Research progress of single-cell transcriptome sequencing in autoimmune diseases and autoinflammatory disease: A review

L Zeng, K Yang, T Zhang, X Zhu, W Hao, H Chen… - Journal of …, 2022 - Elsevier
Autoimmunity refers to the phenomenon that the body's immune system produces antibodies
or sensitized lymphocytes to its own tissues to cause an immune response. Immune …

Network-based structural learning nonnegative matrix factorization algorithm for clustering of scRNA-seq data

W Wu, X Ma - IEEE/ACM transactions on computational biology …, 2022 - ieeexplore.ieee.org
Single-cell RNA sequencing (scRNA-seq) measures expression profiles at the single-cell
level, which sheds light on revealing the heterogeneity and functional diversity among cell …

Artificial intelligence in bulk and single-cell RNA-sequencing data to foster precision oncology

M Del Giudice, S Peirone, S Perrone, F Priante… - International journal of …, 2021 - mdpi.com
Artificial intelligence, or the discipline of developing computational algorithms able to
perform tasks that requires human intelligence, offers the opportunity to improve our idea …

SSNMDI: a novel joint learning model of semi-supervised non-negative matrix factorization and data imputation for clustering of single-cell RNA-seq data

Y Qiu, C Yan, P Zhao, Q Zou - Briefings in bioinformatics, 2023 - academic.oup.com
Motivation Single-cell RNA sequencing (scRNA-seq) technology attracts extensive attention
in the biomedical field. It can be used to measure gene expression and analyze the …

A hypergraph-based framework for personalized recommendations via user preference and dynamics clustering

Z Wang, J Chen, FE Rosas, T Zhu - Expert Systems with Applications, 2022 - Elsevier
The ever-increasing number of users and items continuously imposes new challenges to
existent clustering-based recommendation algorithms. To better simulate the interactions …

Dimension reduction, cell clustering, and cell–cell communication inference for single-cell transcriptomics with DcjComm

Q Ding, W Yang, G Xue, H Liu, Y Cai, J Que, X Jin… - Genome Biology, 2024 - Springer
Advances in single-cell transcriptomics provide an unprecedented opportunity to explore
complex biological processes. However, computational methods for analyzing single-cell …

jSRC: a flexible and accurate joint learning algorithm for clustering of single-cell RNA-sequencing data

W Wu, Z Liu, X Ma - Briefings in bioinformatics, 2021 - academic.oup.com
Single-cell RNA-sequencing (scRNA-seq) explores the transcriptome of genes at cell level,
which sheds light on revealing the heterogeneity and dynamics of cell populations …

Learning deep features and topological structure of cells for clustering of scRNA-sequencing data

H Wang, X Ma - Briefings in Bioinformatics, 2022 - academic.oup.com
Single-cell RNA sequencing (scRNA-seq) measures gene transcriptome at the cell level,
paving the way for the identification of cell subpopulations. Although deep learning has …

Multi-view clustering with graph learning for scRNA-Seq data

W Wu, W Zhang, W Hou, X Ma - IEEE/ACM Transactions on …, 2023 - ieeexplore.ieee.org
Advances in single-cell biotechnologies have generated the single-cell RNA sequencing
(scRNA-seq) of gene expression profiles at cell levels, providing an opportunity to study …

A game-based evolutionary clustering with historical information aggregation for personal recommendation

J Chen, T Zhu, M Gong, Z Wang - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In order to alleviate the network information overload, recommender system becomes
widespread in personalized recommendation. However, due to the increase of the number …