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.

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

single cell foundation model for Gene network inference and more

Code for scKINETICS (ISMB 2023)

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

Diffusion model for gene regulatory network inference.

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

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

R and MATLAB scripts for MAGICAL

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