General Data
Member of UL
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Veterinary Faculty
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Status
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partner |
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Name of the leading partner
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Project code/ Project No.
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Project Title
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Machine Learning-Driven Risk Ranking Framework for Virulence & Resistance Traits: An E. coli Case Study |
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Financier
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Evropska agencija za varnost hrane (EFSA) |
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Project period
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29.04.2026–28.10.2027 |
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Yearly sum of FTE
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11.000,00 EUR
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Leader
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Bojan Papić |
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Scientific field
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Microbiology |
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Partners
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University of Ljubljana, Veterinary Faculty, Slovenia
Technological University Dublin (TU Dublin), Ireland
Polytechnic University of Cartagena (UPCT), Spain
Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna (IZSLER), Italy |
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Project Phases
Task 1. Literature review
Task 2. Development of semi-quantitative risk scoring system
Task 3. Development of a curated WGS dataset
Task 4. Validation of the predictive model
Task 5. User-friendly software application for risk ranking
Task 6. Assessing suitability of framework to enhance stakeholder collaboration
Project Description
"Machine Learning-Driven Risk Ranking Framework for Virulence & Resistance Traits: An E. coli Case Study" is an activity funded by the European Food Safety Authority (EFSA) through a Tailor-Made Activity (TMA) programme. Commenced in April 2026, the project will run for 18 months and brings together four partner institutions: Technological University Dublin as the lead coordinator and host institution of the principal investigator Dr Elena Alexa, Polytechnic University of Cartagena, University of Ljubljana and Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna. Using Escherichia coli as a case study, the project aims to develop an innovative methodology that integrates whole-genome sequencing (WGS) data, machine learning (ML) models, and multi-criteria decision analysis (MCDA) to enhance microbial risk assessment.
Structure of the Project Group
- Bojan Papić
- Minja Stevanović
