Towards inferring nanopore sequencing ionic currents from nucleotide chemical structures.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 34764310.
- Also identified by DOI 10.1038/s41467-021-26929-x and PMC identifier 8586022.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
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.
Medical subject headings
- Nucleotides