
Researchers from our center, in collaboration with State University of New York, Binghamton University and the Instituto Gulbenkian de Ciência developed a mathematical and computational framework to understand how biochemical networks contribute to the evolvability, robustness, and resilience of biological organisms.
In a paper in the journal Journal of the Royal Society Interface, Luis Rocha, George J. Klir Professor of Systems Science, and Drs. Manuel Marques-Pita and Santosh Manicka (who earned his Ph.D. in complex networks and systems from the Luddy School), show that a large amount of redundancy exists in how genes, proteins and other biochemical components process signals. This results in much robustness to perturbations, allowing biological systems to exist in a stable or near-critical dynamical regime, despite being composed of thousands of biochemical variables which would ordinarily result in chaotic dynamics.
The measure of effective connectivity developed by Rocha and Marques-Pita captures redundancy in automata networks and is shown in the paper to be highly predictive of dynamical regime of biochemical systems ranging from flower development to breast cancer in humans. The approach thus adds empirical validity to several well-known hypotheses in theoretical biology: 1) that canalization adds robustness to biological development put forth by C.H. Waddington, 2) that redundancy is essential for evolvability put forth by Michael Conrad, and 3) that biological organisms exist in a near-critical dynamical regime put forth by Stuart Kauffman. The new work further connects the three hypotheses by equating canalization with redundancy, providing a measure of effective connectivity based on dynamical redundancy, and further showing that this measure very accurately predicts the dynamical regime of biochemical networks.
You can read the article following the links in reference:
Manicka Santosh, Marques-Pita Manuel and Rocha Luis M. [2022]. “Effective connectivity determines the critical dynamics of biochemical networks.” J. R. Soc. Interface. 19(186):20210659. doi: 10.1098/rsif.2021.0659.