Evidence map›Paper›PMID 28480997›Full record

ReviewChemMedChem2017

Nucleic Acid Templated Reactions for Chemical Biology.

Margherita Di Pisa, Oliver Seitz

Open access · hybridAbstract readReview
In one paragraph

Review in ChemMedChem, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
3.8field-weighted citation impact, top 6% 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

25 citing papers in PubMed, 63 citations in OpenAlex.

  1. Toward Ideal Proximity-Driven Reactions in Chemical Biology.Chembiochem : a European journal of chemical biology · 2026
    Review
  2. Fuel-Driven Catalytic Molecular Templating.Journal of the American Chemical Society · 2026
    Article
  3. Review
  4. Article
  5. Reactive Quantum Dot-Based FRET Systems for Target-Catalyzed Detection of RNA.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Review
  18. Review
  19. Article
  20. PNA-Based MicroRNA Detection Methodologies.Molecules (Basel, Switzerland) · 2020
    Review
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 1 institution in 1 country.

Margherita Di PisaDepartment of Chemistry, Humboldt University Berlin, Brook-Taylor Strasse 2, 12489, Berlin, Germany.
Oliver SeitzDepartment of Chemistry, Humboldt University Berlin, Brook-Taylor Strasse 2, 12489, Berlin, Germany.
Humboldt-Universität zu Berlin · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nucleic acid directed bioorthogonal reactions offer the fascinating opportunity to unveil and redirect a plethora of intracellular mechanisms. Nano- to picomolar amounts of specific RNA molecules serve as templates and catalyze the selective formation of molecules that 1) exert biological effects, or 2) provide measurable signals for RNA detection. Turnover of reactants on the template is a valuable asset when concentrations of RNA templates are low. The idea is to use RNA-templated reactions to fully control the biodistribution of drugs and to push the detection limits of DNA or RNA analytes to extraordinary sensitivities. Herein we review recent and instructive examples of conditional synthesis or release of compounds for in cellulo protein interference and intracellular nucleic acid imaging.

Indexed as

DNARNAMolecular StructurePharmaceutical PreparationsTemplates, GeneticDNAPharmaceutical PreparationsRNAin situ drug releasein situ drug synthesisnucleic acid encoded reactionsnucleic acid sensing

Identifiers

PMID28480997
PMCPMC5488204
OpenAlexW2613657536

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.