rPredictorDB: a predictive database of individual secondary structures of RNAs and their formatted plots
Language English Country Great Britain, England Media print
Document type Journal Article, Research Support, Non-U.S. Gov't
PubMed
31032840
PubMed Central
PMC6482342
DOI
10.1093/database/baz047
PII: 5479229
Knihovny.cz E-resources
- MeSH
- Databases, Nucleic Acid * MeSH
- Nucleic Acid Conformation * MeSH
- RNA * chemistry genetics MeSH
- Software * MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Names of Substances
- RNA * MeSH
Secondary data structure of RNA molecules provides insights into the identity and function of RNAs. With RNAs readily sequenced, the question of their structural characterization is increasingly important. However, RNA structure is difficult to acquire. Its experimental identification is extremely technically demanding, while computational prediction is not accurate enough, especially for large structures of long sequences. We address this difficult situation with rPredictorDB, a predictive database of RNA secondary structures that aims to form a middle ground between experimentally identified structures in PDB and predicted consensus secondary structures in Rfam. The database contains individual secondary structures predicted using a tool for template-based prediction of RNA secondary structure for the homologs of the RNA families with at least one homolog with experimentally solved structure. Experimentally identified structures are used as the structural templates and thus the prediction has higher reliability than de novo predictions in Rfam. The sequences are downloaded from public resources. So far rPredictorDB covers 7365 RNAs with their secondary structures. Plots of the secondary structures use the Traveler package for readable display of RNAs with long sequences and complex structures, such as ribosomal RNAs. The RNAs in the output of rPredictorDB are extensively annotated and can be viewed, browsed, searched and downloaded according to taxonomic, sequence and structure data. Additionally, structure of user-provided sequences can be predicted using the templates stored in rPredictorDB.
Laboratory of Bioinformatics Institute of Microbiology The Czech Academy of Sciences Videnska Praha
Luxembourg Centre for Systems Biomedicine University of Luxembourg avenue du Swing Belvaux
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R2DT is a framework for predicting and visualising RNA secondary structure using templates