KAUST DepartmentComputational Bioscience Research Center (CBRC)
Computer Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Structural and Functional Bioinformatics Group
Permanent link to this recordhttp://hdl.handle.net/10754/552357
MetadataShow full item record
AbstractProtein structure determination is a very important topic in structural genomics, which helps people to understand varieties of biological functions such as protein-protein interactions, protein–DNA interactions and so on. Nowadays, nuclear magnetic resonance (NMR) has often been used to determine the three-dimensional structures of protein in vivo. This study aims to automate the peak picking step, the most important and tricky step in NMR structure determination. We propose to model the NMR spectrum by a mixture of bivariate Gaussian densities and use the stochastic approximation Monte Carlo algorithm as the computational tool to solve the problem. Under the Bayesian framework, the peak picking problem is casted as a variable selection problem. The proposed method can automatically distinguish true peaks from false ones without preprocessing the data. To the best of our knowledge, this is the first effort in the literature that tackles the peak picking problem for NMR spectrum data using Bayesian method.
CitationBayesian Peak Picking for NMR Spectra 2014, 12 (1):39 Genomics, Proteomics & Bioinformatics
PubMed Central IDPMC4411369
- Bayesian reconstruction of projection reconstruction NMR (PR-NMR).
- Authors: Yoon JW
- Issue date: 2014 Nov
- BATMAN--an R package for the automated quantification of metabolites from nuclear magnetic resonance spectra using a Bayesian model.
- Authors: Hao J, Astle W, De Iorio M, Ebbels TM
- Issue date: 2012 Aug 1
- Protein NMR structure determination with automated NOE-identification in the NOESY spectra using the new software ATNOS.
- Authors: Herrmann T, Güntert P, Wüthrich K
- Issue date: 2002 Nov
- Automatic peak selection by a Benjamini-Hochberg-based algorithm.
- Authors: Abbas A, Kong XB, Liu Z, Jing BY, Gao X
- Issue date: 2013
- APART: automated preprocessing for NMR assignments with reduced tedium.
- Authors: Pawley NH, Gans JD, Michalczyk R
- Issue date: 2005 Mar 1