Gašper Tkačik

Life is never simple: whenever we think of life, we think of complexity. This complexity resides in life’s components: DNA sequences with gigabytes of information, or proteins, the cells’ nano-fabrication machinery. To an even higher degree, complexity is in the interactions of these components: regulatory networks of enzymes and hormones that respond to changing environments, neural networks that generate our thoughts and feelings, or even social networks and ecosystems. For physicists, the “book of nature” is written in the language of mathematics—and this belief has been proven right to a remarkable success. But what should we believe about the “book of life”? Can we only document, observe, measure, describe, and (at best) model the results of evolution? Or is there hope for a true mathematical theory to explain at least some part of this complexity, to understand why and how life’s components, networks and interactions have evolved and to predict their functioning from first principles?

Gašper Tkačik’s research focuses on the latter: At the Institute of Science and Technology (IST Austria) in Klosterneuburg, he studies biological networks that process information—including chemical reaction networks in cells and networks of neurons in the brain—from an interdisciplinary perspective. His research group brings together information theory to measure how well a given network can transmit information, statistical physics to describe how networks made of many interacting components behave collectively, biophysics to quantify the constraints—in terms of space and time, energy expenditure, noise, and connectivity—, and biology to understand the ultimate evolutionary function of these networks. The researchers are trying to answer the following questions: What would be the mathematically optimal way to build a network, considering given biophysical constraints and the desired biological function? How does this optimal prediction compare with what we empirically observe in different organisms?

In humble day-to-day practice, Gašper Tkačik and his group regard themselves as “inverse engineers”: rather than designing and building, they observe what evolution has created and ask whether the result is optimally built to some unknown specification. In the long run, the researchers’ goal is to find matches between mathematical theories for biological networks and empirical data to demonstrate that evolution, the ultimate blind tinkerer, is sometimes forced into regimes where ab initio prediction in the spirit of the “mathematical book of nature” is possible.

Gašper Tkačik hat 2001 das Diplomstudium Mathematische Physik an der Universität Ljubljana abgeschlossen und war bis 2002 an dieser Universität „Graduate Research Fellow“ an der Fakultät für Mathematik und Physik. 2007 promovierte er im Fach Physik an der Universität Princeton, wo er anschließend auch eine Postdoc-Stelle innehatte. Von 2008-2010 war Gašper Tkačik Postdoc an der University of Pennsylvania, Philadelphia. 2011 kam er als Assistant Professor ans Institute of Science and Technology Austria (IST Austria), wo er seine Forschungsgruppe „Theoretical Biophysics and Neuroscience“ aufbaute; 2017 wurde Gašper Tkačik dort zum Tenured Professor ernannt.