Integrative machine learning and gene regulatory network analysis identifies novel genes for leafy head formation in Brassica rapa and B. oleracea
Wei Sun, Jian Wu, Xu Cai, Yue Chen, Aalt D. J. van Dijk, Xiaowu Wang, Guusje Bonnema · 2026
Read Integrative machine learning and gene regulatory network analysis identifies novel genes for leafy head formation in Brassica rapa and B. oleracea by Wei Sun, Jian Wu, Xu Cai, Yue Chen, Aalt D. J. van Dijk, Xiaowu Wang, Guusje Bonnema (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13244942.txt.
Description
Wei Sun and colleagues used machine learning to hunt the genes that make cabbages fold their leaves into a head. Their study appeared in Molecular Horticulture in 2026. Heading is the defining trait of Chinese cabbage and cabbage, and its gene list is still incomplete. A random forest model was trained on forty-seven known heading genes. It was then set loose on both species' genomes, with gene networks built alongside to show how candidates connect.
The models scored with high accuracy in both crops. Filtering their predictions left eleven genes flagged with high confidence in both species, a cross-check that strengthens belief in them. Network analysis grouped the genes into clusters whose hubs include known growth regulators such as ANT and the GRF factors. The same genes and similar wiring in two species support the approach. Breeders gain a shortlist for heading experiments.
Catalog record
| CREATOR | Wei Sun, Jian Wu, Xu Cai, Yue Chen, Aalt D. J. van Dijk, Xiaowu Wang, Guusje Bonnema |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 59 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |