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Generative and interpretable machine learning for aptamer design and analysis of in vitro sequence selection
Di Gioacchino A,
Procyk J,
Molari M,
Schreck JS,
Zhou Y,
et al.
(2022)
Generative and interpretable machine learning for aptamer design and analysis of in vitro sequence selection.
PLOS Computational Biology 18(9): e1010561.
https://doi.org/10.1371/journal.pcbi.1010561