Single Cell Analysis
Showing 22 of 22 projects
A curated list of deep learning implementations and resources for biological research, with a focus on genomics.
A Python library for deep probabilistic modeling and analysis of single-cell and spatial omics data.
A transformer-based foundation model pretrained on millions of single-cell profiles for generative AI tasks in single-cell multi-omics.
A collection of transformer-based foundation models for genomics and transcriptomics, enabling tasks like sequence analysis, functional prediction, and conversational DNA exploration.
R toolkit for inference, visualization and analysis of cell-cell communication from single-cell transcriptomics data.
A scalable Python toolkit for analyzing and visualizing spatial molecular data from tissue sections.
A deep learning library for single-cell analysis of biological images, specializing in cell segmentation and tracking.
A deep learning framework for integrating single-cell multi-omics data using graph-linked unified embeddings.
A probabilistic cell segmentation method for spatial transcriptomics data from platforms like Xenium, CosMx, MERSCOPE, and Visium HD.
A curated collection of databases, software, and papers for computational biology research.
A PyTorch deep generative model for integrating and imputing single-cell multimodal data with missing modalities.
A multitask generative pre-trained language model for zero-shot cell type annotation, batch integration, and conditional cell generation in single-cell transcriptomics.
An interpretable multi-task deep neural network for single-cell multi-omics integration and cross-modal analysis.
A deep learning model that translates between single-cell multi-omic profiles, such as scATAC-seq and scRNA-seq, using a shared latent representation.
An MCP server that enables natural language conversation for analyzing spatial transcriptomics data through 60+ curated methods.
A Python package for 3D single-cell shape analysis using geometric deep learning on point clouds and voxels.
A fast spatial deconvolution tool for transcriptomics data that scales to million-spot datasets while preserving rare cell type signals.
A Julia toolkit for robust multidimensional profiling of high-content cellular imaging data.
A Python package for analyzing high-throughput single-cell imaging data, including protein abundance, endocytosis, and particle tracking.
A MATLAB-based toolbox for interactive visualization and analysis of multiplexed image cytometry data.
A Python library for analyzing mRNA and protein spatial and temporal distributions in single-cell confocal microscopy images.
Interactive visualization of higher-order graphs in Python using proportion of degrees by communities.
Related Tags
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.