Computational Stem Cell Biology

15 March, 31 March, and 12 April 2021

Groundbreaking advances in RNA- and DNA-sequencing and bioinformatic technologies have presented stem cell biologists with new insights into complex biological, developmental, and disease processes. It has also catalyzed a relatively new field of computational stem cell biology. This program focuses on the latest developments in this rapidly advancing field. More information coming soon.


Part 1: Exploring Stem Cells with Single Cell and Combinatorial Analyses
15 March, 2021
02:00 EDT (view your time zone)

With the ability to perturb and molecularly characterise cells at the single-cell resolution comes a new ability to combinatorially explore cell fate at a completely different scale. We will discuss how the evolving single-cell tool-kit and the associated computational tools allow us to understand and control cell fate in new ways, from the emergence of previously uncovered cell-states to the high-throughput screening of transcriptional and genetic perturbations. The session will include presentations from experts in the field and an open discussion on future directions and opportunities. 

Part 1 Co-Organizers

Owen Rackham Square
Owen Rackham, PhD, Duke-NUS, Singapore
Jay Shin Square
Jay Shin, D. Sci., RIKEN Center for Integrative Medical Sciences, Japan


Grace YeoSquare
Grace Hui Ting Yeo, PhD, Genome Institute of Singapore, Singapore
Sarah Pierce Square
Sarah Pierce, BS, Stanford University, USA

Part 2: Reference Maps for Stem Cell Biology
31 March, 2021
02:30 EDT (view your time zone)

Part 2 Co-Organizers

Sam Morris Square
Samantha Morris, PhD, Washington University in St. Louis, USA
Christine Wells Square
Christine Wells, PhD, University of Melbourne, Australia


Melissa Little, BS, PhD, GAI, Murdoch Childrens Research Institute, Australia
Barbara Treutlein, PhD, ETH Zürich, Germany
Shila Ghazanfar Square
Shila Ghazanfar, Cancer Research UK Cambridge Institute, UK

Part 3: Computational Models in Stem Cells and Development
12 April, 2021
14:30 EDT (view your time zone)

The advent of Big Data in biology has created major bottlenecks in translating data into knowledge. Computational modeling can alleviate this problem by providing a platform to explore, in silico, mechanistic models that explain a set of observations and that yield specific, testable hypotheses. In this webinar, three speakers will guide us through different classes and applications of computational models ranging from intra-cellular regulatory networks to multi-scale cell-based models of stem cells.

Part 3 Co-Organizers

Patrick Cahan Square
Patrick Cahan, PhD, Johns Hopkins University, USA
Peter Zandstra Square
Peter Zandstra, PhD, The University of British Columbia, Canada


Sarah Dunn Square
Sara-Jane Dunn, DeepMind, UK
Himanshu Kaul, The University of British Columbia, Canada