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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
Effective date (Start): September 10, 2023
Effective date (End): 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
Research place: 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).

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