Getting numbers out of cells - applications of deep neural networks to microscopy image compendia
High throughput microscopy generates high-dimensional data that are far from straightforward to analyze. I will describe our work in using deep neural networks to derive qualitative descriptors (e.g. subcellular localization of a fluorescent protein, or tissue of a histopathology image) and quantitative features (such as abundance of a tagged protein in cell membrane) from images. We apply these ideas to the publicly available GTEX tissue histology dataset, and yeast GFP collection micrographs.
Date: 17 May 2017, 11:30 (Wednesday, 4th week, Trinity 2017)
Venue: Big Data Institute, Old Road Campus OX3 7LF
Venue Details: LG1 seminar room
Speaker: Dr Leopold Parts (Sanger Institute)
Organiser: Cecilia Lindgren (University of Oxford)
Organiser contact email address: carolena@well.ox.ac.uk
Host: Cecilia Lindgren (University of Oxford)
Booking required?: Not required
Audience: Members of the University only
Editor: Carol Mulligan-John