Title: Machine learning approaches in preclinical phenotypes Tutor: Valter Tucci Background: Preclinical models are important means in modern medicine. The aim of this project is to conduct a multi-step high-level analysis of preclinical phenotypes to advance the translational research in rare genetic diseases. The project includes a comprehensive and descriptive analysis of all phenotypes; the use of artificial intelligence (AI)-driven computational approaches to extract biomedical features and to build predictive models based on the genotypes. Moreover, you will create 'Digital Twins' of the preclinical lines that can be analyzed independently of their physical entity. Through Digital Twins, phenotyping can be used to detect early signs of the disease and the effects of disease treatment, providing new solutions in the therapeutic approaches. Description: The successful candidate will investigate the collected phenotypic data. Based on the stud...