Repository Index

🏃 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

Accurate and efficient spot detection for microscopy data

The repository host gives no description.

The repository host gives no description.

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

code to run sei and obtain sei and sequence class predictions

Integrated pipeline for multiplexed image analysis

• multiplexed-imaging
• python

PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturbations at bulk and single-cell levels.

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

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

• cell-annotation
• multiplexed-imaging
• mpif

High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations

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.

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

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