Advances and limitations of maximum likelihood phylogenetics
Seminar Room 1, Newton Institute
I'll present recent developments in inferring phylogenies from sequences by maximum likelihood (ML). In fact, this approach involves two main components: probabilistic modelling of substitution events, and algorithmics to infer near-optimal trees. I'll show that algorithmics has considerably progressed during the last few years, allowing now for fast ML inference from large datasets. On the other hand, I'll underline the difficulties encountered with modelling, especially of protein evolution, and show that elaborating more realistic and improved substitution models is a major challenge.
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