Author

C. Pancotti

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Preprint Sep 2026

Predicting Mutational Signature Exposures from H&E Whole Slide Images: A Pan-Cancer Feasibility Study

Mutational signatures reveal cancer-driving processes with clinical relevance: MMR-deficient tumors respond better to immunotherapy, HRD tumors are sensitive to PARP inhibitors, and POLE-mutant tumors often have high mutation burdens influencing treatment response. Yet signature profiling remains limited by the cost, c...

Flavio Sartori, C. Rollo, Isabella Caranzano et al. · 0 citations

Open access Aug 2026

A generative model for dimensionality reduction with millions of features and few samples

It is demonstrated that it is feasible to train a deep generative model for dimensionality reduction with millions of features using few samples, which makes this type of generative model a more versatile alternative to standard methods for dimensionality reduction.

C. Pancotti, P. Fariselli, J. Meisner et al. · bioRxiv · 0 citations