Table 1 A list of network sampling and simulation methods
Methods ⇓∖ Features ⇒ | Method-based on | Input | Output |
|---|---|---|---|
sgnesR (SGN sim [13]) | A set of biochemical reactions where transcription and translation of genes and proteins are modelled as multiple time delayed events and their activities are modelled by a stochastic simulation algorithm (SSA) [20] | S4 data object with a network of igraph class. | S4 data object which consists expression data matrix. |
AGN [25] | Set of biochemical reactions in the form of a network, simulation of the kinetics of systems of biochemical reactions based on differential equations. | SMBL | Text file |
GenGe [26] | Non linear differential equation system where degradation of biological molecules are modelled by a linear or Michalies-Menten kinetic and translation is described by a linear kinetic law by using several global and local perturbation parameters. | SMBL | Text file (numeric values). |
GRENDEL [27] | A set of differential equation system uses hill kinetics based activation and repression functions for the transcription rate law. | SMBL | Text file (numeric values) |
NetSim [9] | Differential equations are used to to model the dynamics of transcription and degradation along with the integration of fuzzy logic in order to define the complex regulatory mechanism | adjacency matrix with other parameters | list object in R |
RENCO [28] | Uses pre defined network topology or generates topologies to model ordinary differential equations and use Copasi for simulating expression data. | Text file | Text file |
SynTReN [8] | The interactions of a network uses non-linear functions based on Michaelis-Menten and hill enzyme kinetic equations to model gene regulation | Text file | Text file |