Introduction to networks and graphs

Biological and biomedical networks are essential tools for studying complex interactions within biological systems. These networks represent relationships between biological entities such as DNA, RNA, proteins, and metabolites, with nodes representing the entities and edges symbolising the interactions or relationships between them (Koutrouli et al. 2020).

Biological networks are crucial for studying processes like gene regulation, signal transduction, and metabolic pathways, and they offer valuable insights into diseases and therapeutic targets. With the increasing availability of high-throughput data, biological networks continue to evolve, providing powerful tools for understanding the molecular mechanisms behind health and disease. These concepts are very nicely explained in the EMBL-EBI online tutorial: Network analysis of protein interaction data.

Here, we are only going to introduce some basic graph theory concepts that are useful for visualising mathematical models as graphs. If you are interested in a more mathematical description of network analysis techniques, take a look at this published review: A Guide to Conquer the Biological Network Era Using Graph Theory (Koutrouli et al. 2020).