Dem IPB wird erneut ein beispielhaftes Handeln im Sinne einer chancengleichheitsorientierten Personal- und Organisationspolitik bescheinigt. Das Institut erhält zum 6. Mal in Folge das TOTAL E-QUALITY…
Die Plant Science Student Conference (PSSC) wird seit 20 Jahren im jährlichen Wechsel von Studierenden der beiden Leibniz-Institute IPK und IPB organisiert. Im Interview erläutern Christina Wäsch…
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.
Publikation
Gaida, A.; Neumann, S.;MetHouse: Raw and Preprocessed Mass Spectrometry DataJ. Integr. Bioinformatics4107-114(2007)DOI: 10.1515/jib-2007-56
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/