Author

Zhenya Liu

Agricultural Genomics Institute at ShenzhenORCID 0000-0002-3487-5070Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Plant Biology· 2 Bioinformatics· 1 Genetics· 1

Signature Assays, Organisms & Methods

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Research Focus:gene regulatory network inference· 3 Approach:statistical model· 3 Organism:virus· 3 Approach:deep learning· 2 Assay:whole-genome sequencing· 2 Research Focus:differential expression· 1 Research Focus:ecology & biodiversity· 1 Research Focus:genome assembly· 1

Frequent Co-Authors

Yongfeng ZhouiD· 4 shared Hui Xue· 2 shared Mengyan ZhangiD· 2 shared Qiming LongiD· 2 shared Wenqi Ma· 2 shared Yu Gan· 2 shared Yuting LiuiD· 2 shared Zhongjie LiuiD· 2 shared

Activity by Year

2024-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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4 shared papersPlant Biology

Yongfeng ZhouORCID

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4 papers

Recent·Most cited

Deep learning based genomic breeding of pest-resistant grapevine

Yu Gan, Zhenya Liu, Fan Zhang, Xu Wang, Xu Wang, Hui Xue, Xiangnian Su, Wenqi Ma, Qiming Long, Anqi Ma, Guizhou Huang, Wenwen Liu, Xiaodong Xu, Lei Sun, Yingchun Zhang, , Yongfeng Zhou

This study uses deep learning and genome-wide association studies to identify pest-resistant genes in grapevine, achieving high accuracy in predicting pest damage.

Horticulture Research · May 7, 2025Peer-reviewedPlant Biology

The dynamics of wild Vitis species in response to climate change facilitate the breeding of grapevine and its rootstocks with climate resilience

Mengyan Zhang, Xiaodong Xu, Tianhao Zhang, Zhenya Liu, Xingyi Wang, Xiaoya Shi, Wenjing Peng, Xu Wang, Zhuyifu Chen, Ruoyan Zhao, Wenrui Wang, Yi Zhang, Zhongxin Jin, Yongfeng Zhou, Zhi‐Yao Ma

This study predicts future climate impacts on grapevine and wild Vitis species using ecological niche models, showing wild species may provide climate-resilient rootstocks for breeding.

Horticulture Research · Apr 10, 2025Peer-reviewedPlant Biology

Deep learning facilitates precise identification of disease-resistance genes in plants

Zhenya Liu, Xu Wang, Shuo Cao, Tingyue Lei, Yifu Chenzhu, Mengyan Zhang, Zhongqi Liu, Jianzhong Lu, Wenqi Ma, Bingxiong Su, Yiwen Wang, Yongfeng Zhou

This study introduces ESM-LRR and R-Predictor to identify disease-resistance genes in plants, achieving high accuracy in annotating R genes and predicting NLR-effector complexes.

bioRxiv · Sep 26, 2024 · PreprintBioinformatics

Integrative genomics reveals the polygenic basis of seedlessness in grapevine

Xu Wang, Zhongjie Liu, Fan Zhang, Hua Xiao, Shuo Cao, Hui Xue, Wénwén Liú, Ying Su, Zhenya Liu, Haixia Zhong, Fuchun Zhang, Bilal Ahmad, Qiming Long, Yingchun Zhang, Yuting Liu, , Yongfeng Zhou

This study identifies the polygenic basis of seedlessness in grapevines using integrative genomics, revealing key genes and a machine learning model with 99% prediction accuracy.

Current Biology · Aug 1, 2024Peer-reviewedGenetics