This project aims to develop new bioinformatics tools based on Machine Learning methods (supervised and unsupervised), heuristic search methods, and high-performance computing to explore high-dimensional data in problems of scientific and economic interest in the area of human and animal health. We will develop: (i) algorithms based on adaptive and multiobjective metaheuristics; (ii) multimodal metaheuristics; (iii) time series-based metaheuristics; (iv) combinatorial optimization; (v) interpretable machine learning methods; (vi) algorithms for feature extraction and selection; and (vii) combination of interpretability methods aiming at building general-purpose strategies that contribute to the analysis of large data with complex structure...Read More
The laboratory of Structural Bioinformatics and Computational Biology
conducts research in data science, machine learning, optimization/meta-heuristics,
and high-performance computing for Bioinformatics and Computational Biology.
Projects developed in the laboratory cover sectors of Agricultural Biotech;
Animal Biotech; Industrial Biotech; Medical Biotech; and Forensic Biotech.
The group is engaged in the following scientific-technical projects: