JChander/AutoGERN: Single-Cell RNA-Seq Gene Regulatory Network Inference via Explicit Link Modeling and Adaptive Architectures
Abstract
This release provides the first public, reproducible implementation of AutoGERN, a link-centric graph neural network framework for gene regulatory network (GRN) inference from scRNA-seq. AutoGERN explicitly learns edge (link) embeddings in message passing and integrates a stochastic differentiable architecture search to adapt GNN operators to dataset-specific distribution shifts.
Fields of Study & Subjects
Gene Regulatory Network Analysis
Single-cell and spatial transcriptomics
Bioinformatics and Genomic Networks
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 16 February 2026
- Language
- EN