Behind the Paper
The real stories behind the latest research papers, from conception to publication, the highs and the lows
SCCAF: machine learning infers putative cell types
We describe SCCAF a computational approach to identify putative cell clusters from single-cell RNA-seq data. SCCAF automatically identifies the “ground truth” cell assignments with high accuracy in various benchmark datasets and captures the discriminative feature genes of the cell types.
Let’s chew the fat about influenza A virus and adipose tissue
Our paper, published on May 14 in Communications Biology, shows that influenza A virus infection durably impacts on the host’s systemic energy metabolism, and promotes depot-specific metabolic reprogramming of fat tissues, in mice.
Blog posted by J. Barthelemy (PhD student) and I. Wolowczuk.
