Florbela Pereira is part of the Chemoinformatics lab of LAQV REQUIMTE- FCT-NOVA since 2007. Her main scientific interests include automatic learning of chemical reactivity, the use of machine learning techniques to model Spectra–Structure and Structure-Activity Relationships of natural products/marine natural products and software solutions for the processing of molecular structures and chemical data by blind users. More recently, FP is very interested in the structural elucidation of secondary metabolites from marine actinomycete bacteria and their biological activity evaluation both in real and in virtual screening en route to new drugs. Moreover, Florbela Pereira explores as well a big data approach to the ultra-fast prediction of DFT-calculated properties (e.g. the fast estimation of HOMO and LUMO orbital energies, dipole moments).