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Reference mapping for single-cell genomics
scPerturb: A resource and a python/R tool for single-cell perturbation data
Repository for Nicheformer: a foundation model for single-cell and spatial omics
🏃 The go-to single-cell Foundation Model
Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.
PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturbations at bulk and single-cell levels.
Repository for paper scMulan: a multitask generative pre-trained language model for single-cell analysis.
Deep learning model for single-cell inference of multi-omic profiles from a single input modality.
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