Laboratory uses data science and AI to propose solutions in biology, medicine and pharmacology
Artificial intelligence is already a part of people’s lives. Innovations in this field used to be limited to industrial or technological activities, but now society is impacted every day by new applications and tools, some of which may even affect our perception of reality. It is in this context that Fundação Getulio Vargas’ School of Applied Mathematics (FGV EMAp) has created an artificial intelligence laboratory focused on the health care sector.
The laboratory is led by Professor Alberto Paccanaro, an international authority when it comes to machine learning applied to biology and medicine. PaccanaroLab, as the laboratory is known, is staffed by young researchers and students from several different countries, including the United Kingdom, France, Paraguay and Brazil.
The team seeks to develop new machine learning techniques based on graph theory and statistics, to solve problems in the fields of computational biology, medicine and pharmacology. These techniques may offer answers to many challenges in these areas, as they may discover patterns and regularities in large amounts of data and integrate information from different sources.
All this work is carried out in collaboration with experimental biologists and clinical scientists, who validate the models developed by the researchers. This collaborative network also provides feedback on applications, which is key to improving their predictive powers.
“Much of our research focuses on developing new mathematical methods, which are especially suited to making inferences in biological networks, based on the latest machine learning results. In particular, the methods we are developing consider both the structure of the networks that represent data and the structure of the network that represents the biological question to be answered,” says Paccanaro.
Here are some of the topics of research under way:
- Protein function prediction;
- Network medicine;
- Computational pharmacology;
- Inference of relationships between genotype, phenotype and environment;
- Inference and analysis of large-scale protein-protein interaction networks;
- Analysis of biological processes from co-expression networks;
- 3D genome analysis.
About FGV EMAp
The School of Applied Mathematics was founded in 2011 in order to develop contemporary mathematics adapted to the challenges of the information and knowledge age. The school offers undergraduate programs in Applied Mathematics and Data Science and Artificial Intelligence, as well as graduate courses, stimulating research and development projects, as well as internal and external institutional partnerships.
Thus, the school’s mission is to acquire and transfer scientific and technological knowledge based on mathematics, particularly in related areas of the human and social sciences.
The school aims to become a leader in Latin America in the fields of applied mathematics and data science, focusing on six research areas:
- Data science;
- Control and optimization;
- Finance and risk;
- Stochastic models.
For more information about FGV EMAp, visit its website.