Evidence map›Paper›PMID 40917333›Full record

ArticleDigital discovery2025

Going beyond SMILES enumeration for data augmentation in generative drug discovery.

Helena Brinkmann, Antoine Argante, Hugo Ter Steege, Francesca Grisoni

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Digital discovery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Helena BrinkmannInstitute for Complex Molecular Systems (ICMS), Eindhoven AI Systems Institute (EAISI), Department of Biomedical Engineering, Eindhoven University of Technology Eindhoven The Netherlands f.grisoni@tue.nl.
Antoine ArganteInstitute for Complex Molecular Systems (ICMS), Eindhoven AI Systems Institute (EAISI), Department of Biomedical Engineering, Eindhoven University of Technology Eindhoven The Netherlands f.grisoni@tue.nl.
Hugo Ter SteegeInstitute for Complex Molecular Systems (ICMS), Eindhoven AI Systems Institute (EAISI), Department of Biomedical Engineering, Eindhoven University of Technology Eindhoven The Netherlands f.grisoni@tue.nl.
Francesca GrisoniInstitute for Complex Molecular Systems (ICMS), Eindhoven AI Systems Institute (EAISI), Department of Biomedical Engineering, Eindhoven University of Technology Eindhoven The Netherlands f.grisoni@tue.nl.ORCID https://orcid.org/0000-0001-8552-6615

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Data augmentation can alleviate the limitations of small molecular datasets for generative deep learning by 'artificially inflating' the number of instances available for training. SMILES enumeration - wherein multiple valid SMILES strings are used to represent the same molecules - has become particularly beneficial to improve the quality of

Identifiers

PMID40917333
PMCPMC12409607

What OpenQuestion holds

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LicenceCC BY
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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.