4 citations · 8 across the 7 of their papers we have counts for
5 papers · 1 filter
Predicting Mutational Signature Exposures from H&E Whole Slide Images: A Pan-Cancer Feasibility Study
Flavio Sartori, Cesare Rollo, Isabella Caranzano +3
Mutational signatures reveal cancer-driving processes with clinical relevance: MMR-deficient tumors respond better to immunotherapy, HRD tumors are sensitive to PARP inhibitors, an…
Sparsity is All You Need: Rethinking Biological Pathway-Informed Approaches in Deep Learning
Isabella Caranzano, Corrado Pancotti, Cesare Rollo +4
Biologically-informed neural networks typically leverage pathway annotations to enhance performance in biomedical applications. We hypothesized that the benefits of pathway integra…
JanusDDG: A Thermodynamics-Compliant Model for Sequence-Based Protein Stability via Two-Fronts Multi-Head Attention
Guido Barducci, Ivan Rossi, Francesco Codicè +6
Understanding how residue variations affect protein stability is crucial for designing functional proteins and deciphering the molecular mechanisms underlying disease-related mutat…
Mass Balance Approximation of Unfolding Improves Potential-Like Methods for Protein Stability Predictions
Ivan Rossi, Guido Barducci, Tiziana Sanavia +3
The prediction of protein stability changes following single-point mutations plays a pivotal role in computational biology, particularly in areas like drug discovery, enzyme reengi…
SurvHive: a package to consistently access multiple survival-analysis packages
Giovanni Birolo, Ivan Rossi, Flavio Sartori +3
Survival analysis, a foundational tool for modeling time-to-event data, has seen growing integration with machine learning (ML) approaches to handle the complexities of censored da…