R toolkit for inference, visualization and analysis of cell-cell communication from single-cell data

R toolkit for inference, visualization and analysis of cell-cell communication from single-cell and spatially resolved transcriptomics

Code for ICLR 2024 (Spotlight) paper "MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding"

EcoTyper is a machine learning framework for large-scale identification of cell states and cellular ecosystems from gene expression data.

R package that automatically classifies the cells in the scRNA data by segregating non-malignant cells of tumor microenviroment from the malignant cells. It also infers the copy number profile of malignant cells, identifies subclonal structures and analyses the specific and shared alterations of each subpopulation.

Single-cell transcriptomics and epigenomics unravel the role of monocytes in neuroblastoma bone marrow metastasis

Entrain: Predicting Environmental Regulators of Differentiation Trajectories

A universal tool for rapid identification of cancer foci and tumor boundaries in spatial transcriptome