Cargando…
Identification of cancer subtypes from single-cell RNA-seq data using a consensus clustering method
BACKGROUND: Human cancers are complex ecosystems composed of cells with distinct molecular signatures. Such intratumoral heterogeneity poses a major challenge to cancer diagnosis and treatment. Recent advancements of single-cell techniques such as scRNA-seq have brought unprecedented insights into c...
Autores principales: | Gan, Yanglan, Li, Ning, Zou, Guobing, Xin, Yongchang, Guan, Jihong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6311928/ https://www.ncbi.nlm.nih.gov/pubmed/30598115 http://dx.doi.org/10.1186/s12920-018-0433-z |
Ejemplares similares
-
TriPCE: A Novel Tri-Clustering Algorithm for Identifying Pan-Cancer Epigenetic Patterns
por: Gan, Yanglan, et al.
Publicado: (2020) -
Dynamic epigenetic mode analysis using spatial temporal clustering
por: Gan, YangLan, et al.
Publicado: (2016) -
Identification of Differential Gene Groups From Single-Cell Transcriptomes Using Network Entropy
por: Gan, Yanglan, et al.
Publicado: (2020) -
Genome-wide analysis of epigenetic dynamics across human developmental stages and tissues
por: Zhang, Xia, et al.
Publicado: (2019) -
Inferring Gene Regulatory Networks From Single-Cell Transcriptomic Data Using Bidirectional RNN
por: Gan, Yanglan, et al.
Publicado: (2022)