陈盛泉｜南开大学｜学者主页

2026

A systematic benchmarking framework and dual-view optimization strategy for single-cell DNA methylation imputation

Hu Liang, Heyang Hua, Siyu Li, Shengquan Chen

Briefings in Bioinformatics

DOI

2026

Cross-modality representation and multi-sample integration of spatially resolved omics data

Zhen Li, Xuejian Cui, Xiaoyang Chen, Zijing Gao, Yuyao Liu, Yan Pan, Shengquan Chen, Hairong Lv, Lei Zhai, Rui Jiang

Briefings in Bioinformatics

DOI

2026

MethyAnno: An Interpretable Automated Annotation Method Leveraging Multi‐Scale Information and Metric Learning Framework for scDNAm Data

Yuhang Jia, Siyu Li, Songming Tang, Keju Gu, Shengquan Chen

Advanced Science

DOI

2026

DECANT prioritizes biological heterogeneity over batch effects for various single-cell omics data

Ziyi Zou, Heyang Hua, Siyu Li, Yuhang Jia, Ning Sun, Shengquan Chen

Zenodo (CERN European Organization for Nuclear Research)

DOI

2026

Dissecting epigenetic heterogeneity in single-cell DNA methylomes with a unified framework

Songming Tang, Siyu Li, Guangxin Zhang, Aoran Lyu, Han Li, Shengquan Chen

Nature Communications

DOI

2026

CSFeatures improves the identification of cell-type-specific differential features in single-cell and spatial omics data

Rufeng Li, Yongkang Li, Heyang Hua, Zhen Li, Hongyu Su, Yu Zhang, Yufei Yao, Yidong Wang, Shengquan Chen, Yungang Xu

Journal of Advanced Research

DOI

2026

A generic reference defined by consensus peaks for single-cell ATAC-seq data analysis

Qiuchen Meng, Xinze Wu, Wenchang Chen, Yubo Zhao, Chen Li, Zheng Wei, Xiaocheng Zeng, Jiaqi Li, Xi Xi, Sijie Chen, Catherine Zhang, Shengquan Chen, Jiaqi Li, Xiaowo Wang, Rui Jiang, Lei Wei, Xuegong Zhang

Nature Communications

DOI

2026

A unified framework combining linear and 3D molecular features for robust drug-protein interaction prediction

Chang Sun, Zichen Qin, Minglei Li, Yanfei Li, Rong Tang, Shengquan Chen, Yuxiang Wang, Yanqiang Liu, Jinmao Wei, Jiayi Liu

Cell Reports Methods

DOI

2026

Comparative evaluation of gene selection approaches in transcriptomics: bias correction and visualization with TransPro

Dongyue Yu, Chen Li, Shuo Yan, Lujiale Guo, Jingyu Liang, Shengquan Chen, Wenjun Bu

GigaScience

DOI

2025

Imputing not available values in single‐cell DNA methylation data using the median is straightforward and effective

Songming Tang, Siyu Li, Shengquan Chen

Quantitative Biology

DOI

2025

CASHeart: A database of single cells chromatin accessibility for the human heart

Qun Jiang, Xiaoyang Chen, Zijing Gao, Jinmeng Jia, Shengquan Chen, Rui Jiang

Quantitative Biology

DOI

2025

Graph neural networks for single-cell omics data: a review of approaches and applications

Sijie Li, Heyang Hua, Shengquan Chen

Briefings in Bioinformatics

DOI

2025

DiTSim: A Diffusion-Transformers Based Single-Cell ATAC-seq Data Simulator

Shengze Dong, Songming Tang, Ding Liu, Shengquan Chen

Interdisciplinary Sciences Computational Life Sciences

DOI

2025

Rigorous integration of single-cell ATAC-seq data using regularized barycentric mapping

Shuchen Zhu, Heyang Hua, Shengquan Chen

Nature Machine Intelligence

DOI

2025

Triple-effect correction for Cell Painting data with contrastive and domain-adversarial learning

Chengwei Yan, Yu Zhang, Jiuxin Feng, Heyang Hua, Zhihan Ruan, Zhen Li, Siyu Li, Chaoyang Yan, Pingjing Li, Jian Liu, Shengquan Chen

Nature Communications

DOI

2025

MethAgingDB: a comprehensive DNA methylation database for aging biology

Siyu Li, Songming Tang, Haocheng Ma, Haixin Wang, Shengquan Chen

Scientific Data

DOI

2025

MINGLE: a mutual information-based interpretable framework for automatic cell type annotation in single-cell chromatin accessibility data

Siyu Li, Yifan Huang, Shengquan Chen

Genome biology

DOI

2025

CREATE: cell-type-specific cis-regulatory element identification via discrete embedding

Xuejian Cui, Qijin Yin, Zijing Gao, Zhen Li, Xiaoyang Chen, Hairong Lv, Shengquan Chen, Qiao Liu, Wanwen Zeng, Rui Jiang

Nature Communications

DOI

2025

Facilitating single-cell chromatin accessibility research with a user-friendly database

Heyang Hua, Sijie Li, Hu Liang, Shengquan Chen

Frontiers of Computer Science

DOI

2024

MultiKano: an automatic cell type annotation tool for single-cell multi-omics data based on Kolmogorov–Arnold network and data augmentation

Siyu Li, Xinhao Zhuang, Songbo Jia, Songming Tang, Liming Yan, Heyang Hua, Yuhang Jia, Xuelin Zhang, Yan Zhang, Qingzhu Yang, Shengquan Chen

Protein & Cell

DOI

2024

Accurate cell type annotation for single‐cell chromatin accessibility data via contrastive learning and reference guidance

Siyu Li, Songming Tang, Yunchang Wang, Sijie Li, Yuhang Jia, Shengquan Chen

Quantitative Biology

DOI

2024

BIOTIC: a Bayesian framework to integrate single-cell multi-omics for transcription factor activity inference and improve identity characterization of cells

Lan Cao, Wenhao Zhang, Fan Yang, Shengquan Chen, Xiaobing Huang, Feng Zeng, Ying Wang

Briefings in Bioinformatics

DOI

2024

GATDE: A graph attention network with diffusion-enhanced protein-protein interaction for cancer classification

Ruike Song, Xiaofeng Wang, Jiahao Zhang, Shengquan Chen, Jianyu Zhou

Methods

DOI

2024

scPRAM accurately predicts single-cell gene expression perturbation response based on attention mechanism

Qun Jiang, Shengquan Chen, Xiaoyang Chen, Rui Jiang

Bioinformatics

DOI

2024

EpiCarousel: memory- and time-efficient identification of metacells for atlas-level single-cell chromatin accessibility data

Sijie Li, Yuxi Li, Yu Sun, Yaru Li, Xiaoyang Chen, Songming Tang, Shengquan Chen

Bioinformatics

DOI

2024

Accurate Annotation for Differentiating and Imbalanced Cell Types in Single-Cell Chromatin Accessibility Data

Yuhang Jia, Siyu Li, Rui Jiang, Shengquan Chen

IEEE Transactions on Computational Biology and Bioinformatics

DOI

2024

OpenAnnotateApi: Python and R packages to efficiently annotate and analyze chromatin accessibility of genomic regions

Zijing Gao, Rui Jiang, Shengquan Chen

Bioinformatics Advances

DOI

2024

Unveiling potential threats: backdoor attacks in single-cell pre-trained models

Sicheng Feng, Siyu Li, Luonan Chen, Shengquan Chen

Cell Discovery

DOI

2024

scCrab: A Reference-Guided Cancer Cell Identification Method based on Bayesian Neural Networks

Heyang Hua, Wenxin Long, Yan Pan, Siyu Li, Jianyu Zhou, Haixin Wang, Shengquan Chen

Interdisciplinary Sciences Computational Life Sciences

DOI

2024

Precise detection of cell-type-specific domains in spatial transcriptomics

Zhihan Ruan, Weijun Zhou, Zhihong Liu, Jinmao Wei, Yichen Pan, Chaoyang Yan, Xiaoyi Wei, Wenting Xiang, Chengwei Yan, Shengquan Chen, Jian Liu

Cell Reports Methods

DOI

2024

Discrete latent embedding of single-cell chromatin accessibility sequencing data for uncovering cell heterogeneity

Xuejian Cui, Xiaoyang Chen, Zhen Li, Zijing Gao, Shengquan Chen, Rui Jiang

Nature Computational Science

DOI

2024

scButterfly: a versatile single-cell cross-modality translation method via dual-aligned variational autoencoders

Yichuan Cao, Xiamiao Zhao, Songming Tang, Qun Jiang, Sijie Li, Siyu Li, Shengquan Chen

Nature Communications

DOI

2024

SCREEN: predicting single-cell gene expression perturbation responses via optimal transport

Haixin Wang, Yunhan Wang, Qun Jiang, Yan Zhang, Shengquan Chen

Frontiers of Computer Science

DOI

2024

Publisher Correction: scCASE: accurate and interpretable enhancement for single-cell chromatin accessibility sequencing data

Songming Tang, Xuejian Cui, Rongxiang Wang, Sijie Li, Siyu Li, Xin Huang, Shengquan Chen

Nature Communications

DOI

2024

scCASE: accurate and interpretable enhancement for single-cell chromatin accessibility sequencing data

Songming Tang, Xuejian Cui, Rongxiang Wang, Sijie Li, Siyu Li, Xin Huang, Shengquan Chen

Nature Communications

DOI

2023

scEpiTools: a database to comprehensively interrogate analytic tools for single-cell epigenomic data

Zijing Gao, Xiaoyang Chen, Zhen Li, Xuejian Cui, Qun Jiang, Keyi Li, Shengquan Chen, Rui Jiang

Journal of genetics and genomics/Journal of Genetics and Genomics

DOI

2023

Cofea: correlation-based feature selection for single-cell chromatin accessibility data

Keyi Li, Xiaoyang Chen, Shuang Song, Lin Hou, Shengquan Chen, Rui Jiang

Briefings in Bioinformatics

DOI

2023

simCAS: an embedding-based method for simulating single-cell chromatin accessibility sequencing data

Chen Li, Xiaoyang Chen, Shengquan Chen, Rui Jiang, Xuegong Zhang

Bioinformatics

DOI

2023

scIBD: a self-supervised iterative-optimizing model for boosting the detection of heterotypic doublets in single-cell chromatin accessibility data

Wenhao Zhang, Rui Jiang, Shengquan Chen, Ying Wang

Genome biology

DOI

2023

scIBD

Wenhao Zhang, Shengquan Chen, Ying Wang, Rui Jiang

Zenodo (CERN European Organization for Nuclear Research)

DOI

2023

SINFONIA: Scalable Identification of Spatially Variable Genes for Deciphering Spatial Domains

Rui Jiang, Zhen Li, Yuhang Jia, Siyu Li, Shengquan Chen

Cells

DOI

2022

ASTER: accurately estimating the number of cell types in single-cell chromatin accessibility data

Shengquan Chen, Rongxiang Wang, Wenxin Long, Rui Jiang

Bioinformatics

DOI

2022

RefTM: reference-guided topic modeling of single-cell chromatin accessibility data

Zheng Zhang, Shengquan Chen, Zhixiang Lin

Briefings in Bioinformatics

DOI

2021

DeepCAPE: A Deep Convolutional Neural Network for the Accurate Prediction of Enhancers

Shengquan Chen, Mingxin Gan, Hairong Lv, Rui Jiang

Genomics,Proteomics & Bioinformatics

2019

EpiFIT: functional interpretation of transcription factors based on combination of sequence and epigenetic information

Shaoming Song, Hongfei Cui, Shengquan Chen, Qiao Liu, Rui Jiang

Quantitative Biology

DOI

精选作品

期刊论文

A systematic benchmarking framework and dual-view optimization strategy for single-cell DNA methylation imputation

Cross-modality representation and multi-sample integration of spatially resolved omics data

MethyAnno: An Interpretable Automated Annotation Method Leveraging Multi‐Scale Information and Metric Learning Framework for scDNAm Data

DECANT prioritizes biological heterogeneity over batch effects for various single-cell omics data

Dissecting epigenetic heterogeneity in single-cell DNA methylomes with a unified framework

CSFeatures improves the identification of cell-type-specific differential features in single-cell and spatial omics data

A generic reference defined by consensus peaks for single-cell ATAC-seq data analysis

A unified framework combining linear and 3D molecular features for robust drug-protein interaction prediction

Comparative evaluation of gene selection approaches in transcriptomics: bias correction and visualization with TransPro

Imputing not available values in single‐cell DNA methylation data using the median is straightforward and effective

CASHeart: A database of single cells chromatin accessibility for the human heart

Graph neural networks for single-cell omics data: a review of approaches and applications

DiTSim: A Diffusion-Transformers Based Single-Cell ATAC-seq Data Simulator

Rigorous integration of single-cell ATAC-seq data using regularized barycentric mapping

Triple-effect correction for Cell Painting data with contrastive and domain-adversarial learning

MethAgingDB: a comprehensive DNA methylation database for aging biology

MINGLE: a mutual information-based interpretable framework for automatic cell type annotation in single-cell chromatin accessibility data

CREATE: cell-type-specific cis-regulatory element identification via discrete embedding

Facilitating single-cell chromatin accessibility research with a user-friendly database

MultiKano: an automatic cell type annotation tool for single-cell multi-omics data based on Kolmogorov–Arnold network and data augmentation

Accurate cell type annotation for single‐cell chromatin accessibility data via contrastive learning and reference guidance

BIOTIC: a Bayesian framework to integrate single-cell multi-omics for transcription factor activity inference and improve identity characterization of cells

GATDE: A graph attention network with diffusion-enhanced protein-protein interaction for cancer classification

scPRAM accurately predicts single-cell gene expression perturbation response based on attention mechanism

EpiCarousel: memory- and time-efficient identification of metacells for atlas-level single-cell chromatin accessibility data

Accurate Annotation for Differentiating and Imbalanced Cell Types in Single-Cell Chromatin Accessibility Data

OpenAnnotateApi: Python and R packages to efficiently annotate and analyze chromatin accessibility of genomic regions

Unveiling potential threats: backdoor attacks in single-cell pre-trained models

scCrab: A Reference-Guided Cancer Cell Identification Method based on Bayesian Neural Networks

Precise detection of cell-type-specific domains in spatial transcriptomics

Discrete latent embedding of single-cell chromatin accessibility sequencing data for uncovering cell heterogeneity

scButterfly: a versatile single-cell cross-modality translation method via dual-aligned variational autoencoders

SCREEN: predicting single-cell gene expression perturbation responses via optimal transport

Publisher Correction: scCASE: accurate and interpretable enhancement for single-cell chromatin accessibility sequencing data

scCASE: accurate and interpretable enhancement for single-cell chromatin accessibility sequencing data

scEpiTools: a database to comprehensively interrogate analytic tools for single-cell epigenomic data

Cofea: correlation-based feature selection for single-cell chromatin accessibility data

simCAS: an embedding-based method for simulating single-cell chromatin accessibility sequencing data

scIBD: a self-supervised iterative-optimizing model for boosting the detection of heterotypic doublets in single-cell chromatin accessibility data

scIBD

SINFONIA: Scalable Identification of Spatially Variable Genes for Deciphering Spatial Domains

ASTER: accurately estimating the number of cell types in single-cell chromatin accessibility data

RefTM: reference-guided topic modeling of single-cell chromatin accessibility data

DeepCAPE: A Deep Convolutional Neural Network for the Accurate Prediction of Enhancers

EpiFIT: functional interpretation of transcription factors based on combination of sequence and epigenetic information

预印本

Robust annotation and discovery of novel cell types in single-cell ATAC-seq data through cross-modal reference alignment

High-fidelity bidirectional translation between single-cell transcriptomes and DNA methylomes with scBOND

A multistage, multitask transformer-based framework for multi-disease diagnosis and prediction using personal proteomes

PAST: latent feature extraction with a Prior-based self-Attention framework for Spatial Transcriptomics

研究方向