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Mass spectrometry is an important analytical technology for the identification of metabolites and small compounds by their exact mass. But dozens or hundreds of different compounds may have a similar mass or even the same molecule formula. Further elucidation requires tandem mass spectrometry, which provides the masses of compound fragments, but in silico fragmentation programs require substantial computational resources if applied to large numbers of candidate structures.We present and evaluate an approach to obtain candidates from a relational database which contains 28 million compounds from PubChem.A training phase associates tandem-MS peaks with corresponding fragment structures. For the candidate search, the peaks in a query spectrum are translated to fragment structures, and the candidates are retrieved and sorted by the number of matching fragment structures. In the cross validation the evaluation of the relative ranking positions (RRP) using different sizes of training sets confirms that a larger coverage of training data improves the average RRP from 0.65 to 0.72. Our approach allows downstream algorithms to process candidates in order of importance.
Publications
2D-Nuclear magnetic resonance (NMR) spectra are used in the (structural) analysis of small molecules. In contrast to 1D-NMR spectra, 2D-NMR spectra correlate the chemical shifts of 1H and 13C at the same time. A spectrum consists of several peaks in a two--dimensional space. The most important information of a peak is the location of its center, which captures the bonding relationships of hydrogen and carbon atoms. A spectrum contains much information about the chemical structure of a product, but in most cases the structure cannot be read off in a simple and straightforward manner. Structure elucidation involves a considerable amount (manual) efforts.Using high-field NMR spectrometers, many 2D-NMR spectra can be recorded in short time. So the common situation is that a lab or company has a repository of 2D-NMR spectra, partially annotated with the structural information. For the remaining spectra the structure in unknown. In case two research labs are collaborating, the repositories will be merged and annotations shared.We reduce that problem to the task of finding duplicates in a given set of 2D-NMR spectra. Therefore, we propose a simple but robust definition of 2D-NMR duplicates, which allows for small measurement errors. We give a quadratic algorithm for the problem, which can be implemented in SQL. Further, we analyze a more abstract class of heuristics, which are based on selecting particular peaks. Such a heuristic works as a filter step on the pairs of possible duplicates and allows false positives. We compare all methods with respect to their run time. Finally we discuss the effectiveness of the duplicate definition on real data.
Publications
We are developing a vendor-independent archive and on top of that a data warehouse for mass spectrometry metabolomics data. The archive schema resembles the communitydeveloped object model, the Java implementation of the model classes, and an editor (for both mzData XML files and the database) have been generated using the Eclipse Modeling Framework. Persistence is handled by the JDO2 -compliant framework JPOX. The main content of the Data Warehouse are the results of the signal processing and peak-picking tasks, carried out using the XCMS package from Bioconductor, putative identification and mass decomposition are added to the warehouse afterwards.We present the system architecture, current content, performance observations and describe the analysis tools on top of the warehouse.Availability: http://msbi.ipb-halle.de/