ArticleNature2025
Supervised learning in DNA neural networks.
Article in Nature, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed.
- GenAI-Net: A generative AI framework for automated biomolecular network design.Science advances · 2026Article
- Programmable DNA Logic Systems for Applications in Biomedicine.Chemistry (Weinheim an der Bergstrasse, Germany) · 2026Review
- Advances and challenges in non-canonical nucleic acids data storage.Nature communications · 2026Review
- DNA Circuits That Learn: Biochemical Signal Processing for Personalized Diagnosis and Treatment.MedComm · 2026Article
- Trainable computation in molecular networks.bioRxiv : the preprint server for biology · 2025Article
- Supervised learning in DNA neural networks.Nature · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Learning enables biological organisms to begin life simple yet develop immensely diverse and complex behaviours. Understanding learning principles in engineered molecular systems could enable us to endow non-living physical systems with similar capabilities. Inspired by how the brain processes information, the principles of neural computation have been developed over the past 80 years
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.