University of Cambridge > Talks.cam > Microsoft Research Cambridge, public talks > Synthesising Gene Regulatory Networks from Single-Cell Gene Expression Data

Synthesising Gene Regulatory Networks from Single-Cell Gene Expression Data

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact ecturescam.

Please be aware that this event may be recorded. Microsoft will own the copyright of any recording and reserves the right to distribute it as required.

Recent experimental advances in biology allow researchers to obtain gene expression profiles at single-cell resolution over hundreds, or even thousands of cells at once. These single-cell measurements provide snapshots of the states of the cells that make up a tissue, instead of the population-level averages provided by conventional high-throughput experiments. This new data therefore provides an exciting opportunity for computational modelling.

A fundamental challenge in biology is to understand the gene regulatory networks which control how tissue development occurs in the mammalian embryo. We studied the first emergence of blood in the mammalian embryo by single cell expression analysis of 3,934 cells at four sequential developmental stages. Taking advantage of the single-cell resolution of the data, we treated expression profiles as states of an asynchronous Boolean network and framed the gene regulatory network inference as the problem of reconstructing a Boolean network from its state space. We then introduced a scalable algorithm to solve this synthesis problem. Our technique synthesises a matching Boolean network, and analysis of this model yields new predictions about blood development which our experimental collaborators were able to verify.

This talk is part of the Microsoft Research Cambridge, public talks series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2019 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity