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CellBIC: bimodality-based top-down clustering of single-cell RNA sequencing data reveals hierarchical structure of the cell type
Junil Kim, Diana E Stanescu,
Kyoung Jae Won
Won Group
3
Citations (Scopus)
48
Downloads (Pure)
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Dive into the research topics of 'CellBIC: bimodality-based top-down clustering of single-cell RNA sequencing data reveals hierarchical structure of the cell type'. Together they form a unique fingerprint.
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Keyphrases
Single-cell RNA Sequencing (scRNA-seq)
100%
Single-cell RNA Sequencing Data
100%
Hierarchical Clustering
100%
Bimodality
100%
Hierarchical Structure
100%
Clustering Approach
50%
Distance Metric
50%
Type 2 Diabetes Mellitus (T2DM)
50%
Gene Expression
50%
Cell Population
50%
Dynamic Change
50%
Age-specific
50%
Study Heterogeneity
50%
Data-centric
50%
Clustering Algorithm
50%
Six3
50%
Expression Distribution
50%
Computer Science
Hierarchical Clustering
100%
Bottom-Up Approach
50%
Distance Metric
50%
Cell Population
50%
Clustering Algorithm
50%
clustering approach
50%
Immunology and Microbiology
RNA Sequence
100%
Gene Expression
25%
Cell Population
25%