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.