“One of the greatest contemporary scientific challenges is to understand in depth the mathematical properties that govern living things. » Physicist Thomas Fink, whose research at the London Institute for Mathematical Sciences focuses on theoretical biology, does not mince words. So when he talks about the work on “the algorithmic nature of evolution” published on March 11 in the journal PNAS by an international team of researchers, his enthusiasm is beyond doubt.
The authors of the article in question started from an observation that challenges: everywhere in living things, at all scales and in very varied contexts, there is an overrepresentation of “simple” shapes (symmetrical shapes, shapes with a pattern which is repeated…). For example, to fulfill their functions in our body, proteins need to assemble together, creating large assemblies. Gold, “we observe an overrepresentation of very symmetrical protein assemblies, compared to those that are not very symmetrical”, relates Sylvain Mousset, lecturer at the University Claude-Bernard-Lyon-I and researcher at the Laboratory of Biometrics and Evolutionary Biology. However, proteins could assemble together in many other, asymmetrical ways. “It’s like plunging your hand into a haystack and each time you find a needle there: it’s still very surprising! »smiles Ard Louis, co-author of the study and professor of theoretical physics at the University of Oxford, whose work is at the border between chemistry, physics and biophysics.
A monkey typing on a keyboard
To propose an explanation for this privileged appearance of simple forms in nature, the international team of researchers behind the article turned to… algorithmic information theory, a sub-field of theoretical computer science. “The idea that evolution is some kind of grand calculus has been around for a long time, though it ruffles some people”, says mathematician and computer scientist Jean-Paul Delahaye, professor emeritus at the University of Lille and researcher at the Cristal laboratory. But if the idea is not new, “The strength of this article is that not only do the authors present a very simple model to explain the phenomenon studied, but they also compare the predictions of their model to real data, and it fits rather well”emphasizes Sylvain Billiard, lecturer in evolutionary biology at the University of Lille.
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