Evidence map›Paper›PMID 38217664›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2024

sRNA Structural Modeling Based on NMR Data.

Pengzhi Wu, Lingna Yang

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Article in Methods in molecular biology (Clifton, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 99% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 2 countries.

Pengzhi WuHefei National Laboratory for Physical Sciences at the Microscale, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, People's Republic of China. pengzhi.wu@bc.biol.ethz.ch.
Lingna YangHefei National Laboratory for Physical Sciences at the Microscale, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, People's Republic of China.
ETH Zurich · CHUniversity of Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Small non-coding RNAs (sRNAs) play vital roles in gene expression regulation and RNA interference. To comprehend their molecular mechanisms and develop therapeutic approaches, determining the accurate three-dimensional structure of sRNAs is crucial. Although nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for structural biology, obtaining high-resolution structures of sRNAs using NMR data alone can be challenging. In such cases, structural modeling can provide additional details about RNA structures. In this context, we present a protocol for the structural modeling of sRNA using the SimRNA method based on sparse NMR constraints. To demonstrate the efficacy of our method, we provide selected examples of NMR spectra and RNA structures, specifically for the second stem-loop of DsrA sRNA.

Indexed as

RNARNA, Small UntranslatedGene Expression Regulation, BacterialMagnetic Resonance ImagingMagnetic Resonance SpectroscopyRNA, BacterialRNARNA, BacterialRNA, Small UntranslatedImino protonNMR spectroscopyRNA structureSimRNAStructural modeling

Identifiers

PMID38217664
OpenAlexW4390843444

What OpenQuestion holds

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Registered trials

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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.