An Automated Deep-learning Workflow for HCS
Poster Nov 13, 2019

Alberto Pascual and Oren Kraus
Imaging-based phenotypic screening of cell-based disease models has become an indispensable tool for modern drug discovery. Despite the growing adoption of high-content screening (HCS), analyzing the complex imaging data produced by these systems is particularly time-consuming.
However, recent advances in deep learning have enabled the possibility of automating these analyses.
Download this poster to discover a workflow for successful automation of HCS, with details surrounding:
- How to analyze multiple datasets with minimal tuning
- The deep learning algorithms used
- A case study using the automated workflow
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License

OTHER POSTERS
Like what you just read? You can find similar content on the communities below.
Drug Discovery InformaticsTo personalize the content you see on Technology Networks homepage, Log In or Subscribe for Free
LOGIN SUBSCRIBE FOR FREE