VoxHunt: Resolving human brain organoid heterogeneity through single-cell genomic comparison to spatial brain maps

Graph AI generates neurological hypotheses validated in molecular, organoid, and clinical systems

Organoid Localization and Quantification Using Deep Convolutional Neural Networks

Granular Functional Filtering (Gruffi) to isolate stressed cells

Brain-Referenced In vivo-to-in vitro Developmental Guidance and Evaluation.

Code for the analysis chapter of my PhD thesis looking at kidney organoid scRNA-seq data

Pipeline for analysing and visualising CyTOF datasets, with a focus on PTM signalling networks.

Deterministic evolution and stringent selection during pre-neoplasia

Multi-unit spike analysis in ventral midbrain-striatal-cortical organoids (MISCOs) pre- and post- optogenetic stimulation.

Human brain organoids connected to silicon computers

A sophisticated scientific simulation platform for analyzing organoid learning capacity through cutting-edge machine learning and interactive data visualization. This platform enables researchers to simulate and analyze how organoids learn and adapt in response to various stimuli, focusing on Organoid Intelligence (OI) and Organoid Learning (OL).

Bacterial colonies attaching themselves to human brain organoids, as a neural link to a silicon computer

Electrophysiology analysis in ventral midbrain-striatal-cortical organoids (MISCOs) pre- and post- optogenetic stimulation.

This repository provides deep learning models trained on a large dataset of Pancreatic Ductal Adenocarcinoma Organoids co-cultured with immune cells.

Preprocess, noise-reduction, threshold & quantify images to get box plots for each class (mainly cell cultures of different cel llines). Colocalization due to a naive trick of counting all overlapping signals/pixels. Could be done in ImageJ as well, but i thought this is better suited than fiddling with macros.

Multi-scale bioinformatics pipeline for patient-specific drug screening via computational simulation of patient-derived organoids. Integrates U-Net segmentation, agent-based cell simulation, QSAR drug modelling and PDE diffusion.

Automated, high-throughput, quantitative characterization of morphological features and fluorescence signals of organoid and spheroid cultures

Oraganoid segmentation tool

A Python pipeline for quantitative 3D organoid and spheroid image analysis from confocal microscopy. The project combines Cellpose-based segmentation with single-cell morphological profiling, spatial topology analysis, heterogeneity discovery, and statistical comparisons to enable reproducible analysis of multicellular 3D cultures.