de.NBI Lipidomics

Lipidomics encompasses analytical approaches that aim to identify and quantify the complete set of lipids, defined as lipidome in a given cell, tissue or organism as well as their interactions with other molecules. The majority of lipidomics workflows is based on mass spectrometry and has been proven as a powerful tool in system biology in concert with other Omics disciplines. Unfortunately, bioinformatics infrastructures for this relatively young discipline are limited only to some specialists. Search engines, quantification algorithms, visualization tools and databases developed by the ‘Lipidomics Informatics for Life-Science’ (LIFS) partners will be restructured and standardized to provide broad access to these specialized bioinformatics pipelines. There are many medical challenges related to lipid metabolic alterations that will be fostered by capacity building suggested by LIFS. LIFS as member of the ‘German Network for Bioinformatics’ (de.NBI) node for ‘Bioinformatics for Proteomics’ (BioInfra.Prot) and will provide access to the described software as well as to tutorials and consulting services via a unified web-portal.

de.NBI Proteomics

Computational proteomics is a constantly growing field to support end users with powerful and reliable tools for performing several computational steps within an analytics workflow for proteomics experiments. Typically, after capturing with a mass spectrometer, the proteins have to be identified and quantified. After certain follow-up analyses, an optional targeted approach is suitable for validating the results. The de.NBI (German network for bioinformatics infrastructure) service center in Dortmund provides several software applications and platforms as services to meet these demands. In this work, we present our tools and services, which is the combination of SearchGUI and PeptideShaker. SearchGUI is a managing tool for several search engines to find peptide spectra matches for one or more complex MS2 measurements. PeptideShaker combines all matches and creates a consensus list of identified proteins providing statistical confidence measures. In a next step, we are planning to release a web service for protein identification containing both tools. This system will be designed for high scalability and distributed computing using solutions like the Docker container system among others. As an additional service, we offer a web service oriented database providing all necessary high-quality and high-resolution data for starting targeted proteomics analyses. The user can easily select proteins of interest, review the according spectra and download both protein sequences and spectral library. All systems are designed to be intuitively and user-friendly operable.