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Ardigen phenAID

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Uncovering Gene Functions with the JUMP Cell Painting (JUMP-CP) Dataset

Identifying hits in phenotypic studies using artificial intelligence – based morphological analysis
Poster: Artificial Intelligence predicts cell proliferation from DAPI images of (hISC)-derived colorectal cancer model
Better drug discovery through AI based phenotypic testing
From data to discovery: Interpreting complex phenotypic screens with AI-based insights
Extracting scientific insight from High Content Screening images
Finding divers hit candidates through phenotype-guided virtual screening using AI n molecular and morphology data
Finding diverse hit candidates through phenotype-guided Virtual Screening using Artificial Intelligence on molecular and morphology data
Integrating Cheminformatics and Phenotypic Screening: A Novel Approach for Enhanced Mode of Action Prediction
AI-driven method for identification of hits from phenotypic screening with Cell Painting Assay
Poster