Gene Regulatory Networks

Every phase of the growth and physiology of biological organisms depends on the complex interplay of effects caused by multiple genes, which regulate each other by processes such as the generation of proteins with excitatory or inhibitory effects on the expression of other genes. Gene regulatory networks represent such interactions using graph models whose nodes represent genes and edges represent direct interactions between genes. The presence of edges and values for other network parameters must be learnt from observational data such as measurements of gene expression data at multiple time instants. This is a difficult task from both experimental and computational perspectives, but with great potential to improve our understanding of biological processes. For this special issue, papers are sought on all aspects of gene regulation network formulation and learning, including experimental and computational approaches.