An EOSC-Life internal call for academia-industry collaborations sharing data, tools and workflows in the

European Open Science Cloud


The second Digital Life Science Call for academia-industry collaborations was aimed at existing EOSC-Life partners who wanted to implement a collaborative project together with SME or industry partners. Out of 10 submitted eligible proposals, 2 projects were selected that – if successful – will demonstrate how companies can leverage cloud-based bioinformatics pipelines for sustainability and how further development of analysis software by commercial companies can add value to open research data bases. 

All submitted applications were first reviewed by the technical experts within the EOSC-Life consortium with regards to their technical impact, feasibility and project maturity, before continuing to scientific evaluation. A selection panel of both internal and external experts chose the winning projects from a shortlist of 8 proposals based on transparent selection criteria.

The following projects were selected for funding:

Funded Projects

Accessible and scalable detection and identification of foodborne pathogens

Team lead: Bérénice Batut, University of Freiburg

Industry partner: Biolytix AG

Project team: Ralf Seyfarth, Anna Henger, Engy Nasr


Brief project summary:

Metagenomic sequencing has been proposed as a time- and resource effective method for detecting, identifying and characterizing (e.g., resistance or virulence) foodborne pathogens in complex samples in a single sequencing run without prior isolation of the pathogen. The project aims to modernize and open up the current detection pipelines using long-read ONT sequencing technologies, developed by Biolytix AG. Based on Galaxy, modern paradigms of open data science will be applied to ensure the pipelines are FAIR, accessible, scalable but also portable, cloud deployable, maintainable and shareable.

QSM4SENIOR: Ultra-high Field MRI Quantitative Susceptibility Mapping reconstruction of the healthy Brain-aging cohort

Team lead: Alexandre Vignaud, CNRS

Industry partner: Ventio

Project team: Miguel Guevara, Jean-Francois Mangin, Yann Cointepas, Ludovic de Rochefort, Michael Bottländer


Brief project summary:

This project will re-use ultra high-field MRI imaging data that has been acquired during a longitudinal study in healthy, aging subjects (the SENIOR study) which has not yet been fully exploited. In particular, the investigation of iron load as a quantitative imaging biomarker for aging and brain disease requires complex image reconstruction techniques. QSM4SENIOR will employ quantitative susceptibility mapping (QSM) using the MEDI software combined to the cloud computing implementation developed by the industry partner Ventio SAS, and FAIRify the imaging data, generating the first quantitative imaging database of highly-resolved 7T MRI data, enhancing the value of the SENIOR database by the addition of a novel imaging biomarker, and targeting interoperability to EOSC-Life cloud research infrastructures.

For more details about the research, read the press release here

Industry Internal Call - Information for Grantees

Looking for the Internal Call for Sensitive Data? Find it here.