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Selecting gene features for unsupervised analysis of single-cell gene expression data
J Sheng, WV Li - Briefings in bioinformatics, 2021 - academic.oup.com
Single-cell RNA sequencing (scRNA-seq) technologies facilitate the characterization of
transcriptomic landscapes in diverse species, tissues, and cell types with unprecedented …
transcriptomic landscapes in diverse species, tissues, and cell types with unprecedented …
RCA2: a scalable supervised clustering algorithm that reduces batch effects in scRNA-seq data
The transcriptomic diversity of cell types in the human body can be analysed in
unprecedented detail using single cell (SC) technologies. Unsupervised clustering of SC …
unprecedented detail using single cell (SC) technologies. Unsupervised clustering of SC …
Integrated learning: screening optimal biomarkers for identifying preeclampsia in placental mRNA samples
R Guo, Z Teng, Y Wang, X Zhou… - … Methods in Medicine, 2021 - Wiley Online Library
Preeclampsia (PE) is a maternal disease that causes maternal and child death. Treatment
and preventive measures are not sound enough. The problem of PE screening has attracted …
and preventive measures are not sound enough. The problem of PE screening has attracted …
FSCAM: CAM-based feature selection for clustering scRNA-seq
Y Wang, J Gao, C Xuan, T Guan, Y Wang… - Interdisciplinary …, 2022 - Springer
Cell type determination based on transcriptome profiles is a key application of single-cell
RNA sequencing (scRNA-seq). It is usually achieved through unsupervised clustering. Good …
RNA sequencing (scRNA-seq). It is usually achieved through unsupervised clustering. Good …
[PDF][PDF] Intrusion detection system based on bagging with support vector machine
Due to their rapid spread, computer worms perform harmful tasks in networks, posing a
security risk; however, existing worm detection algorithms continue to struggle to achieve …
security risk; however, existing worm detection algorithms continue to struggle to achieve …