Computing Empirical P-Values for Estimating Gene-Gene Interactions in Genome-Wide Association Studies: A Parallel Computing Approach. - Valentina Giansanti; Daniele D'Agostino; Carlo Maj; Stefano Beretta 001; Ivan Merelli (PDP, 2018)

Improving eQTL Analysis Using a Machine Learning Approach for Data Integration: A Logistic Model Tree Solution. - Stefano Beretta 001; Mauro Castelli; Ivo Gonçalves; Ivan Kel; Valentina Giansanti; Ivan Merelli (J. Comput. Biol., 2018)

Comparing Deep and Machine Learning Approaches in Bioinformatics: A miRNA-Target Prediction Case Study. - Valentina Giansanti; Mauro Castelli; Stefano Beretta 001; Ivan Merelli (ICCS (3), 2019)

Parallel Computing in Deep Learning: Bioinformatics Case Studiesa. - Valentina Giansanti; Stefano Beretta 001; Daniele Cesini; Daniele D'Agostino; Ivan Merelli (PDP, 2019)

SoC-based computing infrastructures for scientific applications and commercial services: Performance and economic evaluations. - Daniele D'Agostino; Alfonso Quarati; Andrea Clematis; Lucia Morganti; Elena Corni; Valentina Giansanti; Daniele Cesini; Ivan Merelli (Future Gener. Comput. Syst., 2019)

Nested Stochastic Block Models applied to the analysis of single cell data. - Leonardo Morelli; Valentina Giansanti; Davide Cittaro (BMC Bioinform., 2021)