🏃 The go-to single-cell Foundation Model
- batch-correction
- cell-biology
- celltype-annotation
- denoising
Repository Index
67,262 visible repositories in the index
25–41 of 41 · Most stars
Data visualisation web components for the life sciences.
- biohackeu21
- bioinformatics
- visualization
- webcomponents
Accurate and efficient spot detection for microscopy data
CASSIA: A Multi-Agent LLM-Based Single-Cell Cell Type Annotation Framework
- ai4science
- llm
- multiagent-systems
- prompt-engineering
Rails frontend to The Genome Institute's drug gene interaction database.
NeuroAnatomy Toolbox: An R package for the (3D) visualisation and analysis of biological image data, especially tracings of single neurons.
- r
- neuroanatomy-toolbox
- cran
- neuron
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
Python package for analysis of multiomic single cell RNA-seq and ATAC-seq.
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
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
Multigrate: multiomic data integration for single-cell genomics
Deciphering cell-cell communication from spatially resolved transcriptomic data at single-cell resolution with subgraph-based attentional graph neural network
Single-cell fluorescence microscopy data analysis
- microscopy
- fluorescence-microscopy-imaging
Data logistics system enabling real-time pathogen surveillance. Built for the Seattle Flu Study.
- postgres
- postgresql
- python
- infectious-disease
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.
gateway for segmentation data to Rstats & visualization with ggplot2 - in development
- visualization
- fluorescence-data
- ggplot
DeepAEG: A model for predicting cancer drug response based on data enhancement and edge-collaborative update strategies