Efficient Inference in Phylogenetic InDel Trees
Abstract
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.
Cite
Text
Bouchard-côté et al. "Efficient Inference in Phylogenetic InDel Trees." Neural Information Processing Systems, 2008.Markdown
[Bouchard-côté et al. "Efficient Inference in Phylogenetic InDel Trees." Neural Information Processing Systems, 2008.](https://mlanthology.org/neurips/2008/bouchardcote2008neurips-efficient/)BibTeX
@inproceedings{bouchardcote2008neurips-efficient,
title = {{Efficient Inference in Phylogenetic InDel Trees}},
author = {Bouchard-côté, Alexandre and Klein, Dan and Jordan, Michael I.},
booktitle = {Neural Information Processing Systems},
year = {2008},
pages = {177-184},
url = {https://mlanthology.org/neurips/2008/bouchardcote2008neurips-efficient/}
}