Author

Qianqian Chen

BGI ResearchORCID 0000-0001-9042-3098Unclaimed 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· 3 Research Focus:gene regulatory network inference· 3 Organism:human· 3 Approach:benchmark study· 2 Research Focus:benchmarking· 2 Assay:ChIP-seq· 2 Research Focus:clustering· 2 Assay:scRNA-seq· 2

Frequent Co-Authors

Hua QiniD· 2 shared Luni Hu· 2 shared Shuangsang FangiD· 2 shared Tianyi XiaiD· 2 shared Yong ZhangiD· 2 shared Yuxiang LiiD· 2 shared Zhaowei YuiD· 2 shared Chenfei WangiD· 1 shared

Activity by Year

2025-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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2 shared papersBioinformatics

Hua QinORCID

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Author profile →

4 papers

Recent·Most cited

RegFormer: A Single-Cell Foundation Model Powered by Gene Regulatory Hierarchies

Luni Hu, Hua Qin, Yong Zhang, Yi Lu, Ping Qiu, Zhihan Guo, Lei Cao, Wenjian Jiang, Qianqian Chen, Qianqian Chen, Yanbang Shang, Tianyi Xia, Ziqing Deng, Xun Xu, Hansheng Zhao, , Yuxiang Li

RegFormer improves single-cell RNA sequencing analysis by integrating gene regulatory networks with Mamba-based modeling, outperforming existing models in clustering, integration, and annotation.

Nature Communications · May 5, 2026Peer-reviewedBioinformatics

ChromBERT-tools: A versatile toolkit for context-specific embedding of transcription regulators across different cell types

Qianqian Chen, Zhaowei Yu, Yong Zhang

ChromBERT-tools generates context-specific embeddings of transcription regulators for different cell types to enhance regulatory modeling and interpretation.

bioRxiv · Feb 6, 2026 · PreprintBioinformatics

BioLLM: A Standardized Framework for Integrating and Benchmarking Single-Cell Foundation Models

Ping Sun Qiu, Qianqian Chen, Hua Qin, Shuangsang Fang, Yilin Zhang, Yanlin Zhang, Tianyi Xia, Lei Cao, Yong Zhang, Xiaodong Fang, Yuxiang Li, Luni Hu

BioLLM integrates and benchmarks single-cell foundation models, revealing scGPTs' robust performance and highlighting limitations of scBERT in gene-level tasks.

Patterns · Jul 30, 2025Peer-reviewedBioinformatics

Learning interpretable representation for context-specific transcription regulatory networks using a foundation model

Zhaowei Yu, Dongxu Yang, Qianqian Chen, Yuxuan Zhang, Zhenkun Li, Yucheng Wang, Chenfei Wang, Yong Zhang

ChromBERT, a foundation model pre-trained on ChIP-seq data, generates interpretable representations of context-specific transcription regulatory networks and improves imputation and modeling of regulatory effects in cell types.

bioRxiv · Mar 29, 2025 · PreprintBioinformatics