Deep learning reveals ecological decoupling and rate heterogeneity in Hymenoptera wing evolution.

Peng A, Guan S, Albera L, Le Bouquin Jeannès R, Shu H, Boderau M, Nel A, Wang B, Jouault C, Legendre F

DOI: 10.1126/sciadv.aef0605
Published: 2026 Oct 16
Container: Science advances
Publisher: Not recorded
Open access: yes

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BibTeX

@article{allodium:10.1126/sciadv.aef0605,
  title = {Deep learning reveals ecological decoupling and rate heterogeneity in Hymenoptera wing evolution.},
  author = {Peng A and Guan S and Albera L and Le Bouquin Jeannès R and Shu H and Boderau M and Nel A and Wang B and Jouault C and Legendre F},
  year = {2026},
  journal = {Science advances},
  doi = {10.1126/sciadv.aef0605},
  url = {https://doi.org/10.1126/sciadv.aef0605}
}

RIS

TY  - JOUR
TI  - Deep learning reveals ecological decoupling and rate heterogeneity in Hymenoptera wing evolution.
AU  - Peng A
AU  - Guan S
AU  - Albera L
AU  - Le Bouquin Jeannès R
AU  - Shu H
AU  - Boderau M
AU  - Nel A
AU  - Wang B
AU  - Jouault C
AU  - Legendre F
PY  - 2026
JO  - Science advances
DO  - 10.1126/sciadv.aef0605
UR  - https://doi.org/10.1126/sciadv.aef0605
ER  -

APA

A, P., S, G., L, A., R, L. B. J., H, S., M, B., A, N., B, W., C, J., & F, L. (2026). Deep learning reveals ecological decoupling and rate heterogeneity in Hymenoptera wing evolution.. Science advances. https://doi.org/10.1126/sciadv.aef0605

Source records

pubmed · retrieved 2026-11-10T10:53:02.754Z