Clustering and classification methods for single-cell RNA-sequencing data.

Qi, Ren; Ma, Anjun; Ma, Qin; Zou, Quan

Qi, Ren; Ma, Anjun; Ma, Qin; Zou, Quan.

Affiliation

Qi R; School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, Tianjin, China.
Ma A; Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, USA.
Ma Q; Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China.
Zou Q; Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, China.

Brief Bioinform ; 21(4): 1196-1208, 2020 07 15.

Article in En | MEDLINE | ID: mdl-31271412

Subject(s)

Sequence Analysis, RNA/methods; Single-Cell Analysis/methods; Algorithms; Cluster Analysis; Datasets as Topic; Transcriptome

Key words

classification; clustering; machine learning; sequences analysis; similarity metric; single-cell RNA-seq

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Full text: 1 Database: MEDLINE Main subject: Sequence Analysis, RNA / Single-Cell Analysis Language: En Journal: Brief Bioinform Journal subject: BIOLOGIA / INFORMATICA MEDICA Year: 2020 Type: Article Affiliation country: China

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