Single-cell Clustering
Single-Cell Clustering is a computational analysis method that partitions individual cells into distinct groups based on the similarity of their high-dimensional gene expression profiles derived from single-cell RNA sequencing data.
920
Publications
148.7K
Citations
5.8K
Authors
1.4K
Institutions
Publications per year
2017–2026
799
920
SCENIC: single-cell regulatory network inference and clustering
Sara Aibar, Carmen Bravo González‐Blas, Thomas Moerman et al. · Nature Methods · 2017 · 6.9K citations · Full text
Dictionary learning for integrative, multimodal and scalable single-cell analysis
Yuhan Hao, Tim Stuart, Madeline H. Kowalski et al. · Nature Biotechnology · 2023 · 4.8K citations · Full text
Single-cell transcriptomic analysis of Alzheimer’s disease
Hansruedi Mathys, José Dávila-Velderrain, Zhuyu Peng et al. · Nature · 2019 · 2.7K citations · Full text
1–5 of 920
5.8K
9
h-index
9
h-index
8
h-index
8
h-index
8
h-index
1–5 of 5.8K
1.4K
Stanford University
Stanford, United States
33 h-index
294 publications
84.9K citations
Harvard University
Cambridge, United States
28 h-index
185 publications
68.2K citations

Peking University
Beijing, China
24 h-index
163 publications
63.6K citations
University of Cambridge
Cambridge, United Kingdom
22 h-index
58 publications
25.4K citations

Wellcome Sanger Institute
Cambridge, United Kingdom
21 h-index
78 publications
35.6K citations

Chinese Academy of Medical Sciences & Peking Union Medical College
Beijing, China
20 h-index
111 publications
9.3K citations

Broad Institute
Cambridge, United States
20 h-index
138 publications
107.3K citations

Howard Hughes Medical Institute
Chevy Chase, United States
20 h-index
53 publications
31.9K citations
1–8 of 1.4K
60 publications · 4.8K citations
33
h-index
Repository · 84 publications · 2.4K citations
28
h-index
31 publications · 4.8K citations
24
h-index
29 publications · 3.8K citations
23
h-index
42 publications · 1.5K citations
23
h-index
1–5