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Human Technopole
- Milan
Highlights
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Stars
a generalist algorithm for cellular segmentation with human-in-the-loop capabilities
nnInteractive is a framework for 3D interactive segmentation, supporting intuitive prompts like points, scribbles, bounding boxes, and lasso. Trained on 120+ diverse 3D datasets, it sets a new stan…
An R package to test for batch effects in high-dimensional single-cell RNA sequencing data.
A machine learning method for the discovery of the minimum marker gene combinations for cell type identification from single-cell RNA sequencing
VIPER is a user-friendly software for assembling and identifying viral genomes (currently SARS-CoV-2, Dengue, and Influenza), from Illumina sequencing data generated through genomic surveillance.
Unified knowledge-driven network inference from omics data
A scanpy extension to analyse single-cell TCR and BCR data.
Interactive image stack viewing in jupyter notebooks based on ipycanvas and ipywidgets
A sandbox for benchmarking detection of out-of-reference cells in single-cell genomics data
Introduction to Computational Biology and Bioinformatics Course at Caltech, 2023
most pretty & lovely tables with matplotlib
Reference mapping for single-cell genomics
Single-cell spatial elucidation through image-augmented graph transformer
We will upload here the material and the code of the napari workshop held in Milano on Sept 26-27th 2023
A tool for semi-automatic cell type classification
A tool for refurbishing and modernizing Python codebases
huggingface / accelerate-wip
Forked from huggingface/accelerate🚀 A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision
Tracking and collecting papers/projects/others related to Segment Anything.
This is the repository for a Python bioimage analysis course which establishes the fundamentals of image analysis in the context of biological imaging.
An analysis pipeline in CellProfiler and R for analysis of Whole-slide immunofluorescence image data
Collection of computational tools for cell-cell communication inference for single-cell and spatially resolved omics