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Shengquan Chen
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2020 – today
- 2024
- [j17]Haixin Wang, Yunhan Wang, Qun Jiang, Yan Zhang, Shengquan Chen:
SCREEN: predicting single-cell gene expression perturbation responses via optimal transport. Frontiers Comput. Sci. 18(3): 183909 (2024) - [j16]Xuejian Cui
, Xiaoyang Chen
Discrete latent embedding of single-cell chromatin accessibility sequencing data for uncovering cell heterogeneity. Nat. Comput. Sci. 4(5): 346-359 (2024) - [j15]Siyu Li, Songming Tang, Yunchang Wang, Sijie Li, Yuhang Jia, Shengquan Chen:
Accurate cell type annotation for single-cell chromatin accessibility data via contrastive learning and reference guidance. Quant. Biol. 12(1): 85-99 (2024) - [j14]Yuhang Jia
Accurate Annotation for Differentiating and Imbalanced Cell Types in Single-Cell Chromatin Accessibility Data. IEEE ACM Trans. Comput. Biol. Bioinform. 21(3): 461-471 (2024) - [i1]Yuxi Li, Yi Liu, Yuekang Li
Lockpicking LLMs: A Logit-Based Jailbreak Using Token-level Manipulation. CoRR abs/2405.13068 (2024) - 2023
- [j13]Zheng Zhang
RefTM: reference-guided topic modeling of single-cell chromatin accessibility data. Briefings Bioinform. 24(1) (2023) - [j12]Shengquan Chen
ASTER: accurately estimating the number of cell types in single-cell chromatin accessibility data. Bioinform. 39(1) (2023) - [j11]Chen Li, Xiaoyang Chen, Shengquan Chen
simCAS: an embedding-based method for simulating single-cell chromatin accessibility sequencing data. Bioinform. 39(8) (2023) - 2022
- [j10]Xiaoyang Chen
Cell type annotation of single-cell chromatin accessibility data via supervised Bayesian embedding. Nat. Mach. Intell. 4(2): 116-126 (2022) - 2021
- [j9]Shengquan Chen
stPlus: a reference-based method for the accurate enhancement of spatial transcriptomics. Bioinform. 37(Supplement): 299-307 (2021) - [j8]Shengquan Chen
DeepCAPE: A Deep Convolutional Neural Network for the Accurate Prediction of Enhancers. Genom. Proteom. Bioinform. 19(4): 565-577 (2021) - [j7]Wanwen Zeng
SilencerDB: a comprehensive database of silencers. Nucleic Acids Res. 49(Database-Issue): D221-D228 (2021) - [j6]Shengquan Chen
OpenAnnotate: a web server to annotate the chromatin accessibility of genomic regions. Nucleic Acids Res. 49(Webserver-Issue): 483-490 (2021) - [j5]Qiao Liu
Simultaneous deep generative modelling and clustering of single-cell genomic data. Nat. Mach. Intell. 3(6): 536-544 (2021) - 2020
- [j4]Xiaoyang Chen, Shengquan Chen, Rui Jiang:
EnClaSC: a novel ensemble approach for accurate and robust cell-type classification of single-cell transcriptomes. BMC Bioinform. 21-S(13): 392 (2020) - [c1]Hui Kang, Shengquan Chen, Lingfeng Lu, Chenkun Meng:
Research and Improvement of Community Discovery Algorithm Based on Spark for Large Scale Complicated Networks. TrustCom 2020: 1499-1508
2010 – 2019
- 2019
- [j3]Shengquan Chen, Kui Hua, Hongfei Cui, Rui Jiang:
VPAC: Variational projection for accurate clustering of single-cell transcriptomic data. BMC Bioinform. 20-S(7): 139-151 (2019) - [j2]Shaoming Song, Hongfei Cui, Shengquan Chen, Qiao Liu, Rui Jiang:
EpiFIT: functional interpretation of transcription factors based on combination of sequence and epigenetic information. Quant. Biol. 7(3): 233-243 (2019) - 2017
- [j1]Xu Min, Wanwen Zeng
Predicting enhancers with deep convolutional neural networks. BMC Bioinform. 18(S-13): 35-46 (2017)
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