Biological networks

...networks are now widely recognized not only as outcomes of complex interactions, but as key determinants of structure, function, and dynamics in systems that span the biological, physical, and social sciences... —Joshua S. Weitz et al.

Biological networks resemble many types of man-made networks, in particular those types of man-made networks consisting of diverse structures and functions, like the World Wide Web.

Both types of networks consist of a collection of parts, the parts themselves differing in type, with multiple copies of each type, parts capable of interconnecting, the interconnections tying all the parts together into a whole entity with a particular topology (i.e., road map, or blueprint) made up of substructures of parts and modules of substructures, the interconnected parts capable of interacting, the interactions capable of producing particular changes in the structure of each part, in their properties, enabling intercommunication with signals that convey information, the whole structure a functional unit 'designed' for a purpose.

Biological networks differ from such man-made networks as the World Wide Web, however, in having no human designer or initiating human engineer. The prototypical biological network is the biological cell.

Biological networks emerged from extra-human nature by natural organic experiments coupled to evolutionary processes. Their foundational network-as-a-whole consists of a biological cell, the cell, an overlay of differing types of networks, all self-fabricated into a self-organized computationally-enabled information-processing bio-computer. The living biocomputer network’s design emerged naturally, basically operating toward the preservation of its living physico-chemical foundation.

Biological networks function autonomously, exhibiting behaviors/functions/properties not in practice predictable or explicable from the properties of its parts. The network-as-whole influences the functioning of its parts and thereby its own expression. Cell cooperate with other cells to generate multicellular complexes, some relatively simple communities, some with an ability to more less consciously design and construct networks as artifacts, inorganic as well as organic ones.

Overview

See also: Systems biology

We have a new continent to explore and will need maps at every scale to find our way. —Dennis Bray

Networks represent (i.e., 're-present') a system as 'nodes' (also referred to as 'vertices') and interactions among the nodes (also referred to as 'edges' or 'arrows' or 'links'). For example, in a spoken sentence, words and phrases make up the nodes, and the interconnections of syntax (subject-to-predicate, preposition-to-object of preposition, etc.) make up the links. In intracellular biological networks, typically, molecules make up the nodes, their interactions, the edges. Intracellular molecular networks represent specific functions in the cell; genes and proteins make up the nodes, and their interactions make up the edges or arrows. The network of the nervous system has neurons as nodes and axons and dendrites as edges. The Internet has a network of HTML files and links pointing between them. Many networks accept inputs of one kind and return outputs of a different kind.

One finds networks everywhere in biology, from intracellular signaling pathways, to intra-species cooperative networks, to ecosystem food webs. Humans deliberately construct social networks of individuals working (more or less) to a common purpose, such as the U.S. Congress; they also construct networks of electronic parts to produce, for example, mobile phones; and networks of sentences and paragraphs to express messages, including this very article. Researchers view the World Wide Web as a network, and study its characteristics and dynamics. 

According to Alon, "The cell can be viewed as an overlay of at least three types of networks, which describes protein-protein, protein-DNA, and protein-metabolite interactions." Alon notes that cellular networks are like many human engineered networks in that they show 'modularity', 'robustness', and 'motifs':

• Modules comprise subnetworks with specific functions differing from those of other modules, and which typically but not invariably connect with other modules, often only at one input node and one output node. An individual module achieves its status as a distinct entity not only by its functional specificity but also by spatial specificity (e.g., ribosomes) or by chemical specificity (e.g., signal transduction networks).
  • Modularity helps to facilitate real-time system adaptability to environmental change, as the organization of modules in the system contributes to the emergent properties of the system.  It also facilitates evolutionary adaption, as, to select an adaptation, evolution may need tinker with just a few modules rather than with the whole system. Evolution can sometimes 'exapt' existing modules for new functions that contribute to reproductive fitness. For example, Darwin surmised that the swim bladder of skeletally heavy fish evolved as an adaptation for control of buoyancy but was exapted as a respiratory organ in certain fish and in land vertebrates.  

• Robustness refers to how a network maintains its functionality despite environmental perturbations that affect the components. Robustness also reduces the range of network types that researchers must consider, because only certain types of networks are robust.

• Network motifs offer economy of network design, as the same circuit can have many different uses in cellular regulation, as in the case of autoregulatory circuits and feedforward loops. Nature selects motifs in part for their ability to make networks robust, so systems use motifs that work well over and over again in many different networks. In several well-studied biological networks, the abundance of network motifs — small subnetworks — correlates with the degree of robustness.
  • Networks, like those in cells and those in neural networks in the brain, use motifs as basic building blocks, like multicellular organisms use cells as basic building blocks. Motifs offer biologists a level of simplicity of biological functionality for their efforts to model the dynamics of organized hierarchies of networks.

The view of the cell as an overlay of mathematically-definable dynamic networks can reveal how a living system can exist as an improbable, intricate, self-orchestrated dance of molecules. The 'overlay of networks' view also suggests how the concept of self-organized networks can extend to all higher levels of living systems.

Small world networks

Holding reference: