Accurate Single-Cell Clustering through Ensemble Similarity Learning

Accurate Single-Cell Clustering through Ensemble Similarity Learning

Single-cell sequencing provides novel means to interpret the transcriptomic profiles of individual cells. To obtain in-depth analysis of single-cell sequencing, it requires effective computational methods to accurately predict single-cell clusters because single-cell sequencing techniques only provi...

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Autores principales: Hyundoo Jeong, Sungtae Shin, Hong-Gi Yeom
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
Materias:
single-cell RNA sequencing
zero-inflated noise reduction
ensemble similarity estimation
correspondence network
visualization and clustering
imputation
Genetics
QH426-470
Acceso en línea:https://doaj.org/article/81efa5a7ee3344549d181b43bcc5a857
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https://doaj.org/article/81efa5a7ee3344549d181b43bcc5a857

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