of the spectrum. |
Equivalent irreversible kinetic scheme for the theory | Any kinetic scheme, reversible or irreversible, that obeys a similar set of equations at steady state Will have a linear-fractional dose-response. |
Equivalent irreversible kinetic scheme for the theory | In steady state , the neW product obeys [X’] = q[X] [P] With mass which mimics a CLS step. |
Equivalent irreversible kinetic scheme for the theory | Reversible and irreversible reactions could be combined as long as the steady state conditions resemble the equilibrium conditions (2) and the mass conservation conditions have bilinear form. |
Theory of non-cooperative gene induction | In steady state , the concentrations obey the equilibrium conditions and the mass conservation conditions where X? |
Discussion | We have shown that one important ingredient affecting the dynamical behavior of the chain is noise, which plays a key role in onset of the pattern formation, i.e., the transition from the initial chain of vegetative cells to the steady state in which heterocysts coexist with vegetative cyanobacteria. |
Regulatory equations | (5) for the steady state . |
Unicellular dynamics | Taking into account the difference between the relaxation times of the constituents of the model, given by the inverses of d* (see Table 1), we can interpret it as composed of two temporally separated systems: a rapid one, formed by HetR and NtcA, showing fast dynamics that relaxes to its steady state almost instantaneously and a slow one, composed of PatS and cN, whose evolution is dictated by the values of HetR and thA in their instantaneous equilibrium. |
Unicellular dynamics | The steady state is very robust against perturbations since it is far from the bifurcation region and there is a significant distance to the saddle in the qr — qa plane. |