ArticleBMC bioinformatics2017
sgnesR: An R package for simulating gene expression data from an underlying real gene network structure considering delay parameters.
Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- GRACKLE: an interpretable matrix factorization approach for biomedical representation learning.Bioinformatics (Oxford, England) · 2025Article
- TRENDY: gene regulatory network inference enhanced by transformer.Bioinformatics (Oxford, England) · 2025Article
- Identification of self-regulatory network motifs in reverse engineering gene regulatory networks using microarray gene expression data.IET systems biology · 2019Article
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Authors and funding
6 authors.
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Abstract
backgroundsgnesR (Stochastic Gene Network Expression Simulator in R) is an R package that provides an interface to simulate gene expression data from a given gene network using the stochastic simulation algorithm (SSA). The package allows various options for delay parameters and can easily included in reactions for promoter delay, RNA delay and Protein delay. A user can tune these parameters to model various types of reactions within a cell. As examples, we present two network models to generate expression profiles. We also demonstrated the inference of networks and the evaluation of association measure of edge and non-edge components from the generated expression profiles.
resultsThe purpose of sgnesR is to enable an easy to use and a quick implementation for generating realistic gene expression data from biologically relevant networks that can be user selected.
conclusionssgnesR is freely available for academic use. The R package has been tested for R 3.2.0 under Linux, Windows and Mac OS X.
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