Computational tools for investigating causality in Cancer data repositories

• Grant number: 23/00678-9
• Support Opportunities: Regular Research Grants
• Start date: May 01, 2023
• End date: April 30, 2024
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Mobility Program: SPRINT - Projetos de pesquisa - Mobilidade
• Principal Investigator: Adenilso da Silva Simão
• Grantee: Adenilso da Silva Simão
• Principal researcher abroad: Mohammad Reza Mousavi
• Institution abroad: King's College London , England
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• City of the host institution: São Carlos
• Associated research grant: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry, AP.CEPID

Abstract

Causality models represent the relation between elements relevant to a given phenomenon. Given a set of conditions that can vary either autonomously or by explicit manipulation, causality models can indicate how and when changes in given elements lead to results in other elements. The area is at the intersection of philosophy and mathematics. More recently, computational approaches have been used to address the problem of dealing with many parameters in the models. (AU)