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BEGIN:VEVENT
DTSTAMP:20260614T160840Z
DTSTART;VALUE=DATE-TIME:20170127T140000
DTEND;VALUE=DATE-TIME:20170127T150000
SUMMARY:OxWaSP mini-symposium: Magnus Rattray (Manchester) "Uncovering pa
 tterns in gene expression dynamics with Gaussian process inference"
TZID:Europe/London
UID:20170127-094d43f559cbcdad0159cffd5f080e73@warwick.ac.uk
CREATED:20170124T102005Z
DESCRIPTION:Gaussian processes provide a convenient and flexible class of
  non-parametric model for temporal and spatial data. We are applying Gau
 ssian processes in a range of biological applications involving high-thr
 oughput time course data\, e.g. modelling the elongation dynamics of pol
 ymerase\, uncovering mRNA production delays\, inferring regulatory netwo
 rks and most recently identifying perturbations and bifurcations from hi
 gh-throughput expression data. I will provide an overview of Gaussian pr
 ocess inference and describe some of our recent work in modelling gene e
 xpression dynamics. Most recently we have been focusing on single-cell d
 ata. Using longitudinal data from microscopy experiments we are using st
 ochastic periodic processes to uncover periodicity controlled by negativ
 e feedback loops. Using genome-wide single-cell expression data we are u
 ncovering branching processes and uncovering the order with which differ
 ent genes differentiate through a developmental process.
LOCATION:F1.07 (Engineering)
CATEGORIES:Seminars
LAST-MODIFIED:20170124T102005Z
ORGANIZER;CN="":
END:VEVENT
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