Efficient Inference in Phylogenetic InDel Trees

Part of Advances in Neural Information Processing Systems 21 (NIPS 2008)

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Alexandre Bouchard-côté, Dan Klein, Michael Jordan


Accurate and efficient inference in evolutionary trees is a central problem in computational biology. Realistic models require tracking insertions and deletions along the phylogenetic tree, making inference challenging. We propose new sampling techniques that speed up inference and improve the quality of the samples. We compare our method to previous approaches and show performance improvement on metrics evaluating multiple sequence alignment and reconstruction of ancestral sequences.