148 skills found · Page 1 of 5
aertslab / PySCENICpySCENIC is a lightning-fast python implementation of the SCENIC pipeline (Single-Cell rEgulatory Network Inference and Clustering) which enables biologists to infer transcription factors, gene regulatory networks and cell types from single-cell RNA-seq data.
aertslab / SCENICSCENIC is an R package to infer Gene Regulatory Networks and cell types from single-cell RNA-seq data.
smorabit / HdWGCNAHigh dimensional weighted gene co-expression network analysis
aertslab / ScenicplusSCENIC+ is a python package to build gene regulatory networks (GRNs) using combined or separate single-cell gene expression (scRNA-seq) and single-cell chromatin accessibility (scATAC-seq) data.
Murali-group / BeelineBEELINE: evaluation of algorithms for gene regulatory network inference
cailab-tamu / ScTenifoldKnkR/MATLAB package to perform virtual knockout experiments on single-cell gene regulatory networks.
aertslab / AUCellAUCell: score single cells with gene regulatory networks
aertslab / SCENICprotocolA scalable SCENIC workflow for single-cell gene regulatory network analysis
pinellolab / DictysContext specific and dynamic gene regulatory network reconstruction and analysis
netZoo / NetZooRnetZooR is a network biology package implemented in R.
iaconogi / BigSCale2Framework for clustering, phenotyping, pseudotiming and inferring gene regulatory networks from single cell data
saezlab / CollecTRIGene regulatory network containing signed transcription factor-target gene interactions
vahuynh / GENIE3Machine learning-based approach for the inference of gene regulatory networks from expression data.
netZoo / NetZooPynetZooPy is a network biology package implemented in Python.
dynverse / DyngenSimulating single-cell data using gene regulatory networks 📠
aertslab / SCopeFast visualization tool for large-scale and high dimensional single-cell data
PayamDiba / SERGIOA simulator for single-cell expression data guided by gene regulatory networks
aertslab / ArboretoA scalable python-based framework for gene regulatory network inference using tree-based ensemble regressors.
ZJUFanLab / ScRankA 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 data
flatironinstitute / InferelatorTask-based gene regulatory network inference using single-cell or bulk gene expression data conditioned on a prior network.