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Start of funding 01.01.2017
Differential expression analysis of branching lineages of single-cell RNA-seq data
Prof. Dr. Fabian Theis
Technische Universität München
Dept. of Mathematik - Institute of computational biology (ICB)
Prof. Dr. Nir Yosef
University of California, Berkeley
EECS - Electrical Engineering and Computer Science
Big data analytics for stem cell Biology:
We aim to develop an algorithm to answer specific questions in developmental cell Biology
which were previously hard to tackle: Questions related to cell fate decision making. Cell
fate decision making is of particular interest for stem cell Biology and the emerging field of
reprogramming of induced pluripotent cells, both fields with great biomedical relevance. The
algorithm is a differential gene expression framework, a class of methods which picks out
"interesting" observations (genes) out of a very large sequencing (single-cell transcriptomic)
data set. One focus of this project is to make the algorithm accessible to a wide variety of
groups working in stem cell biology.