ArticleNucleic acids research2006
Using RNA secondary structures to guide sequence motif finding towards single-stranded regions.
Article in Nucleic acids research, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers.
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Who cites it
88 citing papers in PubMed, 173 citations in OpenAlex.
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- From randomness to recognition: modeling the evolution of DNA sequence information during enrichment for binding.Bioinformatics advances · 2026Article
- RNA Structure and Its Function.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Single-sequence protein-RNA complex structure prediction by geometric attention-enabled pairing of biological language models.Cell systems · 2025Article
- From benign to pathogenic variants and vice versa: pyrimidine transitions at position -3 of TAG and CAG 3' splice sites.Journal of human genetics · 2025Article
- A systematic benchmark of machine learning methods for protein-RNA interaction prediction.Briefings in bioinformatics · 2023Article
- DAPTEV: Deep aptamer evolutionary modelling for COVID-19 drug design.PLoS computational biology · 2023Article
- In vitro selection of aptamers and their applications.Nature reviews. Methods primers · 2023Article
- PRIESSTESS: interpretable, high-performing models of the sequence and structure preferences of RNA-binding proteins.Nucleic acids research · 2022Article
- RNANetMotif: Identifying sequence-structure RNA network motifs in RNA-protein binding sites.PLoS computational biology · 2022Article
- DeepPN: a deep parallel neural network based on convolutional neural network and graph convolutional network for predicting RNA-protein binding sites.BMC bioinformatics · 2022Article
- PhyloPGM: boosting regulatory function prediction accuracy using evolutionary information.Bioinformatics (Oxford, England) · 2022Article
- Aptamers as promising nanotheranostic tools in the COVID-19 pandemic era.Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology · 2022Review
- RNALigands: a database and web server for RNA-ligand interactions.RNA (New York, N.Y.) · 2022Article
- Inferring RNA-binding protein target preferences using adversarial domain adaptation.PLoS computational biology · 2022Article
- Protein-RNA interaction prediction with deep learning: structure matters.Briefings in bioinformatics · 2022Article
- RBPmap: A Tool for Mapping and Predicting the Binding Sites of RNA-Binding Proteins Considering the Motif Environment.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Prediction of RNA-protein interactions using a nucleotide language model.Bioinformatics advances · 2022Article
- Aptamers targeting amyloidogenic proteins and their emerging role in neurodegenerative diseases.The Journal of biological chemistry · 2022Review
28 more citing papers are in PubMed but not listed here.
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
RNA binding proteins recognize RNA targets in a sequence specific manner. Apart from the sequence, the secondary structure context of the binding site also affects the binding affinity. Binding sites are often located in single-stranded RNA regions and it was shown that the sequestration of a binding motif in a double-strand abolishes protein binding. Thus, it is desirable to include knowledge about RNA secondary structures when searching for the binding motif of a protein. We present the approach MEMERIS for searching sequence motifs in a set of RNA sequences and simultaneously integrating information about secondary structures. To abstract from specific structural elements, we precompute position-specific values measuring the single-strandedness of all substrings of an RNA sequence. These values are used as prior knowledge about the motif starts to guide the motif search. Extensive tests with artificial and biological data demonstrate that MEMERIS is able to identify motifs in single-stranded regions even if a stronger motif located in double-strand parts exists. The discovered motif occurrences in biological datasets mostly coincide with known protein-binding sites. This algorithm can be used for finding the binding motif of single-stranded RNA-binding proteins in SELEX or other biological sequence data.
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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.