Repository Index

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

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

MCP server for spatial transcriptomics analysis through natural language interfaces.

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

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

A versatile single-cell cross-modality translation method via dual-aligned variational autoencoders

Fast, deterministic cell-type deconvolution for million-bin spatial transcriptomics

• bioinformatics
• cell-type-deconvolution
• computational-biology
• deconvolution

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

Official implementation of JAMIE, Joint variational Autoencoders for Multimodal Imputation and Embedding

• autoencoder
• imputation
• integration
• multimodal

A flexible Julia toolkit for high-dimensional cellular profiles

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

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.

Analysis of cell migration in Igor Pro

• igor
• imagej
• cell-migration
• tracking

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

Vendor-agnostic, FHIR-Genomics-aligned API contract for cross-vendor NGS interpretation. JSON Schema + TypeScript + Python pydantic.

gateway for segmentation data to Rstats & visualization with ggplot2 - in development

• visualization
• fluorescence-data
• ggplot

Python library for statistical analysis of mRNA and protein distributions in fluorescent microscopy images

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

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