no code implementations • 18 Mar 2019 • Michael P Snyder, Shin Lin, Amanda Posgai, Mark Atkinson, Aviv Regev, Jennifer Rood, Orit Rosen, Leslie Gaffney, Anna Hupalowska, Rahul Satija, Nils Gehlenborg, Jay Shendure, Julia Laskin, Pehr Harbury, Nicholas A Nystrom, Ziv Bar-Joseph, Kun Zhang, Katy Börner, Yiing Lin, Richard Conroy, Dena Procaccini, Ananda L Roy, Ajay Pillai, Marishka Brown, Zorina S Galis
Transformative technologies are enabling the construction of three dimensional (3D) maps of tissues with unprecedented spatial and molecular resolution.
Communication and coordination play a major role in the ability of bacterial cells to adapt to ever changing environments and conditions.
Determining interactions between entities and the overall organization and clustering of nodes in networks is a major challenge when analyzing biological and social network data.
Here we develop a new method that can utilize soft matches (given as priors) to infer both, unique and similar expression patterns across species and a matching for the genes in both species.