Multi-modal Single-cell Clustering
Multi-Modal Single-Cell Clustering is a computational approach that integrates multiple distinct molecular measurement types (such as transcriptome, epigenome, and proteome) from the same single cells to jointly identify cellular subpopulations, thereby enabling more comprehensive and biologically resolved cell type or state classification than unimodal clustering methods.
4
Publications
579
Citations
58
Authors
38
Institutions
Publications per year
2017–2026
4
Variants
Multimodal Single-cell Clustering
Parents
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Deconstruction of rheumatoid arthritis synovium defines inflammatory subtypes
Fan Zhang, A. Helena Jonsson, Aparna Nathan et al. · Nature · 2023 · 393 citations · Full text
Jun Inamo, Masaru Takeshita, Katsuya Suzuki et al. · Nature Communications · 2025 · 11 citations · Full text
Life Sciences, Immunology, Pathology +17
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University of Pittsburgh
Pittsburgh, United States
2 h-index
13 publications
2.2K citations

National University of Defense Technology
Changsha, China
1 h-index
4 publications
244 citations
University of Copenhagen
Copenhagen, Denmark
1 h-index
2 publications
50 citations

University of Rochester
Rochester, United States
1 h-index
1 publications
393 citations
National Institute of Allergy and Infectious Diseases
Bethesda, United States
1 h-index
1 publications
393 citations
Feinstein Institute for Medical Research
Manhasset, United States
1 h-index
2 publications
786 citations

Boston Children's Hospital
Boston, United States
1 h-index
1 publications
393 citations
Queen Mary University of London
London, United Kingdom
1 h-index
4 publications
1.6K citations
1–8 of 38
2 publications · 125 citations
2
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1 publications · 61 citations
1
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1 publications · 393 citations
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1 publications · 11 citations
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