pySCENIC 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.

High dimensional weighted gene co-expression network analysis

Context specific and dynamic gene regulatory network reconstruction and analysis

netZooR is a network biology package implemented in R.

netZooPy is a network biology package implemented in Python.

Fast visualization tool for large-scale and high dimensional single-cell data

PECA is a software for inferring context specific gene regulatory network from paired gene expression and chromatin accessibility data

Netbooks is a JupyterHub catalog of use cases in gene regulatory network inference using netZoo methods..

R/MATLAB package to perform virtual knockout experiments on single-cell gene regulatory networks.

single cell foundation model for Gene network inference and more

netZooM is a network biology package implemented in MATLAB.

netZooC is a network biology package implemented in C.

Adversarial generation of gene expression data using Generative Adversarial Networks

Code for scKINETICS (ISMB 2023)

Causal inference, differential expression, and co-expression for scRNA-seq

Diffusion model for gene regulatory network inference.

Evaluation framework for computationally inferred gene networks from single-cell data.

A deep model infers gene regulation networks from scRNA-seq data.

R and MATLAB scripts for MAGICAL

A scalable method to infer fate specific gene regulatory network from single cell gene expression data