Massive non-natural proteins structure prediction using grid technologies. - Giovanni Minervini; Giuseppe Evangelista; Laura Villanova; Debora Slanzi; Davide De Lucrezia; Irene Poli; Pier Luigi Luisi; Fabio Polticelli (BMC Bioinform., 2009)

On using Bayesian networks for complexity reduction in decision trees. - Adriana Brogini; Debora Slanzi (Stat. Methods Appl., 2010)

Qualitative Particle Swarm Optimization (Q-PSO) for Energy-Efficient Building Designs. - Debora Slanzi; Matteo Borrotti; Davide De March; Daniele Orlando; Silvio Giove; Irene Poli (WIVACE, 2014)

Designing Lead Optimisation of MMP-12 Inhibitors. - Matteo Borrotti; Davide De March; Debora Slanzi; Irene Poli (Comput. Math. Methods Medicine, 2014)

A Predictive Approach Based on Neural Network Models for Building Automation Systems. - Davide De March; Matteo Borrotti; Luca Sartore; Debora Slanzi; Lorenzo Podestà; Irene Poli (Advances in Neural Networks, 2015)

Model-Based Lead Molecule Design. - Alessandro Giovannelli; Debora Slanzi; Marina Khoroshiltseva; Irene Poli (WIVACE, 2016)

Reducing Dimensionality in Molecular Systems: A Bayesian Non-parametric Approach. - Valentina Mameli; Nicola Lunardon; Marina Khoroshiltseva; Debora Slanzi; Irene Poli (WIVACE, 2016)

Using Twitter Data to Monitor Political Campaigns and Predict Election Results. - Shira Fano; Debora Slanzi (PAAMS (Special Sessions), 2017)

Modeling Urbanization Perception: Emerging Topics on Hangzhou Future Sci-Tech City Development. - Debora Slanzi; Valentina Anzoise; Irene Poli (WIVACE, 2017)

Multi-objective Optimization in High-Dimensional Molecular Systems. - Debora Slanzi; Valentina Mameli; Marina Khoroshiltseva; Irene Poli (WIVACE, 2017)

Evolution of Workers' Behaviour in Dual Labor Markets. - Shira Fano; Debora Slanzi (WIVACE, 2018)

A Neural Network Model for Lead Optimization of MMP12 Inhibitors. - Tewodros Mulugeta Dagnew; Claudio Silvestri; Debora Slanzi; Irene Poli (ICPR Workshops (4), 2020)

Exploiting the Potential of Bayesian Networks in Deriving New Insight into Diabetic Kidney Disease (DKD). - Debora Slanzi; Claudio Silvestri; Irene Poli; Gert Mayer (WIVACE, 2023)

A comparative study on high-dimensional bayesian regression with binary predictors. - Debora Slanzi; Valentina Mameli; Philip J. Brown (Commun. Stat. Simul. Comput., 2023)

Learning Optimal Dynamic Treatment Regime from Observational Clinical Data through Reinforcement Learning. - Seyum Abebe; Irene Poli; Roger D. Jones; Debora Slanzi (Mach. Learn. Knowl. Extr., 2024)