Author

Ming Ni

MGI

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Same name, identified by ORCID

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Assay:scRNA-seq· 1 Approach:statistical model· 1 Research Focus:variant calling· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Andrew W. CarrolliD· 1 shared Heng YiiD· 1 shared Hui CheniD· 1 shared Jiahui Hu· 1 shared Kane TohiD· 1 shared Kishwar ShafiniD· 1 shared Liang Wu· 1 shared Lingyun XuiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperBioinformatics

Andrew W. CarrollORCID

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2 papers

Recent·Most cited

PanVariants: Best Practice for Pangenome-based Variant Calling Pipeline and Framework

Heng Yi, Linqi Wang, Xinrui Chen, Yi Ding, Andrew W. Carroll, Pi-Chuan Chang, Kishwar Shafin, Lingyun Xu, Xiaojie Zeng, Xia Zhao, Meihua Gong, Xiaofang Wei, Yong Hou, Ming Ni

PanVariants improves variant calling by integrating k-mer and mapping methods, reducing errors and outperforming existing tools for SNVs, indels, and SVs.

bioRxiv · May 17, 2026 · PreprintBioinformatics

Viral Infection Detector: Ensemble Learning for Predicting Viral Infection in Single-cell Transcriptomics of Virus-Induced Cancers

Wenhao Han, Jiahui Hu, Kane Toh, Ming Ni, Roy Tan, Liang Wu, Xin Jin, Min Jian, Miao Xu, Hui Chen

The paper develops VID, an ensemble machine learning model to predict virus-infected cells in scRNA-seq data, revealing biological differences between infected and uninfected cells in virus-induced cancers.

bioRxiv · Feb 27, 2025 · PreprintBioinformatics