12 citations · 12 across the 2 of their papers we have counts for
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q-bio.BM2025
Integrating experimental feedback improves generative models for biological sequences
Francesco Calvanese, Giovanni Peinetti, Polina Pavlinova +2
Generative probabilistic models have shown promise in designing artificial RNA and protein sequences but often suffer from high rates of false positives, where sequences predicted…
q-bio.BM2023★ 12 cited
Towards Parsimonious Generative Modeling of RNA Families
Francesco Calvanese, Camille N. Lambert, Philippe Nghe +2
Generative probabilistic models emerge as a new paradigm in data-driven, evolution-informed design of biomolecular sequences. This paper introduces a novel approach, called Edge Ac…