Processing, visualising and reconstructing network models from single‐cell data. Issue 3 (8th December 2015)

• Record Type: Journal Article
• Authors: Woodhouse, Steven; Moignard, Victoria; Göttgens, Berthold; Fisher, Jasmin
• Is Part Of: Immunology and cell biology. Volume 94:Issue 3(2016)
• Page Start: 256
• Page End: 265
• Publication Date: 2015-12-08
• Subjects: Immunology -- Periodicals; Cytology -- Periodicals; 616.079
• DOI: 10.1038/icb.2015.102
• Languages: English
• ISSNs: 0818-9641

Abstract

Abstract : 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. Abstract : The March 2016 issue contains a Special Feature on Cutting‐edge single‐cell genomics and modelling in immunology. The recent advent of single‐cell genomics has offered unprecedented possibilities for hypothesis‐independent characterization of cellular heterogeneity and regulatory states. At the same time, the vast datasets produced by these techniques have highlighted the need for new bioinformatics tools to utilize the contained information to the fullest. In this Special Feature, both the experimental methods for producing such data as well as selected modelling approaches are reviewed, with focus on the applications on the study of the immune system. Immunology and Cell Biology thanks the coordinators of this Special Feature ‐ Tapio Lönnberg and Valentina Proserpio ‐ for their planning and input.