Mapping and navigating biology and chemistry with genome-scale imaging
Image-based readouts of biology are information-rich and inexpensive. Yet historically, bespoke data collection methods and the intrinsically unstructured nature of image data have made these assays difficult to work with at scale. This presentation will discuss advances made at Recursion to industrialise the use of cellular imaging to decode biology and drive drug discovery. First, the use of deep learning allows the transformation of unstructured images into biologically meaningful representations, enabling a ‘map of biology’ relating genetic and chemical perturbations to scale drug discovery. Second, building such a map at whole-genome scale led to the discovery of a “proximity bias” globally confounding CRISPR-Cas9-based functional genomics screens. Finally, I will discuss how publicly-shared resources from Recursion, including the RxRx3 dataset and MolRec application, enable downstream research both on cellular images themselves and on deep learning-derived embeddings, making advanced image analysis more accessible to researchers worldwide.
Date:
19 May 2023, 14:00
Venue:
Mathematical Institute, Woodstock Road OX2 6GG
Venue Details:
Virtual
Speaker:
Dr Imran Haque (Recursion Pharmaceuticals)
Organising department:
Mathematical Institute
Organiser:
Sara Jolliffe (University of Oxford)
Organiser contact email address:
sara.jolliffe@maths.ox.ac.uk
Host:
Dr Peter Minary (University of Oxford)
Part of:
Mathematical Biology and Ecology
Booking required?:
Not required
Audience:
Members of the University only
Editor:
Sara Jolliffe
