GNN-FTuckER: A novel link prediction model for identifying suitable populations for tea varieties.
Current research on tea primarily focuses on foundational studies of phenotypic characteristics, with insufficient exploration of the relationship between tea varieties and suitable populations. To address this issue, this paper proposes a link prediction model based on Graph Neural Networks (GNN) a...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0323315 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Search Result 1
GNN-FTuckER: A novel link prediction model for identifying suitable populations for tea varieties
Published 2025-01-01
Get full text
Article