Bayesian multiple protein structure alignment
Conference Paper
Multiple protein structure alignment is an important tool in computational biology, with numerous algorithms published in the past two decades. However, recently literature highlights a growing recognition of the inconsistencies among alignments from different algorithms, and the instability of alignments obtained by individual algorithms under small fluctuations of the input structures. Here we present a probabilistic model-based approach to the problem of multiple structure alignment, using an explicit statistical model. The resulting algorithm produces a Bayesian posterior distribution over alignments which accounts for alignment uncertainty arising from evolutionary variability, experimental noise, and thermal fluctuation, as well as sensitivity to alignment algorithm parameters. We demonstrate the robustness of this approach on alignments identified previously in the literature as "difficult" for existing algorithms. We also show the potential for significant stabilization of tree reconstruction in structural phylogenetics. © 2014 Springer International Publishing Switzerland.
Full Text
Duke Authors
Cited Authors
- Wang, R; Schmidler, SC
Published Date
- January 1, 2014
Published In
Volume / Issue
- 8394 LNBI /
Start / End Page
- 326 - 339
Electronic International Standard Serial Number (EISSN)
- 1611-3349
International Standard Serial Number (ISSN)
- 0302-9743
International Standard Book Number 13 (ISBN-13)
- 9783319052687
Digital Object Identifier (DOI)
- 10.1007/978-3-319-05269-4_27
Citation Source
- Scopus