The past decade has witnessed the transition of computational biology, population genetics, and evolutionary biology, from relatively data-sparse and theory-driven subjects, into highly empirical and data-driven disciplines. The continuing data-explosion has meant that descriptive studies have tended to outpace more in-depth theory development and statistical modeling. Nevertheless, in the past decade our understanding of genome and population biology and evolution has increased dramatically, and combined with the availability of data, it seems that the time is ripe to reap the benefits of these developments, by giving a new impetus to statistical modeling and theory development in computational biology, broadly defined.
In this workshop, we aim to bring together leading experts on genome biology and evolution, with an interest in quantitative modeling. We hope to create an interesting mix of, on the one hand, researchers whose main focus is on biology or evolution, with researchers who are primarily interested in the modeling aspects of these biological problems, from a mathematical, statistical, or algorithmic perspective.
The program is organized around the following five interest areas:
The workshop will feature about 20 short talks spread over 5 days, with plenty of time in between. In these slots it will be possible (and strongly encouraged) to organize informal breakout sessions in smaller groups, to discuss topical problems in more depth.