nichenetr
Cell-cell communication predictor
Predicts ligand-receptor interactions based on gene expression data and integrates prior knowledge to model intercellular communication.
NicheNet: predict active ligand-target links between interacting cells
497 stars
14 watching
118 forks
Language: R
last commit: about 2 years agoLinked from 1 awesome list
cell-cell-communicationdata-integrationgene-expressionintercellular-communicationligand-receptorligand-targetnetwork-inferencerna-seqsingle-cell-omicssingle-cell-rna-seq
Related projects:
| Repository | Description | Stars |
|---|---|---|
| An R package that infers cell-cell communication and ligand-receptor-target networks from spatially resolved transcriptomic data | 61 | |
| An R-based framework to analyze cell-cell communication from single-cell RNA-Seq data by integrating multiple methods and resources | 184 | |
| Infers gene regulatory networks from time-stamped single cell transcriptional expression profiles using a statistical method | 12 | |
| A system that predicts drug-target binding affinity using convolutional neural networks and protein sequences. | 228 | |
| An interactive R/Shiny app for analyzing cell-cell communication from single-cell transcriptomics data | 9 | |
| A deep learning framework for predicting protein-protein interactions based on sequence data | 89 | |
| Predicts cell health from morphological profiles using machine learning and image analysis | 35 | |
| This implementation uses Graph Attention Networks to predict drug response based on genetic influences in heterogeneous networks. | 3 | |
| An R-based software package for analyzing scRNA-seq data to identify robust cell subpopulations and compare population compositions across different tissues and experimental models. | 13 | |
| A framework for predicting pairwise non-covalent interactions and binding affinities between compounds and proteins using machine learning | 100 | |
| Automated assignment of cell types in single-cell RNA-seq data based on marker genes and patient/batch effects | 197 | |
| Automated tool for annotating cell types from single-cell RNA sequencing data based on marker genes | 219 | |
| Analyzes single-cell TCR and BCR data from scRNA-seq using Python | 222 | |
| A tool for identifying cell phenotypes from single-cell RNA sequencing data by projecting onto known cell types | 3 | |
| Reconstructs dynamic gene regulatory networks from single-cell RNA and ATAC-seq data to understand cell-type specific transcription factor regulation. | 111 |