Author

Junwei Liu

Guangzhou LaboratoryORCID 0000-0001-8446-4221Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 4 Assay:scRNA-seq· 4 Research Focus:gene regulatory network inference· 3 Organism:human· 3 Research Focus:cell type annotation· 2 Research Focus:differential expression· 2 Research Focus:batch correction / integration· 1 Research Focus:benchmarking· 1

Frequent Co-Authors

Yixue LiiD· 4 shared Chenxin YiiD· 3 shared Feng‐ao WangiD· 2 shared Jiajun CheniD· 2 shared Jinyu ChengiD· 2 shared Ruikun HeiD· 2 shared Jiajun CheniD· 1 shared Junxiang DingiD· 1 shared

Activity by Year

2025-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 28 mutual co-author links

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4 shared papersBioinformatics

Yixue LiORCID

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4 papers

Recent·Most cited

TSTScope Unifies Single-Cell Multi-Omics to Identify Functional T Cell States Predictive of Immunotherapy Response

Shiwei Cao, Jinyu Cheng, Feng‐ao Wang, Chenxin Yi, Jiajun Chen, Keyue Wang, Lulu Liu, Junwei Liu, Yixue Li

TSTScope integrates single-cell transcriptomics and T-cell receptor data to identify functional T cell states predictive of immunotherapy response, finding that functional state, not abundance, determines treatment outcomes.

Advanced Science · Aug 5, 2026Peer-reviewedBioinformatics

Exploring phenotype-related single-cells through attention-enhanced representation learning

Qinhua Wu, Junxiang Ding, Ruikun He, Lijian Hui, Junwei Liu, Yixue Li

This study introduces a method to predict clinical phenotypes from single-cell data using attention-based multiple instance learning, demonstrating its effectiveness in predicting disease severity and age-related phenotypes.

Genome Medicine · Jan 21, 2026Peer-reviewedBioinformatics

Benchmarking deep learning methods for biologically conserved single-cell integration

Chenxin Yi, Jinyu Cheng, Jiajun Chen, Wanquan Liu, Junwei Liu, Yixue Li

This study benchmarks deep learning methods for single-cell RNA sequencing integration, identifies limitations in existing metrics, and proposes improvements to better preserve biological signals.

Genome biology · Nov 20, 2025Peer-reviewedBioinformatics

scTFBridge: A Disentangled Deep Generative Model Informed by TF-Motif Binding for Gene Regulation Inference in Single-Cell Multi-Omics

Feng‐ao Wang, Chenxin Yi, Jiajun Chen, Ruikun He, Junwei Liu, Yixue Li

scTFBridge infers gene regulatory networks from single-cell multi-omics data by integrating TF-motif binding knowledge, outperforming baselines in cis- and trans-regulation tasks.

Nature Communications · Oct 15, 2025Peer-reviewedBioinformatics