Features

Cellnition embodies a range of functionality, including:

• Work with regulatory networks imported from Cellnition's network_library, use Cellnition to procedurally generate regulatory networks with random or scale-free degree distributions, or import your own user-defined regulatory networks as directed graphs with activating or inhibiting edge characteristics (see Tutorial 1 and Tutorial 2 for some examples).
• Analyze and characterize regulatory network graphs with a variety of metrics (see the characterize_graph method and Tutorial 1 and Tutorial 2).
• Use directed graph representations of regulatory networks to build fully-continuous, differential-equation based simulators of network dynamics (see ProbabilityNet and Tutorial 1).
• Use directed graph representations of regulatory networks to build logic-equation based Boolean simulators of network dynamics (see BooleanNet
  and Tutorial 2).
• Explore regulatory network dynamics with comprehensive equilibrium state search and characterization capabilities, along with temporal simulators (see Tutorial 1 and Tutorial 2 for some examples).
• Create simulated datasets, including simulation of automated gene-knockout experiments for a continuous regulatory network model (see GeneKnockout).
• Generate NFSMs for continuous models (see StateMachine and Tutorial 1) or for Boolean models (see BoolStateMachine and Tutorial 2).
• Create and export a variety of plots and visualizations, including of the regulatory network model analytic equations, regulatory network directed graphs, heatmaps of gene expressions in equilibrium states, gene expressions in temporal simulations, and depictions of the general NFSM and the event-driven NFSM (see Tutorial 1 and Tutorial 2 for some examples).