|Evolutionary games in finite populations
Evolutionary game theory is the study of frequency dependent selection. Those strategies that are more successful in a game produce more offspring and spread in the population. Strategies can either spread genetically (in biological contexts) or by imitation (in social contexts).
Evolutionary games are typically described in infinite, well mixed populations. A large portion of research in this field now addresses spatially structured populations. But even in well-mixed populations, several new aspects arise when a population of finite size is considered. These systems are stochastic in the generic case, which provides a link between theoretical population genetics and evolutionary game theory.
A. Traulsen, J.C. Claussen, and C. Hauert, PRL 95:238701 (2005)
A. Traulsen, J.M. Pacheco, and M.A. Nowak, JTB 246:522 (2007)
J.C. Claussen and A. Traulsen, PRL 100:058104 (2008)
A. Traulsen, N. Shoresh, and M.A. Nowak, BMB 70:1410 (2008)
P.M. Altrock and A. Traulsen, NJP 11:013012 (2009)
|The evolution of cooperation
Why should we help others that we only meet once? Rational individuals should not open the door for a stranger or make any anonymous voluntary contributions. However, in certain contexts it becomes advantageous to cooperate with others, for example if this helps to build a reputation or if someone cooperates with her team that competes with another team.
Currently, we are working on multilevel selection, tag-based cooperation, and the emergence of costly peer-punishment.
Traulsen and M.A. Nowak, PNAS 103:10952 (2006)
J.M. Pacheco, A. Traulsen, and M.A. Nowak, PRL 97:258103 (2006)
A. Traulsen and M.A. Nowak, PLoS One 2:e270 (2007)
Hauert, A. Traulsen, H. Brandt, M.A. Nowak, and K. Sigmund, Science 316:1905 (2007)
A. Traulsen, C. Hauert, H. de Silva, M.A. Nowak, and K. Sigmund, PNAS 106:709 (2009)
|Dynamics of blood disorders
Mammals have a hierarchical architecture of blood formation. At the root of this are relatively few stem cells, which proliferate slowly. They differentiate more and more to produce the huge amount of fast proliferating cells that make up the bulk of blood cells.
Starting from a reference model of blood formation in healthy humans, we have addressed the dynamics of different diseases, such as paroxysmal nocturnal hemoglobinuria, chronic myeloid leukemia or cyclic neutropenia. In all these cases, we can capture the clinical dynamics of the diseases with a simple mathematical model for the hierarchical architecture of the blood system.
D. Dingli, A. Traulsen, and J.M. Pacheco, PLoS One 2:e345 (2007)
A. Traulsen, J.M. Pacheco, and D. Dingli, Stem Cells 25:3081 (2007)
D. Dingli, J.M. Pacheco, and A. Traulsen, PRE 77:021915 (2008)
D. Dingli, A. Traulsen, and J.M. Pacheco, Clinical Leukemia 2:133 (2008)
D. Dingli, A. Traulsen, T. Antal, and J.M. Pacheco, AJH 83:920 (2008)
|The speed of evolution
How fast is evolution? This question is not only of general interest, but also highly relevant in the context of the somatic evolution of cancer, where the accumulation of several mutations ultimately leads to the development of the disease. We are interested in the conditions under which evolution becomes faster or slower as well as in the optimal, fastest evolutionary trajectories.
N. Beerenwinkel, T. Antal, D. Dingli, A. Traulsen, K.W. Kinzler, V.E. Velculescu, B. Vogelstein, and M.A. Nowak, PLoS CB 3:e225 (2007)
A. Traulsen, Y. Iwasa, and M.A. Nowak, JTB 249:617 (2007)