Abstract
The key information driving the development and fate of cells and organisms is encoded in their DNA, and processed through complex regulatory interactions involving different molecular scales. In particular, the production of mRNAs and proteins from genes is a complex process, subject to tight regulation by other gene products. Modelling such regulatory networks allows us to gain a better understanding of the molecular processes governing gene regulation, and enables the simulation of experimental-like data in order to test statistical tools used for the reconstruction of these networks. In this talk we highlight the challenges of building a realistic model for gene regulatory networks, with an emphasis on the often overlooked post-transcriptional regulation. We introduce our R package sismonr (https://CRAN.R-project.org/package=sismonr) for generating gene regulatory networks that include different types of regulation, ranging from transcription regulation to post-translational modification, protein-coding as well as non-coding genes, and simulating molecular profiles for genetically diverse in silico individuals with unrestricted ploidy.
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