Python package for analysis of multiomic single cell RNA-seq and ATAC-seq.
Repository Index
85,081 visible repositories in the index
73–95 of 95 · Most stars
Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications
- cell-annotation
- multiplexed-imaging
- mpif
Repository for paper scMulan: a multitask generative pre-trained language model for single-cell analysis.
- foundation-models
- gpt
- single-cell
Run scripts, explore your genome, and get personalized explanations — all in natural dialogue.
- analysis
- claude
- claudecode
- dna
High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations
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
The repository host gives no description.
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
3D shape analysis using deep learning
- cancer-biology
- cell-biology
- deep-learning
- geometric-deep-learning
A versatile single-cell cross-modality translation method via dual-aligned variational autoencoders
Single-cell fluorescence microscopy data analysis
- microscopy
- fluorescence-microscopy-imaging
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"
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
XitoSBML - the spatial SBML plugin for ImageJ
- sbml
- systems-biology
- spatial-sbml-plugin
- imagej
Interpretable modeling of cellular responses to drug perturbations using cycle consistence learning
Python library for statistical analysis of mRNA and protein distributions in fluorescent microscopy images