Evidence map›Paper›PMID 28503546›Full record

ArticleFrontiers in chemistry2017

Computational Tool for Fast

Giulia Chemi, Sandra Gemma, Giuseppe Campiani, Simone Brogi, Stefania Butini, Margherita Brindisi

Open access · goldAbstract read
In one paragraph

Article in Frontiers in chemistry, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
6.2field-weighted citation impact, top 3% 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

26 citing papers in PubMed, 63 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. In Silico Models for Predicting Acute Systemic Toxicity.Methods in molecular biology (Clifton, N.J.) · 2022
    Review
  9. Quinazolin-4(3Journal of enzyme inhibition and medicinal chemistry · 2021
    Article
  10. Trends in application of advancing computational approaches in GPCR ligand discovery.Experimental biology and medicine (Maywood, N.J.) · 2021
    Review
  11. Review
  12. Cinnamides TargetMolecules (Basel, Switzerland) · 2020
    Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Computational Approaches for Drug Discovery.Molecules (Basel, Switzerland) · 2019
    Article
  18. Article
  19. Article
  20. Deep Learning-Based Prediction of Drug-Induced Cardiotoxicity.Journal of chemical information and modeling · 2019
    Article
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

6 authors at 1 institution in 1 country.

Giulia ChemiEuropean Research Centre for Drug Discovery (NatSynDrugs), University of SienaSiena, Italy.
Sandra GemmaEuropean Research Centre for Drug Discovery (NatSynDrugs), University of SienaSiena, Italy.
Giuseppe CampianiEuropean Research Centre for Drug Discovery (NatSynDrugs), University of SienaSiena, Italy.
Simone BrogiEuropean Research Centre for Drug Discovery (NatSynDrugs), University of SienaSiena, Italy.
Stefania ButiniEuropean Research Centre for Drug Discovery (NatSynDrugs), University of SienaSiena, Italy.
Margherita BrindisiEuropean Research Centre for Drug Discovery (NatSynDrugs), University of SienaSiena, Italy.
University of Siena · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of a novel comprehensive approach for the prediction of

Indexed as

3D-QSARcardiotoxicityhuman Ether-à-go-go-related gene (hERG)ligand-based modelpharmacophore modeling

Identifiers

PMID28503546
PMCPMC5408157
OpenAlexW2588652753

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.