Statistical evaluation of NMR backbone resonance assignment

Authors:
Guohui Lin;Xiang Wan;Theodore Tegos;Yingshu Li
Affiliations:
Department of Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada.;Department of Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada.;Department of Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada.;Department of Computer Science, Georgia State University, P.O. Box 3994, Atlanta, GA 30302, USA
Venue:
International Journal of Bioinformatics Research and Applications
Year:
2006

Citing 2
Cited 0

An Efficient Branch-and-Bound Algorithm for the Assignment of Protein Backbone NMR Peaks

CSB '02 Proceedings of the IEEE Computer Society Conference on Bioinformatics
Introduction to Statistical Methods and Data Analysis (with CD-ROM)

Introduction to Statistical Methods and Data Analysis (with CD-ROM)

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Abstract

This paper proposes a novel statistical evaluation model for automated protein NMR sequential resonance assignment. It can be bound to any assignment program and provides confidences for the whole output assignment and each individual mapping. A simulation study on a set of four proteins shows that the statistical evaluation results are informative.