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Table 1 A list of network sampling and simulation methods

From: sgnesR: An R package for simulating gene expression data from an underlying real gene network structure considering delay parameters

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