GViT-GP: injecting the genomic relationship matrix as an inductive bias into a vision transformer via cross-attention for genomic prediction

These results indicate that injecting GRM-informed inductive bias improves robustness and generalization in "p ≫ n" settings. GViT-GP provides a practical, high-performance framework for capturing complex genotype-phenotype relationships in modern digital breeding.

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Publication Details

Journal
Frontiers in Genetics
Published
2026-03-08
DOI
https://doi.org/10.3389/fgene.2026.1758565
Primary Topic
Genetic and phenotypic traits in livestock
Type
article
Field-Weighted Citation Impact
0.00

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article

GViT-GP: injecting the genomic relationship matrix as an inductive bias into a vision transformer via cross-attention for genomic prediction

S. Li, Jisi Ma, Xishi Huang, Lantao Gu et al.
Frontiers in Genetics
Genetic and phenotypic traits in livestock
article

GViT-GP: injecting the genomic relationship matrix as an inductive bias into a vision transformer via cross-attention for genomic prediction

S. Li, Jisi Ma, Xishi Huang, Lantao Gu, Jingxuan Li, Wei Luo, Honghao Yu, Yong Li
article en

Abstract

These results indicate that injecting GRM-informed inductive bias improves robustness and generalization in "p ≫ n" settings. GViT-GP provides a practical, high-performance framework for capturing complex genotype-phenotype relationships in modern digital breeding.

Frontiers in GeneticsVol. 17
Huazhong Agricultural University (CN), Artificial Intelligence in Medicine (Canada) (CA)
National Natural Science Foundation of China, Natural Science Foundation of Guangxi Province, Guangxi University
Openalex Percentile: Top 29%
Genetic and phenotypic traits in livestock
DOIOpen Access PDFOpenAlex
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