ArticleNucleic acids research2017
Bayesian prediction of RNA translation from ribosome profiling.
Article in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.
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Who cites it
49 citing papers in PubMed.
- RiboBA: a bias-aware probabilistic framework for robust ORF identification across diverse ribosome profiling protocols.Nucleic acids research · 2026Article
- Computational identification and characterization of noncoding RNA-encoded peptides: tools, databases, and in silico strategies.Amino acids · 2026Review
- ATMLP Enhances Radioresistance in Non-Small Cell Lung Cancer through AKT-Mediated Lipid Droplet Accumulation.International journal of biological sciences · 2026Article
- Proteogenomics Reveals Microproteins in Activated T Cells.Molecular & cellular proteomics : MCP · 2025Article
- Small open reading frame-encoded microproteins in cancer: identification, biological functions and clinical significance.Molecular cancer · 2025Review
- Deep learning to decode sites of RNA translation in normal and cancerous tissues.Nature communications · 2025Article
- Transient Inhibition of Translation Improves Cardiac Function After Ischemia/Reperfusion by Attenuating the Inflammatory Response.Circulation · 2024Article
- LncRNA-encoded peptides in cancer.Journal of hematology & oncology · 2024Review
- Rp3: Ribosome profiling-assisted proteogenomics improves coverage and confidence during microprotein discovery.Nature communications · 2024Article
- Next generation sequencing technologies to address aberrant mRNA translation in cancer.NAR cancer · 2024Review
- Deep learning to decode sites of RNA translation in normal and cancerous tissues.bioRxiv : the preprint server for biology · 2024Article
- Review
- PEPseq quantifies transcriptome-wide changes in protein occupancy and reveals selective translational repression after translational stress.Nucleic acids research · 2023Article
- Small Open Reading Frame-Encoded Micro-Peptides: An Emerging Protein World.International journal of molecular sciences · 2023Review
- A vast evolutionarily transient translatome contributes to phenotype and fitness.Cell systems · 2023Article
- Discovering microproteins: making the most of ribosome profiling data.RNA biology · 2023Review
- Review
- Analysis of myocardial cellular gene expression during pressure overload reveals matrix based functional intercellular communication.iScience · 2022Article
- RiboReport - benchmarking tools for ribosome profiling-based identification of open reading frames in bacteria.Briefings in bioinformatics · 2022Article
- Small open reading frames in plant research: from prediction to functional characterization.3 Biotech · 2022Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ribosome profiling via high-throughput sequencing (ribo-seq) is a promising new technique for characterizing the occupancy of ribosomes on messenger RNA (mRNA) at base-pair resolution. The ribosome is responsible for translating mRNA into proteins, so information about its occupancy offers a detailed view of ribosome density and position which could be used to discover new translated open reading frames (ORFs), among other things. In this work, we propose Rp-Bp, an unsupervised Bayesian approach to predict translated ORFs from ribosome profiles. We use state-of-the-art Markov chain Monte Carlo techniques to estimate posterior distributions of the likelihood of translation of each ORF. Hence, an important feature of Rp-Bp is its ability to incorporate and propagate uncertainty in the prediction process. A second novel contribution is automatic Bayesian selection of read lengths and ribosome P-site offsets (BPPS). We empirically demonstrate that our read length selection technique modestly improves sensitivity by identifying more canonical and non-canonical ORFs. Proteomics- and quantitative translation initiation sequencing-based validation verifies the high quality of all of the predictions. Experimental comparison shows that Rp-Bp results in more peptide identifications and proteomics-validated ORF predictions compared to another recent tool for translation prediction.
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