A typical characteristic of modern proteomics and metabolomics studies is the large amount of data that is produced during experimentation. This has led to a situation where the interpretation of data and the formulation of hypotheses lag the pace, at which the information is produced. Although, bioinformatics and statistical data analysis often forms the last step in a study,  we strongly encourage our collaborators to consult us prior to experimentation. Our expertise in proteomics and metabolomics can help scientists to translate their particular research questions into falsifiable research hypotheses that are properly designed and compatible with mass spectrometry experimentation. Once the research hypothesis and the experimental conduct is clear, a post-acquisition data analysis can be performed in fast and transparent  manner.

In order to plough through the data flood produced by mass spectrometry and convert it into meaningful information, we have several computational tools at our dispose:

Commercial software tools:

Identification and quantification of shotgun proteomics data is done by the Proteome Discoverer data manager of Thermo Scientific and includes Sequest for database searching. Moreover, a high-performance Mascot server is available for extensive and enzyme-free database searching. Denovo interpretation of tandem MS data and label-free quantification is conducted with the Peaks software suite from Bioinformatics Solution Inc. The Sieve platform from Thermo Scientific is used for label-free alignment of proteomics and metabolomics LC-MS heatmaps. . Protein Deconvolution and ProSight of Thermo Scientific are used for the interpretation of top-down data. Other software programs include MassLynx (Waters), ProteinPilot (AB Sciex) and Xcalibur (Thermo) for data inspection and data acquisition.

Third Party tools:

The Center for Proteomics also relies on academic and open-source software tools that are developed by third parties. For example, MaxQuant (Max Planck Institue) for the analysis of shotgun experiments, Skyline (University of Washington) for the analysis of our targeted measurement, RawMeat (Vast Scientific) for quick quality assessment and ProteoWizard (Vanderbilt University) for our data conversion tasks. Other third party software platforms can be installed and evaluated on request.

In-house developed tools:

A team of bioinformaticians at the Center for Proteomics is working on dedicated tools and workflows to facilitate the data analysis of routine proteomics and metabolomics analysis. Often these algorithms result into patented applications as indicated in the Figure.

Customized tools:

Specialized analysis task, dedicatede algorithms and data management workflows can be conceived on request by our staff.