Skip to main content
Journal cover image

Bayesian multiple protein structure alignment

Publication ,  Conference
Wang, R; Schmidler, SC
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
January 1, 2014

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.

Duke Scholars

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

ISBN

9783319052687

Publication Date

January 1, 2014

Volume

8394 LNBI

Start / End Page

326 / 339

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Wang, R., & Schmidler, S. C. (2014). Bayesian multiple protein structure alignment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8394 LNBI, pp. 326–339). https://doi.org/10.1007/978-3-319-05269-4_27
Wang, R., and S. C. Schmidler. “Bayesian multiple protein structure alignment.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8394 LNBI:326–39, 2014. https://doi.org/10.1007/978-3-319-05269-4_27.
Wang R, Schmidler SC. Bayesian multiple protein structure alignment. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2014. p. 326–39.
Wang, R., and S. C. Schmidler. “Bayesian multiple protein structure alignment.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8394 LNBI, 2014, pp. 326–39. Scopus, doi:10.1007/978-3-319-05269-4_27.
Wang R, Schmidler SC. Bayesian multiple protein structure alignment. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2014. p. 326–339.
Journal cover image

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

ISBN

9783319052687

Publication Date

January 1, 2014

Volume

8394 LNBI

Start / End Page

326 / 339

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences