Evidence map›Paper›PMID 39507401›Full record

ArticleMolecular therapy. Nucleic acids2024

AptamerRunner: An accessible aptamer structure prediction and clustering algorithm for visualization of selected aptamers.

Dario Ruiz-Ciancio, Suresh Veeramani, Rahul Singh, Eric Embree, Chris Ortman, Kristina W Thiel, William H Thiel

Abstract read
In one paragraph

Article in Molecular therapy. Nucleic acids, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Identification of In Vivo Internalizing Cardiac-Specific RNA Aptamers.bioRxiv : the preprint server for biology · 2024
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Dario Ruiz-CiancioInstituto de Ciencias Biomédicas (ICBM), Facultad de Ciencias Médicas, Universidad Católica de Cuyo, Av. José Ignacio de la Roza 1516, Rivadavia 5400, San Juan, Argentina.
Suresh VeeramaniDepartment of Internal Medicine, University of Iowa, Iowa City, IA 52242, USA.
Rahul SinghDepartment of Computer Sciences, University of Iowa, Iowa City, IA 52242, USA.
Eric EmbreeCarver College of Medicine, University of Iowa, Iowa City, IA 52242, USA.
Chris OrtmanInstitute for Clinical and Translational Science, University of Iowa, Iowa City, IA 52242, USA.
Kristina W ThielHolden Comprehensive Cancer Center, University of Iowa, Iowa City, IA 52242, USA.
William H ThielDepartment of Internal Medicine, University of Iowa, Iowa City, IA 52242, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aptamers are short single-stranded DNA or RNA molecules with high affinity and specificity for targets and are generated using the iterative systematic evolution of ligands by exponential enrichment (SELEX) process. Next-generation sequencing (NGS) revolutionized aptamer selections by allowing a more comprehensive analysis of SELEX-enriched aptamers as compared to Sanger sequencing. The current challenge with aptamer NGS datasets is identifying a diverse cohort of candidate aptamers with the highest likelihood of successful experimental validation. Here we present AptamerRunner, an aptamer sequence and/or structure clustering algorithm that synergistically integrates computational analysis with visualization and expertise-directed decision making. The visual integration of networked aptamers with ranking data, such as fold enrichment or scoring algorithm results, represents a significant advancement over existing clustering tools by providing a natural context to depict groups of aptamers from which ranked or scored candidates can be chosen for experimental validation. The inherent flexibility, user-friendly design, and prospects for future enhancements with AptamerRunner have broad-reaching implications for aptamer researchers across a wide range of disciplines.

Indexed as

aptamerAptamerRunnerbioinformaticsclusteringCytoscapeedit distanceMT: Bioinformaticssequence analysisstructure analysistree distance

Identifiers

PMID39507401
PMCPMC11539416

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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.