Repository Index

Tool for precise, interactive, fast and scalable FISH spot detection

Adaptive Graph Attention Auto-encoder for Spatial Domain Identification of Spatial Transcriptomics

The repository host gives no description.

Deep learning model for single-cell inference of multi-omic profiles from a single input modality.

• single-cell
• scrna-seq
• scatac-seq
• deep-neural-networks

Predicting Cell Health with Morphological Profiles

• carpenter-lab
• morphological-profiling
• crispr
• cell-painting

Multigrate: multiomic data integration for single-cell genomics

CancerFoundation: A single-cell RNA sequencing foundation model to decipher drug resistance in cancer

• cancer
• foundation-model
• single-cell

Deciphering cell-cell communication from spatially resolved transcriptomic data at single-cell resolution with subgraph-based attentional graph neural network

Data logistics system enabling real-time pathogen surveillance. Built for the Seattle Flu Study.

• postgres
• postgresql
• python
• infectious-disease

A flexible Julia toolkit for high-dimensional cellular profiles

• julia
• morphological-analysis
• high-content-screening

DetecDiv provides a comprehensive set of tools to analyze time microscopy images using deep learning methods. The software structure is such that data can be processed either at the command line or using a graphical user-interface. Detecdiv classification models include : image classification and regression, semantic segmentation, LSTM networks to analyze data and image timeseries.

Interpretable modeling of cellular responses to drug perturbations using cycle consistence learning

DeepAEG: A model for predicting cancer drug response based on data enhancement and edge-collaborative update strategies

Interpretable drug response prediction with graph neural networks over drugs, cell lines, and genes.