Société Française de Bioinformatique

Mots-Clés

RNA bioinformatics, long non-coding RNAs, artificial intelligence, multimodal integration, RNA structure, sepsis biomarkers

Description

Sepsis remains a major cause of mortality due to delayed diagnosis and high biological heterogeneity. Long non-coding RNAs (lncRNAs) are key regulators of immune responses, yet current biomarker strategies rely primarily on expression levels and overlook structural determinants of function.
This thesis project aims to develop novel AI-based tools for predicting lncRNA secondary structure and functional motifs, and to integrate these features into predictive models for sepsis diagnosis and prognosis.