Background: The development and improvement of reliable computational methods designed to evaluate the quality of protein models is relevant in the context of protein structure re...
Paolo Mereghetti, Maria Luisa Ganadu, Elena Papale...
Background: Current scoring functions are not very successful in protein-ligand binding affinity prediction albeit their popularity in structure-based drug designs. Here, we propo...
In many complex machine learning applications there is a need to learn multiple interdependent output variables, where knowledge of these interdependencies can be exploited to impr...
Research in floorplanning and block-packing has generated a variety of data structures to represent spatial configurations of circuit modules. Much of this work focuses on the g...
To explore the Perturb and Combine idea for estimating probability densities, we study mixtures of tree structured Markov networks derived by bagging combined with the Chow and Liu...
Sourour Ammar, Philippe Leray, Boris Defourny, Lou...