Редактирование: CDH2 (раздел)

==Publications==

{{medline-entry
|title=CellBIC: bimodality-based top-down clustering of single-cell RNA sequencing data reveals hierarchical structure of the cell type.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/30102368
|abstract=Single-cell RNA sequencing (scRNA-seq) is a powerful tool to study heterogeneity and dynamic changes in cell populations. Clustering scRNA-seq is essential in identifying new cell types and studying their characteristics. We develop CellBIC (single Cell BImodal Clustering) to cluster scRNA-seq data based on modality in the gene expression distribution. Compared with classical bottom-up approaches that rely on a distance metric, CellBIC performs hierarchical clustering in a top-down manner. CellBIC outperformed the bottom-up hierarchical clustering approach and other recently developed clustering algorithms while maintaining the hierarchical structure of cells. Importantly, CellBIC identifies type 2 diabetes and age specific β cell signatures characterized by [[SIX3]] and [[CDH2]], respectively.
|mesh-terms=* Aging
* Algorithms
* Antigens, CD
* Cadherins
* Cluster Analysis
* Computational Biology
* Diabetes Mellitus, Type 2
* Gene Expression Profiling
* Genetic Markers
* Humans
* Islets of Langerhans
* Pancreas
* Sequence Analysis, RNA
* Single-Cell Analysis

|full-text-url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6265269
}}