Author

Pingyuan Xie

Hunan Normal UniversityORCID 0000-0002-0865-9526Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetics· 2 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Research Focus:differential expression· 1 Approach:experimental assay· 1 Research Focus:GWAS / association mapping· 1 Assay:long-read sequencing· 1 Approach:machine learning (classical)· 1 Assay:metabolomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Ge LiniD· 3 shared Bin YaniD· 1 shared Fei GongiD· 1 shared Feitai Tang· 1 shared Hebatallah Ibrahim· 1 shared Hongwei Chu· 1 shared Huimin Gan· 1 shared Jianliang LuiD· 1 shared

Activity by Year

2020-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 22 mutual co-author links

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3 shared papersGenetics

Ge LinORCID

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3 papers

Recent·Most cited

Non-Invasive Embryo Quality Assessment via Matrix-Optimized Untargeted LC-MS Metabolomics of Spent Embryo Culture Media and Weighted Ensemble Machine Learning

Huimin Gan, Xingyao Wang, Feitai Tang, Hebatallah Ibrahim, Xuanyu Chen, Pingyuan Xie, Shuoping Zhang, Ge Lin, Jun Zeng, Hongwei Chu, Shen Zhang

This paper develops a non-invasive method for embryo quality assessment using metabolomics of spent culture media and machine learning, identifying metabolic signatures linked to ploidy and morphology.

bioRxiv · Aug 4, 2026 · PreprintGenetics

Ultra-low coverage genome-wide association study - insights into gestational age using 17,844 embryo samples with preimplantation genetic testing

Shumin Li, Bin Yan, Thomas K. T. Li, Jianliang Lu, Yifan Gu, Yue‐Qiu Tan, Fei Gong, Tak‐Wah Lam, Pingyuan Xie, Yuexuan Wang, Ge Lin, Ruibang Luo

This study uses ultra-low coverage whole genome sequencing on embryo samples to perform GWAS and identifies genetic loci associated with gestational age.

Genome Medicine · Feb 14, 2023Peer-reviewedGenetic & Genomic Medicine

Accurate CNV identification from only a few cells with low GC bias in a single-molecule sequencing platform

Liang Hu, Qunting Lin, Pingyuan Xie, Lidong Zeng, Lichun Liu, Mengxian Huang, Qin Yan, Meng Zhang, Ge Lin

The paper presents a method to accurately identify CNVs and mosaicism from few cells with low GC bias using a single-molecule sequencing platform.

bioRxiv · Jan 21, 2020 · PreprintGenetics