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All Publications Home

h-index: 13   Citations: 803   Erdös #: 3   ORCID   Scopus  

2023

• IEEE ACCESS'23 "On Nonlinear Learned String Indexing", Ferragina, P., Frasca, M., Marino, G.C., and Vinciguerra, G. IEEE Access 2023, 11, pages 74021-74034.
• JPM'23 "Combining Clinical and Genetic Data to Predict Response to Fingolimod Treatment in Relapsing Remitting Multiple Sclerosis Patients: A Precision Medicine Approach", Ferrè L., Clarelli F., Pignolet B., Mascia E., Frasca M., Santoro S., Sorosina M., Bucciarelli F., Moiola L., Martinelli V., Comi G., Liblau R., Filippi M., Valentini G., Esposito F. Journal of Personalized Medicine 2023, 13(1):122.
• NEUROCOMPUTING'23 "Deep neural networks compression: A comparative survey and choice recommendations", Marinò, G.C., Petrini, A., Malchiodi, D., Frasca, M. Neurocomputing 2023, 520, pages 152-170.
• ICBRA'23 "Resource-Limited Automated Ki67 Index Estimation in Breast Cancer", Gliozzo, J., Marinò, G., Bonometti, A., Frasca, M., Malchiodi, D. 10th International Conference on Bioinformatics Research and Applications (ICBRA 23) 2023, Accepted.
• EANN'23 "A Critical Analysis of Classifier Selection in Learned Bloom Filters: The Essentials.", Malchiodi, D., Raimondi, D., Fumagalli, G., Giancarlo, R., Frasca, M. Engineering Applications of Neural Networks (EANN 2023), Communications in Computer and Information Science, vol 1826. Springer, Cham.

2022

• AS'22 "Transcriptional Profiling of Hippocampus Identifies Network Alterations in Alzheimer’s Disease", Quarato, V., D’antona, S., Battista, P., ..., Frasca, M., Cava, C. Applied Sciences 2022, 12(10), 5035.
• CSBJ'22 "Identification of key miRNAs in Prostate cancer progression based on miRNA-mRNA network construction", G. Dal Santo, M. Frasca, G. Bertoli, I. Castiglioni, C. Cava. Computational and Structural Biotechnology Journal 2022, 20:864-873.
• ICPRAM'22 "On the Choice of General Purpose Classifiers in Learned Bloom Filters: An Initial Analysis Within Basic Filters", Fumagalli, G., Raimondi, D., Giancarlo, R., Malchiodi, D. and Frasca, M. InProceedings of the 11th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2022), pages 675-682.

2021

• MED'21 "Identification of Breast Cancer Subtype-Specific Biomarkers by Integrating Copy Number Alterations and Gene Expression Profiles", Cava, C., Pisati, M., Frasca, M., Castiglioni, I.. Medicina, 2021, 57(3), 261.
• OUP'21 "HEMDAG: a family of modular and scalable hierarchical ensemble methods to improve Gene Ontology term prediction", M. Notaro, M. Frasca, A. Petrini, J. Gliozzo, E. Casiraghi, P.N. Robinson and G. Valentini. Bioinformatics, 2021, 1-8. In press. doi:10.1093/bioinformatics/btab485.
• RRPR'21 "Reproducing the Sparse Huffman Address Map Compression for Deep Neural Networks", Marinò, G.C., Ghidoli, G., Frasca, M., Malchiodi, D.. International Workshop on Reproducible Research in Pattern Recognition RRPR 2021, 2021, 161-166.
• DMP'21 "Artificial Intelligence in Predicting Clinical Outcome in COVID-19 Patients from Clinical, Biochemical and a Qualitative Chest X-Ray Scoring System", Esposito, A., Casiraghi, E., Chiaraviglio, F., Scarabelli, A., Stellato, E., Plensich, G., Lastella, G., Di Meglio, L., Fusco, S., Avola, E., Jachetti, A., Giannitto, C., Malchiodi, D., Frasca, M., Beheshti, A., Robinson, P.N., Valentini, G., Forzenigo, L., Carrafiello, G.. Reports in Medical Imaging, 2021, 14, 27-39.

2020

• PONE'20 "Multi-resolution visualization and analysis of biomolecular networks through hierarchical community detection and web-based graphical tools", P. Perlasca, M. Frasca, C.T. Ba, J. Gliozzo, M. Notaro, M. Pennacchioni, G. Valentini, M. Mesiti, PLoS ONE, 15(12): e0244241. 2020.
• SCIREP'20 "Network modeling of patients' biomolecular profiles for clinical phenotype/outcome prediction", J. Gliozzo, P. Perlasca, M. Mesiti, E. Casiraghi, V. Vallacchi, E. Vergani, M. Frasca, G. Grossi, A. Petrini, M. Re, A. Paccanaro and G. Valentini. Scientific Reports, 10:3612, 2020.
• PRL'20 "Protein function prediction as a graph-transduction game", Vascon, S., Frasca, M., Tripodi, R., Valentini, G., Pelillo, M.. Pattern Recognition Letters, 2020, 134, 96-105, doi: 10.1016/j.patrec.2018.04.002.
• IEEE ICPR'20 "Compression strategies and space-conscious representations for deep neural networks", G. Marino', G. Ghidoli, M. Frasca, D. Malchiodi, 25th International Conference on Pattern Recognition (ICPR 20), 2020, 9835-9842, doi: 10.1109/ICPR48806.2021.9412209.
• IEEE Access'20 "Explainable Machine Learning for Early Assessment of COVID-19 Risk Prediction in Emergency Departments", Casiraghi, E., Malchiodi, D., Trucco, G., Frasca, M., Cappelletti, L., Fontana, T., Esposito, A.A., Avola, E., Jachetti, A., Reese, J., Rizzi, A., Robinson, P.N., Valentini, G.. IEEE Access, 2020, 8, pp. 196299-196325, doi: 10.1109/ACCESS.2020.3034032.
• GigaScience'20 "parSMURF, a high-performance computing tool for the genome-wide detection of pathogenic variants", Petrini, A., Mesiti, M., Schubach, M., Frasca, M., Danis, D., Re, M., Grossi, G., Cappelletti, L., Castrignanò, T., Robinson, P.N., Valentini, G.. GigaScience, 2020, 9:20, doi: 10.1093/GIGASCIENCE/GIAA052.
• LNCS'20 "Committee-Based Active Learning to Select Negative Examples for Predicting Protein Functions", Frasca, M., Sepehri, M., Petrini, A., Grossi, G., Valentini, G.. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2020, 11925 LNBI, 80-87, doi: 10.1007/978-3-030-34585-3_7.
• LNCS'20 "A Graphical Tool for the Exploration and Visual Analysis of Biomolecular Networks", Ba, C.T., Casiraghi, E., Frasca, M., Gliozzo, J., Grossi, G., Mesiti, M., Notaro, M., Perlasca, P., Petrini, A., Re, M., Valentini, G.. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2020, 11925 LNBI, pp. 88-98, doi: 10.1007/978-3-030-34585-3_8.

2019

• ECML'19 "Multitask Hopfield Networks", M. Frasca, G. Grossi and G. Valentini, in Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2019, Wurzburg16 September 2019.
• CAFA'19 "The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens", Zhou, N., Jiang, Y., Bergquist, T.R., ...Radivojac, P., Friedberg, I., Genome Biology, 2019, 20:1, 244, doi:10.1186/s13059-019-1835-8.
• BMC'19 "UNIPred-Web: A web tool for the integration and visualization of biomolecular networks for protein function prediction", Perlasca, P., Frasca, M., Ba, C.T., ...Valentini, G., Mesiti, M., BMC Bioinformatics, 2019, 20(1), 422, doi:10.1186/s12859-019-2959-2.
• ACM ICBET'19 "Analysis of novel annotations in the gene ontology for boosting the selection of negative examples", Sepehri, M., Frasca, M., in Proceedings of the 9th International Conference on Biomedical Engineering and Technology (ICBET'19), Tokyo, Japan, March 28-30 2019, 294-301, doi:10.1145/3326172.3326228.
• LNCS'19 "Ensembling descendant term classifiers to improve gene - Abnormal phenotype predictions", Notaro, M., Schubach, M., Frasca, M., Mesiti, M., Robinson, P.N., Valentini, G.. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019, 10834 LNBI, pp. 70–80, doi:10.1007/978-3-030-14160-8_8.
• LNCS'19 "Disease-Genes must guide data source integration in the gene prioritization process", Frasca, M., Fontaine, J.F., Valentini, G., Mesiti, M., Notaro, M., Malchiodi, D., Andrade-Navarro, M.A.. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019, 10834 LNBI, pp. 60–69, doi:10.1007/978-3-030-14160-8_7.

Previous years

• AIM'17 "Gene2DisCo:Gene to disease using disease commonalities", M. Frasca, Artificial Intelligence in Medicine, 82:34-46, 2017. doi:10.1016/j.artmed.2017.08.001.
• IEEE/ACM'17 "Multitask protein function prediction through task dissimilarity", M. Frasca and N. Cesa Bianchi, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 16(5), 2017.
• JCB'15 "Unbalance-aware Network Integration and Prediction of protein functions", M. Frasca, A. Bertoni, G. Valentini, Journal of Computational Biology, 22(12) 1057–1074, 2015.
• NCA'15 "Learning node labels with multi-category Hopfield networks", M. Frasca, S.Bassis, G. Valentini, Neural Computing and Applications, 27(6): 1677-1692, 2015.
• NN'13 "A neural network algorithm for semi-supervised node label learning from unbalanced data", M. Frasca, A. Bertoni, M. Re, and G. Valentini, Neural Networks, 43, pp.84-98, July 2013.
• ECML'11 " COSNet: a Cost Sensitive Neural Network for Semi-supervised Learning in Graphs", A. Bertoni, M. Frasca, G. Valentini, in Proceedings of the European Conference on Machine Learning, ECML PKDD, 2011, Athens, 5-9 September 2011.

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