Computational Proteomics Training European Innovative Network

PROTrEIN is a Training Network composed of 12 beneficiaries, and 8 partner organizations, from the academic and non-academic sectors with the mission to train a new generation of specialized bioinformaticians and improve their future employability while tackling the main challenges in computational proteomics.

Mass spectrometry (MS) is one of the most powerful technologies for the study of the cellular proteome, and it is present in many translational research projects for the diagnosis and prognosis of multiple diseases, and for elucidating the mechanisms of action of drugs of medical interest.

While several proteomics workflows are well established, the field is fast evolving with new acquisition methods and high-content data structures that expand the applications of the technology and make it one of the principal platforms in the multi-omics universe.

Many of these developments require the assistance of artificial intelligence for the acquisition of next generation proteomics datasets, as well as the development of new processing algorithms to reveal hidden proteoforms, interactions, and protein modifications.

Moreover, the usage of the new experimental possibilities requires the development of interactive and highly-visual tools for the integration and presentation of proteomics data with other omics datasets.

Although addressing these different needs is crucial to deliver major contributions in our understanding of biological processes, the shortage of sufficiently trained bioinformaticians represents a major limitation.

Therefore, PROTrEIN puts together an ambitious scientific and training programme to tackle both the challenges in proteomics research and the training of highly valuated professionals by mastering them on: a) the MS raw data structure and information content, b) MS acquisition methods, c) algorithms, gamification, and machine learning tools, d) data integration and visualization, e) science communication, f) data management, and g) RRI.