ArticleFrontiers in molecular biosciences2022
Predicting higher-order mutational effects in an RNA enzyme by machine learning of high-throughput experimental data.
Article in Frontiers in molecular biosciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 8 citations in OpenAlex.
- Machine-learning prediction of affinity and epistasis in the bovine pancreatic trypsin inhibitor-chymotrypsin complex.Protein science : a publication of the Protein Society · 2026Article
- Probing the Specificity of Fluorescent Deoxyribozymes Using Single-Step Selections and Machine Learning.ACS chemical biology · 2026Article
- Using structured libraries, selection, and machine learning to rapidly explore the sequence space of a fluorescent deoxyribozyme.Nucleic acids research · 2025Article
- Machine Learning-Assisted Engineering of Light, Oxygen, Voltage Photoreceptor Adduct Lifetime.JACS Au · 2023Article
- Discovering pathways through ribozyme fitness landscapes using information theoretic quantification of epistasis.RNA (New York, N.Y.) · 2023Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ribozymes are RNA molecules that catalyze biochemical reactions. Self-cleaving ribozymes are a common naturally occurring class of ribozymes that catalyze site-specific cleavage of their own phosphodiester backbone. In addition to their natural functions, self-cleaving ribozymes have been used to engineer control of gene expression because they can be designed to alter RNA processing and stability. However, the rational design of ribozyme activity remains challenging, and many ribozyme-based systems are engineered or improved by random mutagenesis and selection (
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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.