Cargando…
Detection of high variability in gene expression from single-cell RNA-seq profiling
BACKGROUND: The advancement of the next-generation sequencing technology enables mapping gene expression at the single-cell level, capable of tracking cell heterogeneity and determination of cell subpopulations using single-cell RNA sequencing (scRNA-seq). Unlike the objectives of conventional RNA-s...
Autores principales: | Chen, Hung-I Harry, Jin, Yufang, Huang, Yufei, Chen, Yidong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5001205/ https://www.ncbi.nlm.nih.gov/pubmed/27556924 http://dx.doi.org/10.1186/s12864-016-2897-6 |
Ejemplares similares
-
CeL-ID: cell line identification using RNA-seq data
por: Mohammad, Tabrez A., et al.
Publicado: (2019) -
Differential expression analysis of RNA sequencing data by incorporating non-exonic mapped reads
por: Chen, Hung-I Harry, et al.
Publicado: (2015) -
Expression profile of circular RNAs in infantile hemangioma detected by RNA-Seq
por: Li, Jun, et al.
Publicado: (2018) -
A Bayesian approach for identifying miRNA targets by combining sequence prediction and gene expression profiling
por: Liu, Hui, et al.
Publicado: (2010) -
Gene expression variability in mammalian embryonic stem cells using single cell RNA-seq data
por: Mantsoki, Anna, et al.
Publicado: (2016)