SMS scnews item created by Ellis PATRICK at Sun 13 Oct 2019 1758
Type: Seminar
Distribution: World
Expiry: 14 Oct 2019
Calendar1: 14 Oct 2019 1300-1400
CalLoc1: CPC 3003
CalTitle1: Statistical Bioinformatics Seminar
Auth: ellisp@ (epat8919) in SMS-SAML

Statistical Bioinformatics Seminar: Pengyi Yang -- Systems stem cell biology

Hi All, 

For our next Statistical Bioinformatics Seminar on Monday, we will be
hosting Dr. Pengyi Yang from the University of Sydney.  The seminars are held at 1:00
pm on Mondays at the Charles Perkins Centre, Level 3 Large meeting room.  The format of
the talk is approximately 40 minutes plus discussion.  Further information can be found
on the website

Monday October 14th 2019 
1:00 PM Seminar 
Level 3 Large Meeting Room 
Charles Perkins Centre 

Title: Systems stem cell biology 

Abstract: The ability of stem and progenitor cells to differentiate into specialised
cells is essential for organogenesis and opens the possibility for regenerative medicine
where damaged cells in tissues and organs could be replaced using stem cell-derived
cells.  The understanding of identities and fates of stem/progenitor cells is the
foundation for controlling stem cell differentiation and their use for stem cell-based
therapies.  In this talk, I will present three studies where systems approaches were
utilised to understand cell identities and fate decisions in stem cells and during their
differentiation.  The talk will showcase how computational methods can be applied for
making biological discovery and expanding our knowledge in stem cell biology.  

About the Speaker: Pengyi Yang is the Group Leader of the Computational Systems Biology
group at Children’s Medical Research Institute, at the Westmead Research Hub.  He also
heads the Computational Trans-Regulatory Biology group at Charles Perkins Centre, and
holds a Senior Lectureship at the School of Mathematics and Statistics, the University
of Sydney.  As a systems biologist cross-trained in computer science, statistics, and
systems biology, Pengyi combines computational and statistical methods to model
trans-regulatory networks in stem and progenitor cells using large-scale multi-layered
omic data.  

Hope to see you there!

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