Bayesian Top-Down Protein Sequence Alignment with Inferred Position-Specific Gap Penalties.
We describe a Bayesian Markov chain Monte Carlo (MCMC) sampler for protein multiple sequence alignment (MSA) that, as implemented in the program GISMO and applied to large numbers of diverse sequences, is more accurate than the popular MSA programs MUSCLE, MAFFT, Clustal-Ω and Kalign. Features of GI...
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| Автори: | , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
Public Library of Science (PLoS)
2016-05-01
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| Серія: | PLoS Computational Biology |
| Онлайн доступ: | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1004936&type=printable |
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