<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Miller HE</submitter><funding>NIH/NIA</funding><funding>CPRIT</funding><funding>NIA NIH HHS</funding><funding>NIH/NCI</funding><funding>SU2C-CRUK Pediatric Cancer New Discoveries Challenge Team</funding><funding>DOD</funding><funding>NCI NIH HHS</funding><funding>NIH</funding><funding>NIGMS NIH HHS</funding><pagination>D1129-D1137</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9825527</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>51(D1)</volume><pubmed_abstract>R-loops are three-stranded nucleic acid structures formed from the hybridization of RNA and DNA. In 2012, Ginno et al. introduced the first R-loop mapping method. Since that time, dozens of R-loop mapping studies have been conducted, yielding hundreds of publicly available datasets. Current R-loop databases provide only limited access to these data. Moreover, no web tools for analyzing user-supplied R-loop datasets have yet been described. In our recent work, we reprocessed 810 R-loop mapping samples, building the largest R-loop data resource to date. We also defined R-loop consensus regions and developed a framework for R-loop data analysis. Now, we introduce RLBase, a user-friendly database that provides the capability to (i) explore hundreds of public R-loop mapping datasets, (ii) explo</pubmed_abstract><journal>Nucleic acids research</journal><pubmed_title>Exploration and analysis of R-loop mapping data with RLBase.</pubmed_title><pmcid>PMC9825527</pmcid><funding_grant_id>R01 CA152063</funding_grant_id><funding_grant_id>R01CA152063</funding_grant_id><funding_grant_id>GM139549</funding_grant_id><funding_grant_id>CDMRP PR181598</funding_grant_id><funding_grant_id>P30 CA054174</funding_grant_id><funding_grant_id>RP150445</funding_grant_id><funding_grant_id>R35 GM139549</funding_grant_id><funding_grant_id>F31AG072902</funding_grant_id><funding_grant_id>SU2C #RT6187</funding_grant_id><funding_grant_id>R01 CA241554</funding_grant_id><funding_grant_id>F31 AG072902</funding_grant_id><funding_grant_id>1R01CA241554</funding_grant_id><pubmed_authors>Hartono S</pubmed_authors><pubmed_authors>Li J</pubmed_authors><pubmed_authors>Miller HE</pubmed_authors><pubmed_authors>Montemayor D</pubmed_authors><pubmed_authors>Bishop AJR</pubmed_authors><pubmed_authors>Frost B</pubmed_authors><pubmed_authors>Pawar R</pubmed_authors><pubmed_authors>Levy SA</pubmed_authors><pubmed_authors>Sharma K</pubmed_authors><pubmed_authors>Chedin F</pubmed_authors></additional><is_claimable>false</is_claimable><name>Exploration and analysis of R-loop mapping data with RLBase.</name><description>R-loops are three-stranded nucleic acid structures formed from the hybridization of RNA and DNA. In 2012, Ginno et al. introduced the first R-loop mapping method. Since that time, dozens of R-loop mapping studies have been conducted, yielding hundreds of publicly available datasets. Current R-loop databases provide only limited access to these data. Moreover, no web tools for analyzing user-supplied R-loop datasets have yet been described. In our recent work, we reprocessed 810 R-loop mapping samples, building the largest R-loop data resource to date. We also defined R-loop consensus regions and developed a framework for R-loop data analysis. Now, we introduce RLBase, a user-friendly database that provides the capability to (i) explore hundreds of public R-loop mapping datasets, (ii) explo</description><dates><release>2023-01-01T00:00:00Z</release><publication>2023 Jan</publication><modification>2026-04-28T03:15:19.994Z</modification><creation>2025-04-05T17:02:29.135Z</creation></dates><accession>S-EPMC9825527</accession><cross_references><pubmed>36039757</pubmed><doi>10.1093/nar/gkac732</doi></cross_references></HashMap>