BOL

Advancing network science to understand the organisation, function and evolution of biological systems
We are seeking an ambitious PhD student to develop a new generation of approaches for understanding the structure and evolution of biological networks.

Biological systems are extraordinarily complex. Protein-protein interaction networks, gene regulatory networks, metabolic networks and other molecular interaction systems contain enormous numbers of components and interactions, and their organisation is both far from random and far from regular. Their networks exhibit hierarchy (a few nodes with many connections and many nodes with few), homophily (nodes which are more “similar” are more likely to connect), modularity and other forms of structure that emerge from the underlying biological processes governing how components interact. But only recently have methods been proposed to measure network complexity directly and parsimoniously.

So, how statistically complex are biological networks? What mechanisms generate this complexity? And, critically, how is this network complexity related to biological function and evolutionary history?

More at https://evoldir.net/brian/evoldir/GradStudentPositions//UK.Glasgow.UStrathclyde.Statistical_complexity_in_the_evolution_of_biological_networks