GRNFormer: Accurate Gene Regulatory Network Inference Using Graph Transformer

GRNFormer is available on GitHub (https://github.com/BioinfoMachineLearning/GRNformer); the version used in this work is archived on Zenodo (https://doi.org/10.5281/zenodo.18868395), with evaluation resources for reproducibility.

Authors

Jianlin Jack Cheng (ORCID: https://orcid.org/0000-0003-0305-2853)
Akshata Hegde (ORCID: https://orcid.org/0009-0009-7077-9420)

Institutions

University of Missouri Health System (US)
University of Missouri (US)

Publication Details

Journal: Bioinformatics
Published: 2026-03-23
DOI: https://doi.org/10.1093/bioinformatics/btag144
Primary Topic: Bioinformatics and Genomic Networks
Type: article
Field-Weighted Citation Impact: 0.00

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article

GRNFormer: Accurate Gene Regulatory Network Inference Using Graph Transformer

Jianlin Jack Cheng, Akshata Hegde

Mar 23, 2026

Bioinformatics

Bioinformatics and Genomic Networks

article

GRNFormer: Accurate Gene Regulatory Network Inference Using Graph Transformer

Jianlin Jack Cheng, Akshata Hegde

March 23, 2026article en

Abstract

Bioinformatics

University of Missouri Health System (US), University of Missouri (US)

Zero hunger

Openalex Percentile: Top 7%

Bioinformatics and Genomic Networks

DOI Open Access PDF OpenAlex

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GRNFormer: Accurate Gene Regulatory Network Inference Using Graph Transformer — Jianlin Jack Cheng, Akshata Hegde · Bioinformatics (2026) | TGRS Research Map | TGRS