Repository Index

PyTorch implementation of the MIDAS algorithm for single-cell multimodal data integration (Nature Biotechnology 2024).

• deep-generative-model
• deep-learning
• single-cell-data-integration
• single-cell-multiomics

Peax is a tool for interactive visual pattern search and exploration in epigenomic data based on unsupervised representation learning with autoencoders

• epigenomics
• pattern-search
• data-visualization
• interactive-machine-learning

Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications

• cell-annotation
• multiplexed-imaging
• mpif

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

3D shape analysis using deep learning

• cancer-biology
• cell-biology
• deep-learning
• geometric-deep-learning

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

GNN-based gene-selection deep learning model for drug response prediction