Self-Supervised Vision Transformers for multiplexed imaging datasets
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Updated
Apr 23, 2026 - Python
Self-Supervised Vision Transformers for multiplexed imaging datasets
Generative Adversarial Network for single image super-resolution in high content screening microscopy images
BIOMERO.analyzer - A python library for easy connecting between OMERO (jobs) and a Slurm cluster
Microsnoop: A generalist tool for microscopy image representation
A flexible Julia toolkit for high-dimensional cellular profiles
A tool for automatic neurite outgrowth and cell viability estimation using deep learning and graph theory.
Scripts for use with BIOMERO
Novel ultrafast suite for high-throughput & high-content multiparameter screening as in drug discovery. It has unique modules for QC, bias correction, similarity measurement, clustering and visualization. It can process hundreds of samples with many markers in a few hours not days & circumvents bath effect. It couples with any plate reader.
Interactive visualisation of quantitative concepts in high-content screening
Python scripts for the SearchFirst option in Wako Software Suite
Command-line tool to process images from PerkinElmer microscopes
Single-cell CFTR image-analysis pipeline for the mCherry-YFPCFTR quenching assay. The pipeline includes a custom-made Cellpose model for image segmentation, and per-cell quantification of CFTR membrane proximity and function.
Pydantic models for CellVoyager CV7000/CV8000 metadata
High-throughput Neuro-Symbolic Agent for automated phenotypic screening. Orchestrates Cellpose perception with PydanticAI reasoning for reproducible drug-discovery workflows.
Metadata files for the idr0061 submission
Processing of 2D fluorescence multichannel images derived from a siRNA HCS assay. Acquired in a Nikon Crestoptics V3 Spinning Disk. Tool developed for the Molecular Mechanisms of Mycobacterial and Viral Infections (MYCOVIR) lab.
Validate the semantic correctness, metadata completeness, provenance and AI readiness of Cell Painting datasets represented in AnnData.
A bilingual work-in-progress book on AI-driven phenotypic drug discovery, from high-throughput screening and Cell Painting to machine learning and drug development.
Analysis at single-cell level with HCS microscopy and Cell Profiler
Metadata files for idr0056 submission
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