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SeqMaestro: From nucleotide sequences to biological hypotheses through interpretable machine learning

Saveliev, Evgeny S. et al.
arXiv (OAI Expanded) · Papers
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Nucleotide sequence analysis is central to problems spanning regulatory genomics, evolutionary biology, and phenotype prediction. Classical bioinformatics methods extract interpretable sequence properties such as motifs and k-mer composition, but their flexibility is limited. In contrast, modern dee
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