Author

X.Z. Lv

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Genomics· 1

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Approach:machine learning (classical)· 1 Research Focus:variant calling· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Ali Mujtaba ShahiD· 1 shared Ao WangiD· 1 shared G.L. Liu· 1 shared Hojjat Asadollahpour NanaeiiD· 1 shared Honghong HuiD· 1 shared K. Zhu· 1 shared L.L. Wang· 1 shared Qiyan Wang· 1 shared

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2026-2026 · peak 1/yr

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1 shared paperGenomics

Ali Mujtaba ShahORCID

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1 paper

Recent·Most cited

Cost-effective genomic prediction for fertility traits: A comparison of machine learning and conventional models using low-coverage sequencing in Holstein heifers

Zhuangbiao Zhang, Ao Wang, Qiyan Wang, S.Q. Gao, L.L. Wang, Honghong Hu, Hojjat Asadollahpour Nanaei, Ali Mujtaba Shah, G.L. Liu, K. Zhu, X.Z. Lv, R. Li, Yu Yan Jiang

This study compares machine learning and conventional models for genomic prediction of fertility traits in Holstein heifers using low-coverage sequencing data, finding that KRR_GRM improves accuracy over traditional methods when using only genomic data.

animal · Apr 24, 2026Peer-reviewedGenomics