<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>27(1)</volume><submitter>Li J</submitter><pubmed_abstract>Circular RNA (circRNA) represents a critical class of regulatory RNAs with distinctive structural and functional features. The functions of circRNAs are modulated by various RNA modifications. Here, we present CircRM, a nanopore direct RNA sequencing-based computational method for profiling RNA modifications in circRNAs at single-base and single-molecule resolution. By integrating circRNA detection, read-level modification detection, and quantitative assessment of methylation rates, CircRM identified 427 high-confidence circRNAs and enables systematic characterization of three major modifications, m5C (AUC = 0.855), m6A (AUC = 0.817) and m1A (AUC = 0.769). It revealed distinct modification patterns compared with linear RNAs, highlighting RNA-type-specific regulations. We also identified th</pubmed_abstract><journal>Briefings in bioinformatics</journal><pagination>bbaf726</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12798809</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>CircRM: profiling circular RNA modifications from nanopore direct RNA sequencing.</pubmed_title><pmcid>PMC12798809</pmcid><pubmed_authors>Wu Z</pubmed_authors><pubmed_authors>Li J</pubmed_authors><pubmed_authors>Zhang Y</pubmed_authors><pubmed_authors>Wang H</pubmed_authors><pubmed_authors>Xia R</pubmed_authors><pubmed_authors>Chen S</pubmed_authors><pubmed_authors>Meng J</pubmed_authors></additional><is_claimable>false</is_claimable><name>CircRM: profiling circular RNA modifications from nanopore direct RNA sequencing.</name><description>Circular RNA (circRNA) represents a critical class of regulatory RNAs with distinctive structural and functional features. The functions of circRNAs are modulated by various RNA modifications. Here, we present CircRM, a nanopore direct RNA sequencing-based computational method for profiling RNA modifications in circRNAs at single-base and single-molecule resolution. By integrating circRNA detection, read-level modification detection, and quantitative assessment of methylation rates, CircRM identified 427 high-confidence circRNAs and enables systematic characterization of three major modifications, m5C (AUC = 0.855), m6A (AUC = 0.817) and m1A (AUC = 0.769). It revealed distinct modification patterns compared with linear RNAs, highlighting RNA-type-specific regulations. We also identified th</description><dates><release>2026-01-01T00:00:00Z</release><publication>2026 Jan</publication><modification>2026-06-10T03:10:06.97Z</modification><creation>2026-06-10T03:07:16.922Z</creation></dates><accession>S-EPMC12798809</accession><cross_references><pubmed>41529120</pubmed><doi>10.1093/bib/bbaf726</doi></cross_references></HashMap>