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Tracing Molecular Chronologies Onto Growing Biological Networks
M Fayez Aziz1, Gustavo Caetano-Anollés2
1Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA. aziz4@illinois.edu.
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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.
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