The characteristic ionic currents of nucleotide kmers are commonly used in analyzing nanopore sequencing readouts. We present a graph convolutional network-based deep learning framework for predicting kmer characteristic ionic currents from corresponding chemical structures. We show such a framework can generalize the chemical information of the 5-methyl group from thymine to cytosine by correctly predicting 5-methylcytosine-containing DNA 6mers, thus shedding light on the de novo detection of nucleotide modifications.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8586022 | PMC |
http://dx.doi.org/10.1038/s41467-021-26929-x | DOI Listing |
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