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Jean Gayon (IHPST & Pantheon-Sorbonne): Are population genetics models “reversible”: (ir)reversibility of evolution
12 December 2017 | 14 h 30 min - 16 h 00 min
Jean Gayon is the Director of the Institut d’Histoire et Philosophie des Sciences et des Techniques (IHPST) and Professor Emeritus at Université Paris 1 Panthéon-Sorbonne (Philosophy and history of science).
“Are population genetics models “reversible”: a case test for the problem of the (ir)reversibility of evolution”
Repetitiveness and reversibility have long been considered as characteristic features of scientific knowledge. In theoretical population genetics, repetitiveness is illustrated by a number of genetic equilibria realized under specific conditions. Since these equilibria are maintained despite a continual flux of changes in the course of generations (reshuffling of genes, reproduction…), it can legitimately be said that population genetics reveals important properties of invariance through transformation. Time-reversibility is a more controversial subject. Here, the parallel with classical mechanics is much weaker. Time-reversibility is unquestionable in some stochastic models, but at the cost of a special, probabilistic concept of reversibility. But it does not seem to be a property of the most basic deterministic models describing the dynamics of evolutionary change at the level of populations and genes. Furthermore, various meanings of ‘reversibility’ are distinguished. In particular, time-reversibility should not be confused with retrodictability.
André Ariew (Professor or Philosophy, University of Missouri, USA), Darwin’s use of statistics to develop his theory of evolution7 February | 14 h 30 min - 16 h 00 min at Centre de Génomique Fonctionnelle, Salle de réunion Sud
- 17 February at Centre de Génomique Fonctionnelle, Salle de réunion Nord
Thomas Kirkwood (Newcastle University and University of Copenhagen) – Understanding Ageing: The Great Puzzle of Our Time17 February | 17 h 30 min - 19 h 00 min at Salle de conférence du Centre de génomique fonctionnelle