Stefano Lanzeni

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Automatically assessing the value of bioavailability from the chemical structure of a molecule is a very important issue in biomedicine and pharmacology. In this paper, we present an empirical study of some well known Machine Learning techniques, including various versions of Genetic Programming, which have been trained to this aim using a dataset of(More)
The success of a drug treatment is strongly correlated with the ability of a molecule to reach its target in the patient’s organism without inducing toxic effects. Moreover the reduction of cost and time associated with drug discovery and development is becoming a crucial requirement for pharmaceutical industry. Therefore computational methods allowing(More)
Background We propose a Petri Net-based method for metabolic networks profiling with respect to specific environmental conditions, based on the concept of metabolic reactions hierarchical ordering considered in [1]. One or more metabolites are seeded in the network, then the newly synthesized compounds are iteratively integrated in the system until no new(More)
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