ArticleFrontiers in plant science2024
A new model construction based on the knowledge graph for mining elite polyphenotype genes in crops.
Article in Frontiers in plant science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- From knowledge graph to topological data analysis: a novel framework to analyze gene regulatory networks for tomato-multi-pathogen interactions.The New phytologist · 2026Article
- Cross-residual knowledge graph learning for robust multi-trait gene-trait prioritization in rice.Frontiers in plant science · 2026Article
- The Use of AI for Phenotype-Genotype Mapping.Methods in molecular biology (Clifton, N.J.) · 2025Article
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Authors and funding
5 authors.
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Abstract
Identifying polyphenotype genes that simultaneously regulate important agronomic traits (e.g., plant height, yield, and disease resistance) is critical for developing novel high-quality crop varieties. Predicting the associations between genes and traits requires the organization and analysis of multi-dimensional scientific data. The existing methods for establishing the relationships between genomic data and phenotypic data can only elucidate the associations between genes and individual traits. However, there are relatively few methods for detecting elite polyphenotype genes. In this study, a knowledge graph for traits regulating-genes was constructed by collecting data from the PubMed database and eight other databases related to the staple food crops rice, maize, and wheat as well as the model plant
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