We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
When using machine learning for in silico modeling, the goal is normally to obtain highly accurate predictive models. Often, however, models should also bring insights into intere...
In Smart Spaces (SSs), the capability of learning from experience is fundamental for autonomous adaptation to environmental changes and for proactive interaction with users. New re...
Alessio Dore, Andrea F. Cattoni, Carlo S. Regazzon...
Background: The prediction of protein-protein binding site can provide structural annotation to the protein interaction data from proteomics studies. This is very important for th...
Background: Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods ha...