Inner ear models for Python
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Inner ear models for Python
Learning cell communication from spatial graphs of cells
CASSIA: A Multi-Agent LLM-Based Single-Cell Cell Type Annotation Framework
Official repo for CellPLM: Pre-training of Cell Language Model Beyond Single Cells.
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).
Python package for analysis of multiomic single cell RNA-seq and ATAC-seq.
Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications
Repository for paper scMulan: a multitask generative pre-trained language model for single-cell analysis.
High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations
Methods for Image-Based Cell Profiling
Deep learning model for single-cell inference of multi-omic profiles from a single input modality.
MCP server for spatial transcriptomics analysis through natural language interfaces.
Predicting Cell Health with Morphological Profiles
A foundation model-driven whole slide image-scale cell phenotyping method with QuPath integration Resources
Multigrate: multiomic data integration for single-cell genomics
CancerFoundation: A single-cell RNA sequencing foundation model to decipher drug resistance in cancer
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
A versatile single-cell cross-modality translation method via dual-aligned variational autoencoders
Single-cell fluorescence microscopy data analysis
Fast, deterministic cell-type deconvolution for million-bin spatial transcriptomics
A flexible Julia toolkit for high-dimensional cellular profiles
scPair: Boosting single cell multimodal analysis by leveraging single cell atlases and implicit feature selection