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Evolutionary processes are at the heart of many problems that we face in our world today, ranging from antibiotics resistance evolution to species extinction. Addressing such problems requires models of the underlying causes. Laurence Loewe aims to improve the quality of these models by quantifying evolution with increasing precision. To this end he estimates the strength of selection in various systems, using different approaches, including the analysis of DNA sequences by population genetics methods. Loewe also develops a new approach that builds on existing quantitative models from molecular systems biology and links them to potential fitness correlates to help estimate distributions of mutational effects in silico. This is an important part of what he calls evolutionary systems biology which aims to combine the strengths of evolutionary genetics and systems biology. To facilitate his work he is developing Evolvix a biologist-friendly model description programming language that is being designed to make it easy for biologists to describe their systems in such a way that computers can automatically analyze these models. Because these computational tasks can become very challenging, Loewe is integrating Evolvix with Evolution@home, the first globally distributed computing system for evolutionary biology. The work in Loewe’s lab is ‘in silico’ only, but addresses a broad range of questions from the molecular systems biology of circadian clocks and cholesterol biosynthesis, over antibiotics resistance evolution to genome evolution, the population genetics of harmful mutations and species extinction. Much of this work is aimed at quantifying evolutionary processes better, since this is key to developing practical strategies for tackling many applied problems. Nothing in biology makes sense except when properly quantified in the light of evolution.