Computational Biology

Deciphering function from single-cell data

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Science  28 Aug 2015:
Vol. 349, Issue 6251, pp. 940-941
DOI: 10.1126/science.349.6251.940-g

Given their wide range of duties, cells must make tradeoffs between optimal performance and the ability to multitask. Scientists have proposed that groups of cells do this by arranging themselves in the shape of a polygon, in which cells at the vertices express distinct genes optimized for different tasks. |Korem et al. analyzed single-cell measurements of gene expression in various mouse and human tissues and confirmed that cells do organize themselves in this manner. Some tissues showed distinct clusters or well-separated cell types, whereas other tissues had cells with a continuum of gene expression profiles. Examining the gene expression patterns in the cells closest to the vertices may reveal unknown functions for such cells.

PLOS Comput. Biol. 11, e1004224 (2015).

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