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Zhenlan Liang
Institution:
Changsha University
Observed institutions:
Central South University,
Changsha University
ORCID:
0000-0001-6556-071X
Observed ORCID:
0000-0001-6556-071X
OpenAlex ID:
A5032008468
SinNLRR: a robust subspace clustering method for cell type detection by non-negative and low-rank representation
2019
·
Ruiqing Zheng
, Min Li
, et al.
·
Bioinformatics
·
168
SSRE: Cell Type Detection Based on Sparse Subspace Representation and Similarity Enhancement
2021
·
Zhenlan Liang
, Min Li
, et al.
·
Genomics Proteomics & Bioinformatics
·
35
PDF
A data-driven clustering recommendation method for single-cell RNA-sequencing data
2021
·
Yu Tian
, Ruiqing Zheng
, et al.
·
Tsinghua Science & Technology
·
33
PDF
An Adaptive Sparse Subspace Clustering for Cell Type Identification
2020
·
Ruiqing Zheng
, Zhenlan Liang
, et al.
·
Frontiers in Genetics
·
27
PDF
A deep matrix factorization based approach for single-cell RNA-seq data clustering
2022
·
Zhenlan Liang
, Ruiqing Zheng
, et al.
·
Methods
·
5
DeepCI: a deep learning based clustering method for single cell RNA-seq data
2021
·
Zhenlan Liang
, Ruiqing Zheng
, et al.
·
IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
·
5
MKG: a mutual information based method to infer single cell gene regulatory network
2021
·
Yanping Zeng
, Xuhua Yan
, et al.
·
IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
·
3
A robust single cell clustering method based on subspace learning and partial imputation
2020
·
Ruiqing Zheng
, Zhenlan Liang
, et al.
·
IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
·
2
ScCLC: A Flexible Contrastive Learning Framework for Single-cell Multi-omics Data Clustering
2026
·
Zhenlan Liang
, Ruiqing Zheng
, et al.
·
IEEE Transactions on Computational Biology and Bioinformatics
Contrastive Learning-Based Method for Single-Cell Multi-omics Data Clustering
2025
·
Zhenlan Liang
, Ruiqing Zheng
, et al.
·
Lecture notes in computer science
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Works count:
10
Citation count:
278
H-index:
5
I10-index:
4
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