| Popis: |
Biomolecular networks have already found great utility in characterizing complex biological systems arising from pair-wise interactions amongst biomolecules. Here, we review how graph theoretical approaches can be applied not only for a better understanding of various proximate (mechanistic) relations, but also, ultimate (evolutionary) structures encoded in such networks. A central question deals with the evolutionary dynamics by which different topologies of biomolecular networks might have evolved, as well as the biological principles that can be hypothesized from a deeper understanding of the induced network dynamics. We emphasize the role of gene duplication in terms of signaling game theory, whereby sender and receiver gene players accrue benefit from gene duplication, leading to a preferential attachment mode of network growth. Information asymmetry between sender and receiver genes is hypothesized as a key driver of the resulting network topology. The study of the resulting dynamics suggests many mathematical/computational problems, the majority of which are intractable but yield to efficient approximation algorithms, when studied through an algebraic graph theoretic lens. |
