SMS scnews item created by Miranda Luo at Wed 24 Apr 2024 1406
Type: Seminar
Distribution: World
Expiry: 30 Apr 2024
Calendar1: 29 Apr 2024 1300-1400
CalLoc1: In person: Access Grid Room, Level 8, Carslaw Building OR Zoom: https://uni-sydney.zoom.us/j/84087321707
Auth: [email protected] (jluo0722) in SMS-SAML

Statistical Bioinformatics Seminar: Dr Fabio Zanini (UNSW)

Speaker: Dr Fabio Zanini (UNSW) 

Abstract: Single cell sequencing has recently opened a new frontier in biomedicine,
enabling characterisation of cell identities and behaviours with granularity and scale.
Most analyses take place at a mesoscopic scale of sorts: thousands of cells from a
specific organ and organism (e.g.  adult human blood) are individually sequenced and
later computationally grouped (clustering, pseudotime) to gain biological insights.  In
this talk, I will tell two stories that challenge this paradigm in quite opposite ways.
First, I will describe HyperSeq, a new experimental method combining microscopy and
transcriptomics to find cellular diversity where there appears to be none: a healthy
cell line.  Second, I will outline atlas approximations, a desperate quest to fit all
cellular diversity on Earth into a single online place.  

About the speaker: Fabio Zanini is a group leader at UNSW focussing on single cell
biomedicine and open source software development.  After a PhD at the Max Planck
Institute (Germany) and a postdoc at Stanford University (USA), he moved to Australia in
2019 to create the Data Driven Biomedicine lab (https://fabilab.org).  His research
covers three areas: (i) Data science on specific biomedical systems including
development of the lung, viral infections, immunology, and cancer, (ii) Bioinformatic
software including HTSeq 2.0 and igraph, and (iii) Innovation in single cell methods
including computational algorithms and experimental protocols.  Fabio’s overall research
passion is cellular diversity.  

This event will be held in person and online.  

Venue: Carslaw Building, Level 8, Access Grid Room 

Zoom: https://uni-sydney.zoom.us/j/84087321707


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