Repository Index

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

MCP server for spatial transcriptomics analysis through natural language interfaces.

• bioinformatics
• cell-communication
• deconvolution
• machine-learning

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

PyTorch implementation of "TGSA: Protein-Protein Association-Based Twin Graph Neural Networks for Drug Response Prediction with Similarity Augmentation"

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

• postgres
• postgresql
• python
• infectious-disease

scPair: Boosting single cell multimodal analysis by leveraging single cell atlases and implicit feature selection

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

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