ArticleNucleic acids research2016
A novel method for the identification of conserved structural patterns in RNA: From small scale to high-throughput applications.
Article in Nucleic acids research, 2016. 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, 24 citations in OpenAlex.
- RNAtive to recognize native-like structure in a set of RNA 3D models.Bioinformatics (Oxford, England) · 2025Article
- Definition of the binding specificity of the T7 bacteriophage primase by analysis of a protein binding microarray using a thermodynamic model.Nucleic acids research · 2024Article
- RNANetMotif: Identifying sequence-structure RNA network motifs in RNA-protein binding sites.PLoS computational biology · 2022Article
- PhyloPGM: boosting regulatory function prediction accuracy using evolutionary information.Bioinformatics (Oxford, England) · 2022Article
- Relative Information Gain: Shannon entropy-based measure of the relative structural conservation in RNA alignments.NAR genomics and bioinformatics · 2021Article
- Motif Discovery from CLIP Experiments.Methods in molecular biology (Clifton, N.J.) · 2021Article
- Discovering sequence and structure landscapes in RNA interaction motifs.Nucleic acids research · 2019Article
- Long Noncoding RNA and Protein Interactions: From Experimental Results to Computational Models Based on Network Methods.International journal of molecular sciences · 2019Article
- RNAvista: a webserver to assess RNA secondary structures with non-canonical base pairs.Bioinformatics (Oxford, England) · 2019Article
- Prediction of RNA-protein sequence and structure binding preferences using deep convolutional and recurrent neural networks.BMC genomics · 2018Article
- BEAM web server: a tool for structural RNA motif discovery.Bioinformatics (Oxford, England) · 2018Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Functional RNA regions are often related to recurrent secondary structure patterns (or motifs), which can exert their role in several different ways, particularly in dictating the interaction with RNA-binding proteins, and acting in the regulation of a large number of cellular processes. Among the available motif-finding tools, the majority focuses on sequence patterns, sometimes including secondary structure as additional constraints to improve their performance. Nonetheless, secondary structures motifs may be concurrent to their sequence counterparts or even encode a stronger functional signal. Current methods for searching structural motifs generally require long pipelines and/or high computational efforts or previously aligned sequences. Here, we present BEAM (BEAr Motif finder), a novel method for structural motif discovery from a set of unaligned RNAs, taking advantage of a recently developed encoding for RNA secondary structure named BEAR (Brand nEw Alphabet for RNAs) and of evolutionary substitution rates of secondary structure elements. Tested in a varied set of scenarios, from small- to large-scale, BEAM is successful in retrieving structural motifs even in highly noisy data sets, such as those that can arise in CLIP-Seq or other high-throughput experiments.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.