Learning functional linkage networks with a cost-sensitive approach. - Alberto Bertoni; Marco Frasca 001; Giuliano Grossi; Giorgio Valentini (WIRN, 2010)

COSNet: A Cost Sensitive Neural Network for Semi-supervised Learning in Graphs. - Alberto Bertoni; Marco Frasca 001; Giorgio Valentini (ECML/PKDD (1), 2011)

A Mathematical Model for the Validation of Gene Selection Methods. - Marco Muselli; Alberto Bertoni; Marco Frasca 001; Alessandro Beghini; Francesca Ruffino; Giorgio Valentini (IEEE ACM Trans. Comput. Biol. Bioinform., 2011)

A Neural Procedure for Gene Function Prediction. - Marco Frasca 001; Alberto Bertoni; Andrea Sion (WIRN, 2012)

A neural network based algorithm for gene expression prediction from chromatin structure. - Marco Frasca 001; Giulio Pavesi (IJCNN, 2013)

A neural network algorithm for semi-supervised node label learning from unbalanced data. - Marco Frasca 001; Alberto Bertoni; Matteo Re; Giorgio Valentini (Neural Networks, 2013)

GOssTo: a stand-alone application and a web tool for calculating semantic similarities on the Gene Ontology. - Horacio Caniza; Alfonso E. Romero; Samuel Heron; Haixuan Yang; Alessandra Devoto; Marco Frasca 001; Marco Mesiti; Giorgio Valentini; Alberto Paccanaro (Bioinform., 2014)

A Hierarchical Ensemble Method for DAG-Structured Taxonomies. - Peter N. Robinson; Marco Frasca 001; Sebastian Köhler 001; Marco Notaro; Matteo Re; Giorgio Valentini (MCS, 2015)

Automated gene function prediction through gene multifunctionality in biological networks. - Marco Frasca 001 (Neurocomputing, 2015)

UNIPred: Unbalance-Aware Network Integration and Prediction of Protein Functions. - Marco Frasca 001; Alberto Bertoni; Giorgio Valentini (J. Comput. Biol., 2015)

Multi-species protein function prediction: towards web-based visual analytics. - Paolo Perlasca; Giorgio Valentini; Marco Frasca 001; Marco Mesiti (iiWAS, 2016)

Gene-Disease Prioritization Through Cost-Sensitive Graph-Based Methodologies. - Marco Frasca 001; Simone Bassis (IWBBIO, 2016)

RANKS: a flexible tool for node label ranking and classification in biological networks. - Giorgio Valentini; Giuliano Armano; Marco Frasca 001; Jianyi Lin; Marco Mesiti; Matteo Re (Bioinform., 2016)

Learning node labels with multi-category Hopfield networks. - Marco Frasca 001; Simone Bassis; Giorgio Valentini (Neural Comput. Appl., 2016)

Selection of Negative Examples for Node Label Prediction Through Fuzzy Clustering Techniques. - Marco Frasca 001; Dario Malchiodi (Advances in Neural Networks, 2016)

Disease-Genes Must Guide Data Source Integration in the Gene Prioritization Process. - Marco Frasca 001; Jean-Fred Fontaine; Giorgio Valentini; Marco Mesiti; Marco Notaro; Dario Malchiodi; Miguel A. Andrade-Navarro (CIBB, 2017)

Ensembling Descendant Term Classifiers to Improve Gene - Abnormal Phenotype Predictions. - Marco Notaro; Max Schubach; Marco Frasca 001; Marco Mesiti; Peter N. Robinson; Giorgio Valentini (CIBB, 2017)

Analysis of Informative Features for Negative Selection in Protein Function Prediction. - Marco Frasca 001; Fabio Lipreri; Dario Malchiodi (IWBBIO (2), 2017)

Gene2DisCo: Gene to disease using disease commonalities. - Marco Frasca 001 (Artif. Intell. Medicine, 2017)

COSNet: An R package for label prediction in unbalanced biological networks. - Marco Frasca 001; Giorgio Valentini (Neurocomputing, 2017)

Committee-Based Active Learning to Select Negative Examples for Predicting Protein Functions. - Marco Frasca 001; Maryam Sepehri; Alessandro Petrini; Giuliano Grossi; Giorgio Valentini (CIBB, 2018)

A Graphical Tool for the Exploration and Visual Analysis of Biomolecular Networks. - Cheick Tidiane Ba; Elena Casiraghi; Marco Frasca 001; Jessica Gliozzo; Giuliano Grossi; Marco Mesiti; Marco Notaro; Paolo Perlasca; Alessandro Petrini; Matteo Re; Giorgio Valentini (CIBB, 2018)

Evaluating the impact of topological protein features on the negative examples selection. - Paolo Boldi; Marco Frasca 001; Dario Malchiodi (BMC Bioinform., 2018)

Correction to: Evaluating the impact of topological protein features on the negative examples selection. - Paolo Boldi; Marco Frasca 001; Dario Malchiodi (BMC Bioinform., 2018)

A novel computational method for automatic segmentation, quantification and comparative analysis of immunohistochemically labeled tissue sections. - Elena Casiraghi; Veronica Huber; Marco Frasca 001; Mara Cossa; Matteo Tozzi; Licia Rivoltini; Biagio Eugenio Leone; Antonello Villa; Barbara Vergani (BMC Bioinform., 2018)

A GPU-based algorithm for fast node label learning in large and unbalanced biomolecular networks. - Marco Frasca 001; Giuliano Grossi; Jessica Gliozzo; Marco Mesiti; Marco Notaro; Paolo Perlasca; Alessandro Petrini; Giorgio Valentini (BMC Bioinform., 2018)

Combining Cost-Sensitive Classification with Negative Selection for Protein Function Prediction. - Marco Frasca 001; Nicolò Cesa-Bianchi (CoRR, 2018)

Analysis of Novel Annotations in the Gene Ontology for Boosting the Selection of Negative Examples. - Maryam Sepehri; Marco Frasca 001 (ICBET, 2019)

Multitask Hopfield Networks. - Marco Frasca 001; Giuliano Grossi; Giorgio Valentini (ECML/PKDD (2), 2019)

UNIPred-Web: a web tool for the integration and visualization of biomolecular networks for protein function prediction. - Paolo Perlasca; Marco Frasca 001; Cheick Tidiane Ba; Marco Notaro; Alessandro Petrini; Elena Casiraghi; Giuliano Grossi; Jessica Gliozzo; Giorgio Valentini; Marco Mesiti (BMC Bioinform., 2019)

Multitask Protein Function Prediction through Task Dissimilarity. - Marco Frasca 001; Nicolò Cesa-Bianchi (IEEE ACM Trans. Comput. Biol. Bioinform., 2019)

Compression strategies and space-conscious representations for deep neural networks. - Giosuè Cataldo Marinò; Gregorio Ghidoli; Marco Frasca 001; Dario Malchiodi (ICPR, 2020)

Explainable Machine Learning for Early Assessment of COVID-19 Risk Prediction in Emergency Departments. - Elena Casiraghi; Dario Malchiodi; Gabriella Trucco; Marco Frasca 001; Luca Cappelletti; Tommaso Fontana; Alessandro Andrea Esposito; Emanuele Avola; Alessandro Jachetti; Justin T. Reese; Alessandro Rizzi; Peter N. Robinson; et al. (IEEE Access, 2020)

Protein function prediction as a graph-transduction game. - Sebastiano Vascon; Marco Frasca 001; Rocco Tripodi; Giorgio Valentini; Marcello Pelillo (Pattern Recognit. Lett., 2020)

Reproducing the Sparse Huffman Address Map Compression for Deep Neural Networks. - Giosuè Cataldo Marinò; Gregorio Ghidoli; Marco Frasca 001; Dario Malchiodi (RRPR, 2021)

HEMDAG: a family of modular and scalable hierarchical ensemble methods to improve Gene Ontology term prediction. - Marco Notaro; Marco Frasca 001; Alessandro Petrini; Jessica Gliozzo; Elena Casiraghi; Peter N. Robinson; Giorgio Valentini (Bioinform., 2021)

Compact representations of convolutional neural networks via weight pruning and quantization. - Giosuè Cataldo Marinò; Alessandro Petrini; Dario Malchiodi; Marco Frasca 001 (CoRR, 2021)

On the Choice of General Purpose Classifiers in Learned Bloom Filters: An Initial Analysis Within Basic Filters. - Giacomo Fumagalli; Davide Raimondi; Raffaele Giancarlo; Dario Malchiodi; Marco Frasca 001 (ICPRAM, 2022)

Integration and Visual Analysis of Biomolecular Networks Through UNIPred-Web. - Paolo Perlasca; Marco Frasca 001; Cheick Tidiane Ba; Jessica Gliozzo; Marco Notaro; Mario Pennacchioni; Giorgio Valentini; Marco Mesiti (ICWE Workshops, 2022)

A Critical Analysis of Classifier Selection in Learned Bloom Filters. - Dario Malchiodi; Davide Raimondi; Giacomo Fumagalli; Raffaele Giancarlo; Marco Frasca 001 (CoRR, 2022)

A Critical Analysis of Classifier Selection in Learned Bloom Filters: The Essentials. - Dario Malchiodi; Davide Raimondi; Giacomo Fumagalli; Raffaele Giancarlo; Marco Frasca 001 (EANN, 2023)

Resource-Limited Automated Ki67 Index Estimation in Breast Cancer. - Jessica Gliozzo; Giosuè Cataldo Marinò; Arturo Bonometti; Marco Frasca 001; Dario Malchiodi (ICBRA, 2023)

On Nonlinear Learned String Indexing. - Paolo Ferragina; Marco Frasca 001; Giosuè Cataldo Marinò; Giorgio Vinciguerra (IEEE Access, 2023)

Efficient and Compact Representations of Deep Neural Networks via Entropy Coding. - Giosuè Cataldo Marinò; Flavio Furia; Dario Malchiodi; Marco Frasca 001 (IEEE Access, 2023)

Deep neural networks compression: A comparative survey and choice recommendations. - Giosuè Cataldo Marinò; Alessandro Petrini; Dario Malchiodi; Marco Frasca 001 (Neurocomputing, 2023)

The role of classifiers and data complexity in learned Bloom filters: insights and recommendations. - Dario Malchiodi; Davide Raimondi; Giacomo Fumagalli; Raffaele Giancarlo; Marco Frasca 001 (J. Big Data, 2024)