Shengquan Chen

Orcid: 0000-0002-3503-9306

According to our database1, Shengquan Chen authored at least 16 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
SCREEN: predicting single-cell gene expression perturbation responses via optimal transport.
Frontiers Comput. Sci., June, 2024

Accurate cell type annotation for single-cell chromatin accessibility data via contrastive learning and reference guidance.
Quant. Biol., 2024

2023
simCAS: an embedding-based method for simulating single-cell chromatin accessibility sequencing data.
Bioinform., August, 2023

ASTER: accurately estimating the number of cell types in single-cell chromatin accessibility data.
Bioinform., January, 2023

RefTM: reference-guided topic modeling of single-cell chromatin accessibility data.
Briefings Bioinform., January, 2023

2022
Cell type annotation of single-cell chromatin accessibility data via supervised Bayesian embedding.
Nat. Mach. Intell., 2022

2021
Simultaneous deep generative modelling and clustering of single-cell genomic data.
Nat. Mach. Intell., 2021

SilencerDB: a comprehensive database of silencers.
Nucleic Acids Res., 2021

OpenAnnotate: a web server to annotate the chromatin accessibility of genomic regions.
Nucleic Acids Res., 2021

DeepCAPE: A Deep Convolutional Neural Network for the Accurate Prediction of Enhancers.
Genom. Proteom. Bioinform., 2021

stPlus: a reference-based method for the accurate enhancement of spatial transcriptomics.
Bioinform., 2021

2020
EnClaSC: a novel ensemble approach for accurate and robust cell-type classification of single-cell transcriptomes.
BMC Bioinform., 2020

Research and Improvement of Community Discovery Algorithm Based on Spark for Large Scale Complicated Networks.
Proceedings of the 19th IEEE International Conference on Trust, 2020

2019
EpiFIT: functional interpretation of transcription factors based on combination of sequence and epigenetic information.
Quant. Biol., 2019

VPAC: Variational projection for accurate clustering of single-cell transcriptomic data.
BMC Bioinform., 2019

2017
Predicting enhancers with deep convolutional neural networks.
BMC Bioinform., 2017


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