ArticleNano letters2016
Electrophoretic Deformation of Individual Transfer RNA Molecules Reveals Their Identity.
Article in Nano letters, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
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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
23 citing papers in PubMed.
- tRNA modifications in cancer: from molecular mechanisms to clinical translation.Biomarker research · 2026Review
- Nanopore sequencing of intact aminoacylated tRNAs.Nature communications · 2025Article
- Chemical Composition and Backbone Modifications Define Deformability of Nucleic Acid Nanoparticles.ACS nano · 2025Article
- Nanopore-Based Neurotransmitter Detection: Advances, Challenges, and Future Perspectives.ACS nano · 2025Review
- Angular-Inertia Regulated Stable and Nanoscale Sensing of Single Molecules Using Nanopore-In-A-Tube.Advanced materials (Deerfield Beach, Fla.) · 2025Article
- Post-transcriptional methylation of mitochondrial-tRNA differentially contributes to mitochondrial pathology.Nature communications · 2024Article
- Article
- T-S2Inet: Transformer-based sequence-to-image network for accurate nanopore sequence recognition.Bioinformatics (Oxford, England) · 2024Article
- Quantitative analysis of tRNA abundance and modifications by nanopore RNA sequencing.Nature biotechnology · 2024Article
- Active learning for efficient analysis of high-throughput nanopore data.Bioinformatics (Oxford, England) · 2023Article
- [Unsupervised deep learning for identifying the OSheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2022Article
- Promising Assays for Examining a Putative Role of Ribosomal Heterogeneity in COVID-19 Susceptibility and Severity.Life (Basel, Switzerland) · 2022Review
- Zero-mode waveguides and nanopore-based sequencing technologies accelerate single-molecule studies.Biophysics and physicobiology · 2022Article
- Article
- Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection.Nature communications · 2021Article
- Structural-profiling of low molecular weight RNAs by nanopore trapping/translocation using Mycobacterium smegmatis porin A.Nature communications · 2021Article
- Ribosome Fingerprinting with a Solid-State Nanopore.ACS sensors · 2020Article
- How Nanopore Translocation Experiments Can Measure RNA Unfolding.Biophysical journal · 2020Article
- Selective detections of single-viruses using solid-state nanopores.Scientific reports · 2018Article
- QuipuNet: Convolutional Neural Network for Single-Molecule Nanopore Sensing.Nano letters · 2018Article
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.
Funding
Abstract
It has been hypothesized that the ribosome gains additional fidelity during protein translation by probing structural differences in tRNA species. We measure the translocation kinetics of different tRNA species through ∼3 nm diameter synthetic nanopores. Each tRNA species varies in the time scale with which it is deformed from equilibrium, as in the translocation step of protein translation. Using machine-learning algorithms, we can differentiate among five tRNA species, analyze the ratios of tRNA binary mixtures, and distinguish tRNA isoacceptors.
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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.