BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Synthesising Gene Regulatory Networks from Single-Cell Gene Expres
 sion Data - Steven Woodhouse\, University of Cambridge
DTSTART:20160105T100000Z
DTEND:20160105T110000Z
UID:TALK62976@talks.cam.ac.uk
CONTACT:44918
DESCRIPTION:Recent experimental advances in biology allow researchers to o
 btain gene expression profiles at single-cell resolution over hundreds\, o
 r 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 th
 e population-level averages provided by conventional high-throughput exper
 iments. This new data therefore provides an exciting opportunity for compu
 tational modelling.\n\nA 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 ma
 mmalian embryo by single cell expression analysis of 3\,934 cells at four 
 sequential developmental stages. Taking advantage of the single-cell resol
 ution of the data\, we treated expression profiles as states of an asynchr
 onous Boolean network and framed the gene regulatory network inference as 
 the problem of reconstructing a Boolean network from its state space. We t
 hen introduced a scalable algorithm to solve this synthesis problem. \nOur
  technique synthesises a matching Boolean network\, and analysis of this m
 odel yields new predictions about blood development which our experimental
  collaborators were able to verify.\n\n
LOCATION:Auditorium\, Microsoft Research Ltd\, 21 Station Road\, Cambridge
 \, CB1 2FB
END:VEVENT
END:VCALENDAR