AImageLab publications export - 30 publications; author=mlovino

Grasso, M., Fidilio, A., L'Episcopo, F., Recupero, M., Barone, C., Lovino, M., Alboni, S., Bacalini, M. G., Caruso, G., Greco, D., Buono, S., De La Torre, R., Tascedda, F., Blom, J. M., Benatti, C., & Caraci, F. (2026). Searching for New Possible Peripheral Biomarkers of Cognitive Decline in Down Syndrome: The Role of IL-18 Pathway and its Interaction with TGF-β1 and TNF-α. NEUROMOLECULAR MEDICINE. https://doi.org/10.1007/s12017-025-08901-w

Bernardi, F., Torrejon, J., Basili, I., Van Ommeren, R., Marsaud, V., Yu, H., Talbot, J., Souphron, J., Indersie, E., Forget, A., Bonneau, B., Massiot, A., Alcazar, C., Figeac, L., Bonerandi, E., Cancila, G., Sirbu, O., Yadav, N., Mohanakrishnan, D., ... Agnihotri, S. (2026). Multiomic integration reveals tumoral heterogeneity of lipid dependence within lethal group 3 medulloblastoma. CANCER CELL. https://doi.org/10.1016/j.ccell.2025.12.012

Miccolis, F., Ficarra, E., & Lovino, M. (2026). Practical guidelines for multiple instance learning in computational pathology: how embedding choice impacts overall survival prediction. FRONTIERS IN BIOINFORMATICS. https://doi.org/10.3389/fbinf.2026.1809049

Miccolis, F., Demarco, M., Ficarra, E., & Lovino, M. (2026). MuGNet: a graph-based framework for multi-tissue integration in computational pathology. PEERJ. COMPUTER SCIENCE. https://doi.org/10.7717/peerj-cs.3820

Miccolis, F., Lovino, M., Lehtonen, O., Hynninen, J., Hautaniemi, S., Virtanen, A., & Ficarra, E. (2026). PATHOS: Pathology attention framework for treatment response stratification in ovarian high-grade serous carcinomas following neoadjuvant chemotherapy on H&E images. JOURNAL OF PATHOLOGY INFORMATICS. https://doi.org/10.1016/j.jpi.2026.100545

Adani, E., Vasquez, S. S. V., Lovino, M., Bighinati, A., Cappellino, L., D'Alessandro, S., Kalatzis, V., & Marigo, V. (2026). Modulation of Aerobic Glycolysis Genes During the Progression of Retinitis Pigmentosa. INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE. https://doi.org/10.1167/iovs.67.1.49

Miccolis, F., Lovino, M., & Ficarra, E. (2025). A Benchmark Study of Gene Fusion Prioritization Tools. International Conference on Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB). https://doi.org/10.1007/978-3-031-90714-2_15

Miccolis, F., Marinelli, F., Pipoli, V., Afenteva, D., Virtanen, A., Lovino, M., & Ficarra, E. (2025). OXA-MISS: A Robust Multimodal Architecture for Chemotherapy Response Prediction under Data Scarcity. INTERNATIONAL CONFERENCE ON MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION. https://iris.unimore.it/handle/11380/1389572

Bellameche, F., Modica, F., Cortiello, M., Costi, E., Riccioni, C., De Marchis, F., Rubini, A., Belfiori, B., Bellucci, M., Brilli, L., Sberveglieri, V., Lovino, M., Núñez-Carmona, E., & Giovanardi, D. (2025). Root colonization pattern of Pseudomonas spp. strains: a key step in the biocontrol of soilborne pathogens in hops. JOURNAL OF PLANT PATHOLOGY. https://doi.org/10.1007/s42161-025-02022-w

Miccolis, F., Riccomi, O., Lovino, M., & Ficarra, E. (2025). Impact of Embedding Methods on Weakly Supervised Lymph Node Classification with MIL on the Camelyon16 Dataset. Conference on Computational Intelligence methods for Bioinformatics and Biostatistics Milano. https://iris.unimore.it/handle/11380/1390234

Corso, G., Lovino, M., Akpinar, R., Di Tommaso, L., Ficarra, E., & Ranzini, M. (2025). Foundation Models for Hepatocellular Carcinoma: Challenges in Generalization under Data Scarcity. International Joint Conference on Neural Networks (IJCNN). https://doi.org/10.1109/IJCNN64981.2025.11228716

Rausio, H., Cervera, A., Heuser, V. D., West, G., Oikkonen, J., Pianfetti, E., Lovino, M., Ficarra, E., Taimen, P., Hynninen, J., Lehtonen, R., Hautaniemi, S., Carpen, O., & Huhtinen, K. (2024). PIK3R1 fusion drives chemoresistance in ovarian cancer by activating ERK1/2 and inducing rod and ring-like structures. NEOPLASIA. https://doi.org/10.1016/j.neo.2024.100987

Lovino, M., Ficarra, E., & Martignetti, L. (2024). Integrated microRNA and proteome analysis of cancer datasets with MoPC. PLOS ONE. https://doi.org/10.1371/journal.pone.0289699

Pianfetti, E., Lovino, M., Ficarra, E., & Martignetti, L. (2023). MiREx: mRNA levels prediction from gene sequence and miRNA target knowledge. BMC BIOINFORMATICS. https://doi.org/10.1186/s12859-023-05560-1

Bontempo, G., Bartolini, N., Lovino, M., Bolelli, F., Virtanen, A., & Ficarra, E. (2023). Enhancing PFI Prediction with GDS-MIL: A Graph-based Dual Stream MIL Approach. International Conference on Image Analysis and Processing (ICIAP). https://doi.org/10.1007/978-3-031-43148-7_46

Ghione, G., Lovino, M., Ficarra, E., & Cirrincione, G. (2023). BERT Classifies SARS-CoV-2 Variants. SMART INNOVATION, SYSTEMS AND TECHNOLOGIES. https://doi.org/10.1007/978-981-99-3592-5_15

Cirrincione, G., Cannata, S., Cicceri, G., Prinzi, F., Currieri, T., Lovino, M., Militello, C., Pasero, E., & Vitabile, S. (2023). Transformer-Based Approach to Melanoma Detection. SENSORS. https://doi.org/10.3390/s23125677

Stefanini, M., Lovino, M., Cucchiara, R., & Ficarra, E. (2023). Predicting gene and protein expression levels from DNA and protein sequences with Perceiver. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE. https://doi.org/10.1016/j.cmpb.2023.107504

Pipoli, V., Cappelli, M., Palladini, A., Peluso, C., Lovino, M., & Ficarra, E. (2022). Predicting gene expression levels from DNA sequences and post-transcriptional information with transformers. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE. https://doi.org/10.1016/j.cmpb.2022.107035

Citarrella, F., Bontempo, G., Lovino, M., & Ficarra, E. (2022). FusionFlow: an integrated system workflow for gene fusion detection in genomic samples. Workshop on Intelligent Data - From Data to Knowledge (DOING). https://doi.org/10.1007/978-3-031-15743-1_8

Borgato, S., Bottino, M., Lovino, M., & Ficarra, E. (2022). SARS-CoV-2 variants classification and characterization. International Conference on Bioinformatics and Computational Biology (BICOB). https://iris.unimore.it/handle/11380/1281685

Lovino, M., Montemurro, M., Barrese, V. S., & Ficarra, E. (2022). Identifying the oncogenic potential of gene fusions exploiting miRNAs. JOURNAL OF BIOMEDICAL INFORMATICS. https://doi.org/10.1016/j.jbi.2022.104057

Lovino, M., Randazzo, V., Ciravegna, G., Barbiero, P., Ficarra, E., & Cirrincione, G. (2022). A survey on data integration for multi-omics sample clustering. NEUROCOMPUTING. https://doi.org/10.1016/j.neucom.2021.11.094

Rickert, D., Bartl, J., Picard, D., Bernardi, F., Qin, N., Lovino, M., Puget, S., Meyer, F., Mahoungou Koumba, I., Beez, T., Varlet, P., Dufour, C., Fischer, U., Borkhardt, A., Reifenberger, G., Ayrault, O., & Remke, M. (2021). Circular RNA profiling distinguishes medulloblastoma groups and shows aberrant RMST overexpression in WNT medulloblastoma. ACTA NEUROPATHOLOGICA. https://doi.org/10.1007/s00401-021-02306-2

Lovino, M., Urgese, G., Macii, E., Santa Di Cataldo, & Ficarra, E. (2020). Predicting the oncogenic potential of gene fusions using convolutional neural networks. International Conference on Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB). https://doi.org/10.1007/978-3-030-34585-3_24

Lovino, M., Bontempo, G., Cirrincione, G., & Ficarra, E. (2020). Multi-omics Classification on Kidney Samples Exploiting Uncertainty-Aware Models. International Conference, ICIC Bari (Online). https://doi.org/10.1007/978-3-030-60802-6_4

Barbiero, P., Lovino, M., Siviero, M., Ciravegna, G., Randazzo, V., Ficarra, E., & Cirrincione, G. (2020). Unsupervised Multi-Omic Data Fusion: the Neural Graph Learning Network. International Conference on Intelligent Computing (ICIC). https://doi.org/10.1007/978-3-030-60799-9_15

Lovino, M., Ciaburri, M. S., Urgese, G., Di Cataldo, S., & Ficarra, E. (2020). DEEPrior: a deep learning tool for the prioritization of gene fusions. BIOINFORMATICS. https://doi.org/10.1093/bioinformatics/btaa069

Lovino, M., Urgese, G., Macii, E., Di Cataldo, S., & Ficarra, E. (2019). A Deep Learning Approach to the Screening of Oncogenic Gene Fusions in Humans. INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES. https://doi.org/10.3390/ijms20071645

Roberti, I., Lovino, M., Di Cataldo, S., Ficarra, E., & Urgese, G. (2019). Exploiting Gene Expression Profiles for the Automated Prediction of Connectivity between Brain Regions. INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES. https://doi.org/10.3390/ijms20082035