UM  > Faculty of Science and Technology  > DEPARTMENT OF MATHEMATICS
Status已發表Published
WaVPeak: picking NMR peaks through wavelet transform and volume-based filtering
Liu, Z.; Abbas, A.; Jing, B.Y.; Gao, X.
2012-03-01
Source PublicationBioinformatics
ISSN1367-4803
Pages914-920
AbstractMotivation: Nuclear magnetic resonance (NMR) has been widely used as a powerful tool to determine the 3D structures of proteins in vivo. However, the post-spectra processing stage of NMR structure determination usually involves a tremendous amount of time and expert knowledge, which includes peak picking, chemical shift assignment and structure calculation steps. Detecting accurate peaks from the NMR spectra is a prerequisite for all following steps, and thus remains a key problem in automatic NMR structure determination. Results: We introduce WaVPeak, a fully automatic peak detection method. WaVPeak first smoothes the given NMR spectrum by wavelets. The peaks are then identified as the local maxima. The false positive peaks are filtered out efficiently by considering the volume of the peaks. WaVPeak has two major advantages over the state-of-the-art peak-picking methods. First, through wavelet-based smoothing, WaVPeak does not eliminate any data point in the spectra. Therefore, WaVPeak is able to detect weak peaks that are embedded in the noise level. NMR spectroscopists need the most help isolating these weak peaks. Second, WaVPeak estimates the volume of the peaks to filter the false positives. This is more reliable than intensity-based filters that are widely used in existing methods. We evaluate the performance of WaVPeak on the benchmark set proposed by PICKY (Alipanahi et al., 2009), one of the most accurate methods in the literature. The dataset comprises 32 2D and 3D spectra from eight different proteins. Experimental results demonstrate that WaVPeak achieves an average of 96%, 91%, 88%, 76% and 85% recall on 15N-HSQC, HNCO, HNCA, HNCACB and CBCA(CO)NH, respectively. When the same number of peaks are considered, WaVPeak significantly outperforms PICKY.
KeywordNMR data Peak picking Volume-based filtering
URLView the original
Language英語English
The Source to ArticlePB_Publication
PUB ID25999
Document TypeJournal article
CollectionDEPARTMENT OF MATHEMATICS
Corresponding AuthorJing, B.Y.; Gao, X.
Recommended Citation
GB/T 7714
Liu, Z.,Abbas, A.,Jing, B.Y.,et al. WaVPeak: picking NMR peaks through wavelet transform and volume-based filtering[J]. Bioinformatics, 2012, 914-920.
APA Liu, Z.., Abbas, A.., Jing, B.Y.., & Gao, X. (2012). WaVPeak: picking NMR peaks through wavelet transform and volume-based filtering. Bioinformatics, 914-920.
MLA Liu, Z.,et al."WaVPeak: picking NMR peaks through wavelet transform and volume-based filtering".Bioinformatics (2012):914-920.
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