RIBRA – an error-tolerant algorithm for the NMR backbone assignment problem. (English) Zbl 1119.92338

Miyano, Satoru (ed.) et al., Research in computational molecular biology. 9th annual international conference, RECOMB 2005, Cambridge, MA, USA, May 14–18, 2005. Proceedings. Berlin: Springer (ISBN 3-540-25866-3/pbk). Lecture Notes in Computer Science 3500. Lecture Notes in Bioinformatics, 103-117 (2005).
Summary: We develop an iterative relaxation algorithm, called RIBRA, for NMR protein backbone assignment. RIBRA applies nearest neighbor and weighted maximum independent set algorithms to solve the problem. To deal with noisy NMR spectral data, RIBRA is executed in an iterative fashion based on the quality of spectral peaks. We first produce spin system pairs using the spectral data without missing peaks, then the data group with one missing peak, and finally, the data group with two missing peaks. We test RIBRA on two real NMR datasets: hb-SBD and hbLBD, and perfect BMRB data (with 902 proteins) and four synthetic BMRB data which simulate four kinds of errors. The accuracy of RIBRA on hbSBD and hbLBD are 91.4% and 83.6%, respectively. The average accuracy of RIBRA on perfect BMRB datasets is 98.28%, and 98.28%, 95.61%, 98.16% and 96.28% on four kinds of synthetic datasets, respectively.
For the entire collection see [Zbl 1073.92504].


92C40 Biochemistry, molecular biology
92-08 Computational methods for problems pertaining to biology
92C55 Biomedical imaging and signal processing


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