AutoGERN: Single-Cell RNA-Seq Gene Regulatory Network Inference via Explicit Link Modeling and Adaptive Architectures | Synapse
March 26, 2026Open Access
AutoGERN: Single-Cell RNA-Seq Gene Regulatory Network Inference via Explicit Link Modeling and Adaptive Architectures
Key Points
The study aims to develop AutoGERN, a method for inferring gene regulatory networks from single-cell RNA sequencing data.
Developed an explicit link modeling approach for gene regulatory networks.
Utilized adaptive architectures for improved inference accuracy.
Made code and data publicly available on GitHub and Zenodo.
Demonstrated improved inference of regulatory networks compared to existing methods.
Showed enhanced resolution of gene interactions at single-cell level.
Abstract
The code and data of AutoGERN are available on GitHub at https://github.com/JChander/AutoGERN and on Zenodo at https://doi.org/10.5281/zenodo.18659807.