Journal Article

A “Long Indel” Model For Evolutionary Sequence Alignment

I. Miklós, G. A. Lunter and I. Holmes

in Molecular Biology and Evolution

Published on behalf of Society for Molecular Biology and Evolution

Volume 21, issue 3, pages 529-540
Published in print March 2004 | ISSN: 0737-4038
Published online March 2004 | e-ISSN: 1537-1719 | DOI: https://dx.doi.org/10.1093/molbev/msh043
A “Long Indel” Model For Evolutionary Sequence Alignment

More Like This

Show all results sharing these subjects:

  • Evolutionary Biology
  • Molecular and Cell Biology

GO

Show Summary Details

Preview

We present a new probabilistic model of sequence evolution, allowing indels of arbitrary length, and give sequence alignment algorithms for our model. Previously implemented evolutionary models have allowed (at most) single-residue indels or have introduced artifacts such as the existence of indivisible “fragments.” We compare our algorithm to these previous methods by applying it to the structural homology dataset HOMSTRAD, evaluating the accuracy of (1) alignments and (2) evolutionary time estimates. With our method, it is possible (for the first time) to integrate probabilistic sequence alignment, with reliability indicators and arbitrary gap penalties, in the same framework as phylogenetic reconstruction. Our alignment algorithm requires that we evaluate the likelihood of any specific path of mutation events in a continuous-time Markov model, with the event times integrated out. To this effect, we introduce a “trajectory likelihood” algorithm (Appendix A). We anticipate that this algorithm will be useful in more general contexts, such as Markov Chain Monte Carlo simulations.

Keywords: Stochastic modeling of molecular evolution; Structural alignment; Maximum Likelihood evolutionary time estimation

Journal Article.  8035 words.  Illustrated.

Subjects: Evolutionary Biology ; Molecular and Cell Biology

Full text: subscription required

How to subscribe Recommend to my Librarian

Users without a subscription are not able to see the full content. Please, subscribe or login to access all content. subscribe or login to access all content.