Author

Kailun Bai

University of VictoriaORCID 0009-0002-4996-8875Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Approach:machine learning (classical)· 2 Assay:scRNA-seq· 2 Organism:human· 1

Frequent Co-Authors

Xuekui ZhangiD· 2 shared Belaid MoaiD· 1 shared Danielle Tsao· 1 shared Don D. SiniD· 1 shared Firoozeh V. GerayeliiD· 1 shared Janice M. LeungiD· 1 shared Li XingiD· 1 shared Min TsaoiD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersGenomics

Xuekui ZhangORCID

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2 papers

Recent·Most cited

GenomicsbioRxivPreprintJan 9, 2026

A standardized atlas of human bronchoalveolar lavage cells built using scalable ensemble annotation and cross-study robust markers

Yushan Hu, Ziying Liu, Kailun Bai…·Xuekui Zhang

The paper constructs a standardized BAL scRNA-seq atlas using BAL-EA, a novel annotation framework, revealing disease-associated shifts in COPD and validating findings in COVID-19 datasets.

1 citation

𝕏 PostBluesky

BioinformaticsBioinformatics AdvancesPeer-reviewedJan 1, 2023

scAnnotate: an automated cell type annotation tool for single-cell RNA-sequencing data

Xiangling Ji, Danielle Tsao, Kailun Bai…·Xuekui Zhang

scAnnotate is a cell type annotation tool for scRNA-seq data that uses dropout information through a mixture model and ensemble learning, showing competitive performance across multiple datasets.

36 citations

scRNA-seqmachine learning (classical)

𝕏 PostBluesky