This study presents a fully automated workflow for morphological profiling of microscopy images using deep learning–based segmentation built on the IKOSA platform. The system was developed to reduce the manual setup and technical expertise typically required in...
Cell Painting
Harnessing and Validating Deep Learning-based Image Analysis for Cell Painting as an Unbiased Approach to Phenotypic Drug Discovery
The field of target and drug discovery is rapidly embracing high-content (HC) image-based methods, such as Cell Painting. To address the complexity of tools like CellProfiler, we've introduced IKOSA AI, a user-friendly deep learning-based computer vision tool. IKOSA...
How to Successfully Conduct Morphological Cell Profiling With The Cell Painting Assay
The Cell Painting Assay provides researchers with a powerful tool for morphological cell profiling, enabling investigations into cellular behavior and the effect of therapeutic compounds on cellular structures. In this article, we explore the principles and...
Learning From the JUMP CP Pilot Data: Insights for Platform Development
Together with Core Life Analytics, we have embarked on a collaborative project at the forefront of target and drug discovery. IKOSA and StratoMineR provide a comprehensive solution for analyzing, visualizing, and prioritizing features within the JUMP CP dataset. By...
A Fast Approach for Fully-Automated Cell Painting Image Analysis and Feature Extraction from Raw Image Data
In this innovative collaboration with Core Life Analytics we aim to transform cell profiling and reproducible morphological profiling in the pursuit of advanced drug discovery. Our companies are driven by a shared vision to make cell profiling easily accessible to...
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