Evidence map›Paper›PMID 41478907›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

A New Approach to Define Spectral References for Nucleic Acids Structural Groups.

Kevin Mosca, Sergio Marco

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Article in Methods in molecular biology (Clifton, N.J.), 2026. 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
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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

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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.

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.

Kevin MoscaLaboratoire Léon Brillouin LLB, CEA, CNRS UMR 12, CEA Saclay, Gif-sur-Yvette, France.
Sergio MarcoSanofi. Biophysics, Imaging, Particles & Process analysis Unit Neuville (BIPP-NVL). Biochemistry and Biophysics Neuville. Global Analytical Sciences. EU Hub, Neuville Sur Saône, France. Sergio.Marco@sanofi.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the structural diversity of nucleic acids, particularly RNA, is essential for elucidating their biological functions. However, classifying nucleic acid conformations using a single spectroscopic technique remains challenging due to their inherent structural variability and the absence of standardized spectral references for consistent comparison. This chapter presents a robust, data-driven workflow for defining and validating structural classes of nucleic acids based on spectral data. The method combines manual class definition, spectral normalization, dimensionality reduction via Singular Value Decomposition (SVD), and validation using both linear and nonlinear similarity metrics. An auto-iterative process ensures convergence and consistency in class assignment. This approach enables the creation of reliable reference spectra and supports the classification of unknown samples, offering a valuable tool for structural studies of nucleic acids across various spectroscopic techniques.

Indexed as

Nucleic Acid ConformationNucleic AcidsRNASpectrum AnalysisAlgorithmsNucleic AcidsRNACircular DichroismRNA secondary and tertiary structureRNA spectroscopy; Spectral reference

Identifiers

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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.