2008
NeurIPS
NeurIPS 2008
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.
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Interdisciplinary Bridge
- Artificial Intelligence and Data Science & Analytics and Healthcare & Medicine and Interdisciplinary
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Trend Setter
- Markov Chain Monte Carlo
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Keyword Pioneer
- sequence alignment
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Hot Topic Early Bird
- markov chain monte carlo
Topics
Machine Learning > Optimization & Theory > Bayesian Inference
Healthcare & Medicine > Research > Bioinformatics
Data Science & Analytics > Methods > Time Series
Artificial Intelligence > Bayesian & Probabilistic > Bayesian Inference
Machine Learning > Bayesian & Probabilistic > Markov Chain Monte Carlo
Interdisciplinary > Science > Bioinformatics
Keywords
bayesian inference
markov chain monte carlo
sequence alignment
ancestral sequences
evolutionary trees
insertions deletions
mcmc sampling
ancest序列 reconstruction
evolutionary biology
phylogenetic inference
phylogenetic tree
multiple sequence alignment
ancest sequence reconstruction
insertions and deletion
insertion deletion
ancestral sequence reconstruction