Showing 7 of 7 projects
A transformer-based foundation model pretrained on millions of single-cell profiles for generative AI tasks in single-cell multi-omics.
An automated cell type annotation tool for single-cell RNA-seq data using logistic regression classifiers.
A deep learning framework for integrating single-cell multi-omics data using graph-linked unified embeddings.
A multitask generative pre-trained language model for zero-shot cell type annotation, batch integration, and conditional cell generation in single-cell transcriptomics.
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 fast spatial deconvolution tool for transcriptomics data that scales to million-spot datasets while preserving rare cell type signals.
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