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 …
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
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 …
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 …
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
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 …
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
The ever-increasing number of users and items continuously imposes new challenges to
existent clustering-based recommendation algorithms. To better simulate the interactions …
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 …
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
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 …
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
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 …
paving the way for the identification of cell subpopulations. Although deep learning has …
Multi-view clustering with graph learning for scRNA-Seq data
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 …
(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
In order to alleviate the network information overload, recommender system becomes
widespread in personalized recommendation. However, due to the increase of the number …
widespread in personalized recommendation. However, due to the increase of the number …