Scientists created a framework to test the predictions of biological optimality theories, including evolution.
Evolution adapts and optimizes organisms to their ecological niche. This could be used to predict how an organism evolves, but how can such predictions be rigorously tested? The Biophysics and Computational Neuroscience group led by professor Gašper Tkačik at the Institute of Science and Technology (IST) Austria has now created a mathematical framework to do exactly that.
Evolutionary adaptation often finds clever solutions to challenges posed by different environments, from how to survive in the dark depths of the oceans to creating intricate organs such as an eye or an ear. But can we mathematically predict these outcomes?
This is the key question that motivates the Tkačik research group. Working at the intersection of biology, physics, and mathematics, they apply theoretical concepts to complex biological systems, or as Tkačik puts it: “We simply want to show that it is sometimes possible to predict change in biological systems, even when dealing with such a complex beast as evolution.”
Climbing mountains in many dimensions
In a joint work by the postdoctoral fellow Wiktor Młynarski and PhD student Michal Hledík, assisted by group alumnus Thomas Sokolowski, who is now working at the Frankfurt Institute for Advanced Studies, the scientists spearheaded an essential advance towards their goal. They developed a statistical framework that uses experimental data from complex biological systems to rigorously test and quantify how well such a system is adapted to its environment. An example of such