The sismonr Package: Simulation of In Silico Multi-Omic Networks in R

Abstract

Cellular regulatory networks can be deciphered from multi-omics data using network inference methods. To assess the performance of such methods, one can use simulated data. To be insightful, the simulations must mimic the complexity of biological systems, including post-transcriptional regulation and genetic variations. Here we present our new simulation R package, sismonr, capable of generating gene expression profiles for complex in silico regulatory systems.

Cite us

Angelin-Bonnet, O., Biggs, P. J., & Vignes, M. (2018). The sismonr Package: Simulation of In Silico Multi-Omic Networks in R. In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 2729-2731). IEEE. https://doi.org/10.1109/BIBM.2018.8621131

Or with bibtex:

@inproceedings{angelin2018sismonr,
	title        = {The sismonr Package: Simulation of In Silico Multi-Omic Networks in R},
	author       = {Angelin-Bonnet, Olivia and Biggs, Patrick J and Vignes, Matthieu},
	year         = 2018,
	booktitle    = {2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)},
	pages        = {2729--2731},
	organization = {IEEE},
	doi          = {10.1109/BIBM.2018.8621131}
}