Author

U. Lomoio

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Open access Sep 2026

Interpretable Classification of Missense Variants Using ESM2 Embeddings and UMAP

Missense variants can alter protein stability, conformation, activity, or expression, yet their clinical interpretation remains challenging, particularly for variants of uncertain significance. Protein language models provide sequence derived representations that capture evolutionary and biophysical constraints, but...

Ugo Lomoio, T. Mazza, Pierangelo Veltri et al. · Bioinformatics Advances · 0 citations

Open access Jul 2026

Deep Learning-Based Malaria Parasite Image Classification on Real Microscopy Data

The findings demonstrate that convolutional, transformer-based, and hybrid deep learning architectures can be successfully trained on real microscopy data for species-level malaria diagnosis and support the feasibility of deploying scalable, automated diagnostic systems to improve both accuracy and accessibility of mal...

F. Branda, Lilia Andriani, Riccardo Lucis et al. · Infectious Disease Reports · 0 citations

Jul 2026

Comparing Mpox epidemic controls through simulations and explainable graph convolution networks: A case study in the Republic of the Congo and Nigeria

The study supports the potential usefulness of combining contact-based models with explainable graph neural networks for scenario-based epidemic analysis and suggests that the k-GCN model captures relevant temporal and structural dependencies in the simulated graph-organized data.

Francesco Branda, G. Ceccarelli, Massimo Ciccozzi et al. · Network Modeling Analysis in... · 0 citations