Chronologies derived from phylogenetic reconstruction enable the tracing of evolutionary history onto networks that model the evolution of biological systems. Here, we outline protocols for constructing and analyzing time series of evolving biological networks, integrating molecular chronologies with dynamic network models to explore the evolution of structural and functional complexity. The methodology employs Pajek for network visualization and R packages for statistical tests to examine connectivity patterns, enabling the study of preferential attachment, degree distributions, and the interplay between long-term evolutionary trends and short-term adaptive dynamics. These approaches provide a framework for uncovering fundamental principles of molecular evolution across deep timescales.
Aziz et al. (Thu,) studied this question.