Application of causal structure learning algorithms to obesity and other risk factors for cardiovascular diseases

• Grant number: 23/08647-5
• Support Opportunities: Scholarships abroad - Research Internship - Scientific Initiation
• Start date: September 10, 2023
• End date: October 09, 2023
• Field of knowledge: Physical Sciences and Mathematics - Probability and Statistics - Statistics
• Principal Investigator: Andressa Cerqueira
• Grantee: Milena Crnkovic Luzia
• Supervisor: Adele Helena Ribeiro
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
• Institution abroad: Philipps-Universität Marburg, Germany
• Associated to the scholarship: 22/03420-0 - Learning causal graphical models for obesity and other nutrition-related disorders, BP.IC

Abstract

The study of cause-effect relationships from observational data has received a lot of attention in the empirical sciences, but it is still underdeveloped in the nutritional area. The construction of such a causal model would promote a better understanding about the human biological system. In this way, the goal of this project is the construction of graphical causal models for nutritional disorders using genotypic and phenotypic information of the individuals. To achieve this challenging aim, the first step is the selection of the genetic variants associated with the phenotypic variables considered important in the study of obesity. After that, the construction of graphical causal models will be done using a causal structure learning algorithms such as the Fast Causal Inference (FCI).