Current advances in genomics, proteomics and systems biology require the combination of techniques from Algorithmics, Artificial Intelligence, Mathematics and Statistics to deal with the theoretical and practical issues of extracting knowledge from biological data. The research in our laboratory is focused on the development of machine learning models and methods to extract motifs, functional sites or clustering/classification rules from biological data. The applications are currently concentrated on

• Biological Networks Identification

• Immunoinformatics

• Protein Function Prediction

Our interests also include algorithmic aspects of support vector machines, kernel methods and optimization methods.

More to come...