Chemoinformatics and bioinformatics

Development of mathematical relationships linking chemical structure and pharmacological activity in a quantitative manner for a series of compounds. Standard statistical tools as well as advanced machine learning methodologies (neural networks, kernel methods, evolutionary algorithms) have been employed. Emphasis is given in the development of Quantitative Structure Activity Relationships for drug design. We have also introduced a metaheuristic method for the reconstruction of the DNA string from its l-mer content in the presence of large amounts of positive and negative errors, based on the formulation of an Asymmetric Traveling Salesman problem.