ArticleBioinformatics (Oxford, England)2018
SSMART: sequence-structure motif identification for RNA-binding proteins.
Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- A resource of RNA-binding protein motifs across eukaryotes reveals evolutionary dynamics and gene-regulatory function.Nature biotechnology · 2026Article
- RNA-protein interaction prediction without high-throughput data: An overview and benchmark ofComputational and structural biotechnology journal · 2024Article
- Positional motif analysis reveals the extent of specificity of protein-RNA interactions observed by CLIP.Genome biology · 2022Article
- RNANetMotif: Identifying sequence-structure RNA network motifs in RNA-protein binding sites.PLoS computational biology · 2022Article
- Interrelationship between miRNA and splicing factors in pancreatic ductal adenocarcinoma.Epigenetics · 2022Review
- The NSUN5-FTH1/FTL pathway mediates ferroptosis in bone marrow-derived mesenchymal stem cells.Cell death discovery · 2022Article
- Protein-RNA interaction prediction with deep learning: structure matters.Briefings in bioinformatics · 2022Article
- Introduction to Bioinformatics Resources for Post-transcriptional Regulation of Gene Expression.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Thermodynamic modeling reveals widespread multivalent binding by RNA-binding proteins.Bioinformatics (Oxford, England) · 2021Article
- SP1 induced long non-coding RNA AGAP2-AS1 promotes cholangiocarcinoma proliferation via silencing of CDKN1A.Molecular medicine (Cambridge, Mass.) · 2021Article
- DeepCLIP: predicting the effect of mutations on protein-RNA binding with deep learning.Nucleic acids research · 2020Article
- Expectation pooling: an effective and interpretable pooling method for predicting DNA-protein binding.Bioinformatics (Oxford, England) · 2020Article
- Deep neural networks for interpreting RNA-binding protein target preferences.Genome research · 2020Article
- Discovering sequence and structure landscapes in RNA interaction motifs.Nucleic acids research · 2019Article
- Deciphering human ribonucleoprotein regulatory networks.Nucleic acids research · 2019Article
- Long noncoding RNA MAPKAPK5-AS1 promotes colorectal cancer proliferation by partly silencing p21 expression.Cancer science · 2019Article
- Dynamic mLife science alliance · 2018Article
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Authors and funding
3 authors.
Funding
Abstract
Motivation: RNA-binding proteins (RBPs) regulate every aspect of RNA metabolism and function. There are hundreds of RBPs encoded in the eukaryotic genomes, and each recognize its RNA targets through a specific mixture of RNA sequence and structure properties. For most RBPs, however, only a primary sequence motif has been determined, while the structure of the binding sites is uncharacterized. Results: We developed SSMART, an RNA motif finder that simultaneously models the primary sequence and the structural properties of the RNA targets sites. The sequence-structure motifs are represented as consensus strings over a degenerate alphabet, extending the IUPAC codes for nucleotides to account for secondary structure preferences. Evaluation on synthetic data showed that SSMART is able to recover both sequence and structure motifs implanted into 3'UTR-like sequences, for various degrees of structured/unstructured binding sites. In addition, we successfully used SSMART on high-throughput in vivo and in vitro data, showing that we not only recover the known sequence motif, but also gain insight into the structural preferences of the RBP. Availability and implementation: SSMART is freely available at https://ohlerlab.mdc-berlin.de/software/SSMART_137/. Supplementary information: Supplementary data are available at Bioinformatics online.
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