an SRT simulator for simulating multiple spatial variability in spatial resolved transcriptomics and generating unbiased simulated SRT data

A computational method to rank and infer drug-responsive cell population towards in-silico drug perturbation using a target-perturbed gene regulatory network (tpGRN) for single-cell transcriptomic …

Code and data for the Nature Machine Intelligence paper "Knowledge graph-enhanced molecular contrastive learning with functional prompt".

Spatial omics analysis toolbox

MultiNicheNet: a flexible framework for differential cell-cell communication analysis from multi-sample multi-condition single-cell transcriptomics data

Knowledge-graph-based cell-cell communication inference for spatially resolved transcriptomic data

an integrative algorithm to distinguish spatially variable cell subclusters by reconstructing cells onto a pseudo space with spatial transcriptome references

a spatial deconvolution method based on deep learning frameworks, which converts bulk transcriptomes into spatially resolved single-cell expression profiles

Graph Transformer Architecture. Source code for "A Generalization of Transformer Networks to Graphs", DLG-AAAI'21.

This is a Pytorch implementation of the paper: Self-Supervised Graph Transformer on Large-Scale Molecular Data

Graph Transformer Networks (Authors' PyTorch implementation for the NeurIPS 19 paper)

Identifying key genes and cell subclusters for time-series single cell sequencing data

A clinical genomics-guided prioritizing strategy enables accurately selecting proper cancer cell lines for biomedical research

A manually curated database of literature-supported ligand-receptor interactions in human and mouse

The source code and results of performance comparison on the detail of the process among scCATCH, CellAssign, Garnett, SingleR, scMap and CHETAH, and CellMatch database

The source code and results for different methods on annotating external testing datsets of human and mouse.

Cell-type Annotation for Single-cell Transcriptomics using Deep Learning with a Weighted Graph Neural Network

Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.

Automatic Annotation on Cell Types of Clusters from Single-Cell RNA Sequencing Data