Peer-reviewedCC BYScience advances
Deep learning reveals ecological decoupling and rate heterogeneity in Hymenoptera wing evolution
6 affiliations
- 1Institut de Systématique, Évolution, Biodiversité (UMR 7205), Muséum national d’Histoire naturelle, CNRS, SU, EPHE-PSL, UA, Paris F-75005, France.
- 2State Key Laboratory of Palaeobiology and Stratigraphy, Nanjing Institute of Geology and Palaeontology, Chinese Academy of Sciences, Nanjing 210008, China.
- 3Laboratory of Image Science and Technology (LIST), School of Computer Science and Engineering, Southeast University, Nanjing 210096, China.
- 4Centre de Recherche en Information Biomédicale Sino-français (CRIBs), Inserm, Rennes F-35000, France.
- 5Univ Rennes, Laboratoire Traitement du Signal et de l’Image (LTSI), UMR 1099, Rennes F-35000, France.
- 6Oxford University Museum of Natural History, University of Oxford, Oxford OX1 3PW, UK.
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BibTeX
@article{peng2026deep,
title = {{Deep learning reveals ecological decoupling and rate heterogeneity in Hymenoptera wing evolution}},
author = {Ancheng Peng and Shihan Guan and Laurent Albera and Régine Le Bouquin Jeannès and Huazhong Shu and Mathieu Boderau and André Nel and Bo Wang and Corentin Jouault and Frédéric Legendre},
journal = {Science advances},
year = {2026},
month = oct,
doi = {10.1126/sciadv.aef0605},
url = {https://europepmc.org/article/PMC/PMC13665928},
note = {CC BY},
}
RIS
TY - JOUR
TI - Deep learning reveals ecological decoupling and rate heterogeneity in Hymenoptera wing evolution
AU - Ancheng Peng
AU - Shihan Guan
AU - Laurent Albera
AU - Régine Le Bouquin Jeannès
AU - Huazhong Shu
AU - Mathieu Boderau
AU - André Nel
AU - Bo Wang
AU - Corentin Jouault
AU - Frédéric Legendre
PY - 2026
DA - 2026/10/16
JO - Science advances
DO - 10.1126/sciadv.aef0605
UR - https://europepmc.org/article/PMC/PMC13665928
SN - 2375-2548
ER -