Deep learning for morphological cell profiling
Title: Deep learning for morphological cell profiling
SNIC Project: Berzelius-2022-143
Project Type: LiU Berzelius
Principal Investigator: Ola Spjuth <ola.spjuth@farmbio.uu.se>
Affiliation: Uppsala universitet
Duration: 2022-08-31 – 2023-03-01
Classification: 10610
Homepage: https://pharmb.io/project/autonomous-phenomics/
Keywords:

Abstract

In our lab we expose cells to drugs and environmental toxicants and use the Cell Painting methodology to capture images using high-content imaging. We analyze these images using AI/MOL methods including deep neural (convolutional) networks and recurrent neural networks. We also develop new methods for live-cell imaging. Key objectives are to propose new combination treatments for different types of cancers, and to study effects of combinations of environmental toxicants.