Repository Index

Open-source software for exploring and analyzing large, high-dimensional image-derived data.

• cellprofiler-analyst
• cellprofiler
• image-analysis
• machine-learning

🏃 The go-to single-cell Foundation Model

• batch-correction
• cell-biology
• celltype-annotation
• denoising

Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.

• disentanglement
• drug-discovery
• genomics
• perturbation

TransformerCPI: Improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments(BIOINFORMATICS 2020) https://doi.org/10.1093/bioinformatics/btaa524

• self-attention
• compound-protein-interaction
• transformercpi
• structure-free-virtual-sreening

Interpretable bilinear attention network with domain adaptation improves drug-target prediction.

A collection of tasks to probe the effectiveness of protein sequence representations in modeling aspects of protein design

• protein
• protein-sequences
• protein-design
• representation-learning

A tool for cell instance aware segmentation in densely packed 3D volumetric images

• segmentation
• deep-learning
• bioinformatics
• neural-network

Learning cell communication from spatial graphs of cells

• tensorflow
• gnn
• glm
• cvae

Toolbox for the analysis of smFISH images.

• pattern-classification
• rna-localization
• segmentation
• smfish

NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions

• computational-biology
• bioinformatics
• graph-convolution
• deep-learning

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

Predicting Cell Health with Morphological Profiles

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

3D shape analysis using deep learning

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

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

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

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