Master Degree (Artificial Intelligence curriculum)
CHL course, Academic Year: 2021/2022
Date: May 2022
Integrate metabolomics and proteomics data from PANS. Perform classification of patients based on the two types of data, and extract biomarkers that maximize classification performance.
PANS is a pediatric disorder that involves symptoms such as obsessive-compulsive disorder (OCD), tics, anxiety attacks, depression, and sleep problems. The causes of the onset of this disease are probably related to an immune response to a bacterial or viral infection; therefore, current treatments include antibiotics, anti-inflammatories, and antidepressants. Our project is based on two data sets: metabolic data and proteomic data. Most of the patients they refer to are in common. Then, as we described in the Method section, we merged these two datasets into a new one to try the a-priori methodology. Hence, our aim is to integrate omics data to maximize the classification performance extracting the biomarkers. This report is organized as followi