INEXTVIR – Network for Next Generation Training and Sequencing of Virome

Project duration: 01.02.2019 – 31.01.2023
Official website:
Project type: Horizon 2020
Project partners: National Institute of Biology (SI) – coordinator, FERA, CBGP, INRA, Liege Uni, Abiopep, DNA Vision, CGFB, Newcastle Uni, Uni of Murcia, IJS Postgraduate School


INEXTVIR is a Marie Sklodowska-Curie Innovative Training Network (MSCA-ITN). INEXTVIR is implemented by a European Consortium of universities, research institutions, and companies in Belgium, France, Spain, Slovenia, and the UK. It offers fully funded 15 PhD positions in a transdisciplinary network of research and training aimed at accelerating the start of the applicants’ scientific careers.
Plant viruses cause 50% of the emerging plant diseases globally and pose an important threat to many agricultural crops. Losses are estimated at €15 to 45 billion per year through lower yields and reduced product quality. That is why Inextvir seeks to generate a better understanding of viral communities and their role in agricultural ecosystems by using the latest advances in high throughput sequencing (HTS) technologies coupled with modern big data analytical approaches and socioeconomic analysis. The project provides a timely opportunity to change our approach to plant health and improve our ability to overcome global agricultural, food security, and environmental challenges.

BioSistemika’s role:

BioSistemika is hosting one of the 15 PhD early-stage researchers (PhD students). Along with a mentor from the Faculty of Computer and Information Sciences (University of Ljubljana), we are applying machine learning algorithms and building a decision support system that will help bioinformaticians and researchers find the most suitable bioinformatics tool for the analysis of their high throughput sequencing (HTS) datasets based on their specific needs and researcher questions. We will continue the work towards building a recommendation system and integrating it with external software platforms such as electronic laboratory notebooks.


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This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No813542.