ArticleNucleic acids research2024
CropGS-Hub: a comprehensive database of genotype and phenotype resources for genomic prediction in major crops.
Article in Nucleic acids research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- GWAS meta-analysis using a graph-based pan-genome enhanced gene mining efficiency for agronomic traits in rice.Nature communications · 2025Pooled it
- Transposable element-driven expansion of enhancer RNA repertoires underlies regulatory innovation and polyploid adaptation in cereal crops.Plant communications · 2026Article
- Robustly enhancing crop genomic prediction accuracy through ensemble learning and iterative optimization.Nature communications · 2026Article
- Challenges in Bringing Pangenome Research Into Breeding: A Case Study in Rice.Plant biotechnology journal · 2026Review
- A benchmarking of genomic selection models for predicting grain-yield related traits using haplotype-based and genome-wide association study-based markers in rice.The plant genome · 2026Article
- G2P datasets: a hub for genomic datasets for predictive modeling in plants and animals.G3 (Bethesda, Md.) · 2026Article
- CLCNet: a contrastive learning and chromosome-aware network for genomic prediction in plants.Briefings in bioinformatics · 2026Article
- The SynMall resource for characterizing the functional impact of synonymous variation.Genome research · 2026Article
- Statistics and data science unlock the predictive power of quantitative genetics.Frontiers in plant science · 2026Review
- Article
- HaploVar: An R package for defining local haplotype variants for trait association and trait prediction analyses.Bioinformatics (Oxford, England) · 2025Article
- Order from entropy: big data from FAIR data cohorts in the digital age of plant breeding.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Review
- Genomics-assisted breeding for designing salinity-smart future crops.Plant biotechnology journal · 2025Review
- AutoGP: An intelligent breeding platform for enhancing maize genomic selection.Plant communications · 2025Article
- Article
- WheatGP, a genomic prediction method based on CNN and LSTM.Briefings in bioinformatics · 2025Article
- Big data and artificial intelligence-aided crop breeding: Progress and prospects.Journal of integrative plant biology · 2025Review
- PidTools: Algorithm and web tools for crop pedigree identification analysis.Computational and structural biotechnology journal · 2024Article
- Unlocking the mystery of heterosis opens the era of intelligent rice breeding.Plant physiology · 2024Review
- Dual-extraction modeling: A multi-modal deep-learning architecture for phenotypic prediction and functional gene mining of complex traits.Plant communications · 2024Article
Corrections and comments
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14 authors.
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Abstract
The explosive amount of multi-omics data has brought a paradigm shift both in academic research and further application in life science. However, managing and reusing the growing resources of genomic and phenotype data points presents considerable challenges for the research community. There is an urgent need for an integrated database that combines genome-wide association studies (GWAS) with genomic selection (GS). Here, we present CropGS-Hub, a comprehensive database comprising genotype, phenotype, and GWAS signals, as well as a one-stop platform with built-in algorithms for genomic prediction and crossing design. This database encompasses a comprehensive collection of over 224 billion genotype data and 434 thousand phenotype data generated from >30 000 individuals in 14 representative populations belonging to 7 major crop species. Moreover, the platform implemented three complete functional genomic selection related modules including phenotype prediction, user model training and crossing design, as well as a fast SNP genotyper plugin-in called SNPGT specifically built for CropGS-Hub, aiming to assist crop scientists and breeders without necessitating coding skills. CropGS-Hub can be accessed at https://iagr.genomics.cn/CropGS/.
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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 OpenQuestion graph.