A5084369069- Single-cell and spatial transcriptomics
- Gene expression and cancer classification
- Neurogenesis and neuroplasticity mechanisms
- Cell Image Analysis Techniques
- Gene Regulatory Network Analysis
- MicroRNA in disease regulation
Huaqiao University
2023
Anhui University
2021-2022
Abstract The advances in single-cell ribonucleic acid sequencing (scRNA-seq) allow researchers to explore cellular heterogeneity and human diseases at cell resolution. Cell clustering is a prerequisite scRNA-seq analysis since it can recognize identities. However, the high dimensionality, noises significant sparsity of data have made big challenge. Although many methods emerged, they still fail fully intrinsic properties cells relationship among cells, which seriously affects downstream...
Rapid development of single-cell RNA sequencing (scRNA-seq) technology has allowed researchers to explore biological phenomena at the cellular scale. Clustering is a crucial and helpful step for study heterogeneity cell. Although many clustering methods have been proposed, massive dropout events curse dimensionality in scRNA-seq data make it still difficult analysis because they reduce accuracy methods, leading misidentification cell types. In this work, we propose scHFC, which hybrid fuzzy...