ArticleGenome biology2017
DotAligner: identification and clustering of RNA structure motifs.
Article in Genome biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Epigenetic-Genetic Coupling and Understanding the Molecular and Cellular Basis of Lamarckian Inheritance.International journal of molecular sciences · 2026Review
- ECSFinder: optimized prediction of evolutionarily conserved RNA secondary structures from genome sequences.Nucleic acids research · 2025Article
- Clusters of mammalian conserved RNA structures in UTRs associate with RBP binding sites.NAR genomics and bioinformatics · 2024Article
- Long non-coding RNAs: definitions, functions, challenges and recommendations.Nature reviews. Molecular cell biology · 2023Review
- Structure-based screening for functional non-coding RNAs in fission yeast identifies a factor repressing untimely initiation of sexual differentiation.Nucleic acids research · 2022Article
- Deep forest ensemble learning for classification of alignments of non-coding RNA sequences based on multi-view structure representations.Briefings in bioinformatics · 2021Article
- Review
- RNAmountAlign: Efficient software for local, global, semiglobal pairwise and multiple RNA sequence/structure alignment.PloS one · 2020Article
- Article
- Article
- The State of Long Non-Coding RNA Biology.Non-coding RNA · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
The diversity of processed transcripts in eukaryotic genomes poses a challenge for the classification of their biological functions. Sparse sequence conservation in non-coding sequences and the unreliable nature of RNA structure predictions further exacerbate this conundrum. Here, we describe a computational method, DotAligner, for the unsupervised discovery and classification of homologous RNA structure motifs from a set of sequences of interest. Our approach outperforms comparable algorithms at clustering known RNA structure families, both in speed and accuracy. It identifies clusters of known and novel structure motifs from ENCODE immunoprecipitation data for 44 RNA-binding proteins.
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Registered trials
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