Networks are models of biological systems
A biological model is an idealistic construct, in simulacra , that allows us to understand, explain and predict biological phenomena. A network, in the current context, is a graph model of a biological system which depicts molecular entities and the interactions between them. Mathematically, a network is a graph G(V,E), where a set of vertices or alternatively nodes (V) map to biological entities, connected by a set of ordered pairs or edges E, which represent the relationships between nodes. Network models vary greatly in their coverage of established biological knowledge, level of detail and interoperability with other networks. A network model can be as simple as the interaction ”MDM2 binds to TP53” or can cover a system-level map that encompasses all known cellular processes. In some models, a single node may represent one entity, whereas others may have multiple nodes corresponding to the same entity but representing different states. Similarly, edges may have directionality that indicates the flow of cause and effect from reactant to product in an interaction or be undirected. They may also be signed, meaning they describe the nature of the reaction (ex. activation/inhibition), or unsigned. Some highly complex network models even account for stochiometric ratios and reaction dynamics equations in their construction.
Several domains of biology are modeled by networks, including: (i) Metabolic pathways (Figure 1A) are usually characterized by the abstraction of enzymes, substrates, and products. Typically, these reactions involve small molecules, and an enzyme, often a protein, catalyzes the reaction. Inhibitors and activators can also modulate the catalysis event. (ii) Signaling pathways (Figure 1B), on the other hand, encompass a range of biochemical reactions, including binding, transportation, and catalysis events involving molecules and complexes. These pathways may describe molecular states such as cellular location, covalent and non-covalent modifications, and sequence fragments. (iii) Gene regulatory networks (Figure 1C) involve transcription and translation events, along with their control mechanisms. (iv) Molecular interactions (Figure 1D) are typically represented as undirected graphs and cover non-covalent binding events. (v) Genetic interactions (Figure 1E) capture relationships between two genes when the observed phenotypic consequence of perturbing both genes is different from what is expected given the phenotypes of each single gene perturbation, such as in the case of epistasis.