Gene Regulatory Networks: A Primer in Biological Processes and Statistical Modelling.
Modelling gene regulatory networks requires not only a thorough understanding of the biological system depicted, but also the ability to accurately represent this system from a mathematical perspective. Throughout this chapter, we aim to familiarize the reader with the biological processes and molecular factors at play in the process of gene expression regulation. We first describe the different interactions controlling each step of the expression process, from transcription to mRNA and protein decay. In the second section, we provide statistical tools to accurately represent this biological complexity in the form of mathematical models. Among other considerations, we discuss the topological properties of biological networks, the application of deterministic and stochastic frameworks, and the quantitative modelling of regulation. We particularly focus on the use of such models for the simulation of expression data that can serve as a benchmark for the testing of network inference algorithms.
['Angelin-Bonnet|Olivia|O|', 'Biggs|Patrick J|PJ|', 'Vignes|Matthieu|M|']
D000465:Algorithms D020869:Gene Expression Profiling D005786:Gene Expression Regulation D053263:Gene Regulatory Networks D008957:Models, Genetic D015233:Models, Statistical D013269:Stochastic Processes D049490:Systems Biology
Gene expression regulation Deterministic and stochastic models Molecular regulatory interactions Post-transcriptional regulation Post-translational regulation Regulatory network modelling Systems biology data simulation