Statistical evaluation of NMR backbone resonance assignment.
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.
Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada. ghlin@cs.ualberta.ca
Guohui
G
Lin
Xiang
X
Wan
Theodore
T
Tegos
Yingshu
Y
Li
D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D030562:Databases, Protein; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D015233:Models, Statistical; D010363:Pattern Recognition, Automated; D011506:Proteins / Q000737:chemistry; D015203:Reproducibility of Results; D012984:Software
D011506:Proteins