ArticleNucleic acids research2019
TriPepSVM: de novo prediction of RNA-binding proteins based on short amino acid motifs.
Article in Nucleic acids research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
31 citing papers in PubMed, 62 citations in OpenAlex.
- RIBEX: predicting and explaining RNA binding across structured and intrinsically disordered regions (IDR)-rich proteins.Bioinformatics (Oxford, England) · 2026Article
- Bridging technical innovation and computational advances in studies of RNA-protein assemblies.Nature reviews. Genetics · 2026Review
- A framework for the exploration of subcellular compartmentalization of RNA-binding proteins.Nature communications · 2026Article
- Generative design of intrinsically disordered protein regions with IDiom.bioRxiv : the preprint server for biology · 2026Article
- RAPDOR: Using Jensen-Shannon Distance for the computational analysis of complex proteomics datasets.Nature communications · 2025Article
- TransFactor-prediction of pro-viral SARS-CoV-2 host factors using a protein language model.Bioinformatics (Oxford, England) · 2025Article
- R-DeeP/TripepSVM identifies the RNA-binding OB-fold-like protein PatR as regulator of heterocyst patterning.Nucleic acids research · 2025Article
- Bioinformatics Approaches for Understanding the Binding Affinity of Protein-Nucleic Acid Complexes.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Large-scale map of RNA-binding protein interactomes across the mRNA life cycle.Molecular cell · 2024Article
- pyRBDome: a comprehensive computational platform for enhancing RNA-binding proteome data.Life science alliance · 2024Article
- Decoding the genomic landscape of chromatin-associated biomolecular condensates.Nature communications · 2024Article
- High-throughput quantitation of protein-RNA UV-crosslinking efficiencies as a predictive tool for high-confidence identification of RNA-binding proteins.RNA (New York, N.Y.) · 2024Article
- A comprehensive review of protein-centric predictors for biomolecular interactions: from proteins to nucleic acids and beyond.Briefings in bioinformatics · 2024Review
- Exploring new roles for RNA-binding proteins in epigenetic and gene regulation.Current opinion in genetics & development · 2024Review
- HydRA: Deep-learning models for predicting RNA-binding capacity from protein interaction association context and protein sequence.Molecular cell · 2023Article
- Large-scale map of RNA binding protein interactomes across the mRNA life-cycle.bioRxiv : the preprint server for biology · 2023Article
- qNABpredict: Quick, accurate, and taxonomy-aware sequence-based prediction of content of nucleic acid binding amino acids.Protein science : a publication of the Protein Society · 2023Article
- RBP-TSTL is a two-stage transfer learning framework for genome-scale prediction of RNA-binding proteins.Briefings in bioinformatics · 2022Article
- Dual Attention Mechanisms and Feature Fusion Networks Based Method for Predicting LncRNA-Disease Associations.Interdisciplinary sciences, computational life sciences · 2022Article
- The RNA-bound proteome of MRSA reveals post-transcriptional roles for helix-turn-helix DNA-binding and Rossmann-fold proteins.Nature communications · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, hundreds of novel RNA-binding proteins (RBPs) have been identified, leading to the discovery of novel RNA-binding domains. Furthermore, unstructured or disordered low-complexity regions of RBPs have been identified to play an important role in interactions with nucleic acids. However, these advances in understanding RBPs are limited mainly to eukaryotic species and we only have limited tools to faithfully predict RNA-binders in bacteria. Here, we describe a support vector machine-based method, called TriPepSVM, for the prediction of RNA-binding proteins. TriPepSVM applies string kernels to directly handle protein sequences using tri-peptide frequencies. Testing the method in human and bacteria, we find that several RBP-enriched tri-peptides occur more often in structurally disordered regions of RBPs. TriPepSVM outperforms existing applications, which consider classical structural features of RNA-binding or homology, in the task of RBP prediction in both human and bacteria. Finally, we predict 66 novel RBPs in Salmonella Typhimurium and validate the bacterial proteins ClpX, DnaJ and UbiG to associate with RNA in vivo.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.