ArticleNPJ systems biology and applications2024
Crop-GPA: an integrated platform of crop gene-phenotype associations.
Article in NPJ systems biology and applications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- RGPA-GCN: Graph convolutional networks for rice gene-phenotype association prediction.Plant biology (Stuttgart, Germany) · 2026Article
- Genomics-assisted breeding for designing salinity-smart future crops.Plant biotechnology journal · 2025Review
- Big data and artificial intelligence-aided crop breeding: Progress and prospects.Journal of integrative plant biology · 2025Review
- Innovative opportunities for gene editing technology in crop breeding: from the perspective of literature analysis.Frontiers in plant science · 2025Article
- RiceSNP-ABST: a deep learning approach to identify abiotic stress-associated single nucleotide polymorphisms in rice.Briefings in bioinformatics · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
With the increasing availability of large-scale biology data in crop plants, there is an urgent demand for a versatile platform that fully mines and utilizes the data for modern molecular breeding. We present Crop-GPA ( https://crop-gpa.aielab.net ), a comprehensive and functional open-source platform for crop gene-phenotype association data. The current Crop-GPA provides well-curated information on genes, phenotypes, and their associations (GPAs) to researchers through an intuitive interface, dynamic graphical visualizations, and efficient online tools. Two computational tools, GPA-BERT and GPA-GCN, are specifically developed and integrated into Crop-GPA, facilitating the automatic extraction of gene-phenotype associations from bio-crop literature and predicting unknown relations based on known associations. Through usage examples, we demonstrate how our platform enables the exploration of complex correlations between genes and phenotypes in crop plants. In summary, Crop-GPA serves as a valuable multi-functional resource, empowering the crop research community to gain deeper insights into the biological mechanisms of interest.
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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.