Hey City Zen!

I don't often post about our science on this blog, but it is also my Zen, I am going to start posting updates of that dimension here as well.

In a paper in the journal Journal of the Royal Society Interface,  in a collaboration started long ago with Manuel Marques-Pita and Santosh Manicka, we 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 we developed 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.

Beyond the biochemical models we tested, because automata networks are canonical examples of complex systems, the work suggests that redundancy and canalization should be important design principles of resilient and evolvable organizations.

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.

Labels: #Biology, #Complexity, #ComplexNetworks, #ComplexSystems, #Evolution, #Resilience, #Robustness, #Science

The year ends with tons of media attention, a bit of media whoring, really: The Independent, Time, Publico, GizModo, The National Post, Men's Fitness, Mother Jones, ArsTechnica, The Sun, Drive with Yasmeen Khan (at 17:30) (audio of interview), etc.

What is important is that it refers to a paper I'm really proud of. First, because it was a great collaboration that started with Joana Sá at Gulbenkian, who had the idea to look at the birth peaks problem. Then it involved Johan Bollen, a long time partner in crime, and Ian Wood, one my students who has been a real pleasure to work with. I am very proud with our demonstration that Data Science, Computational Social Science, and Complexity research can be used to obtain surprising results and invalidate previous hypotheses. In other words, Data Science that does not simply validate our pre-existing biases and accepted wisdom, but demonstrates new explanations. In this case, we found that online interest in sex rises at Christmas and other cultural celebrations, with more births nine months later, in what is the first global analysis of human birth-rate cycles. Another bonus was that to reach our results, we developed a novel spectral methodology for sentiment analysis on social media. To make things even better, it is fun Science dealing with the Sweetest Taboo, as all the media attention shows and Sade knew all along: Everyday is Christmas, and every night is New Years eve.

Labels: #Christmas, #Complexity, #DataScience, #Sade, #Sex