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Processing, visualising and reconstructing network models from single-cell data
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DOI：10.1038/icb.2015.102.png)
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Abstract
En 中文
New single-cell technologies readily permit gene expression profiling of thousands of cells at single-cell resolution. In this review, we will discuss methods for visualisation and interpretation of single-cell gene expression data, and the computational analysis needed to go from raw data to predictive executable models of gene regulatory network function. We will focus primarily on single-cell real-time quantitative PCR and RNA-sequencing data, but much of what we cover will also be relevant to other platforms, such as the mass cytometry technology for high-dimensional single-cell proteomics.
Keywords:
GENE-EXPRESSION ANALYSIS
RNA-SEQ
FATE DECISIONS
TRANSCRIPTIONAL HETEROGENEITY
STEM
DISSECTION
LANDSCAPE
HIERARCHY
DYNAMICS
Journal
IF:
3
Papers:
2.9K
Citations:
4.8K