[2603.02273] Graph Attention Based Prioritization of Disease Responsible Genes from Multimodal Alzheimer's Network

Computer Science > Machine Learning arXiv:2603.02273 (cs) [Submitted on 1 Mar 2026] Title:Graph Attention Based Prioritization of Disease Responsible Genes from Multimodal Alzheimer's Network Authors:Binon Teji, Subhajit Bandyopadhyay, Swarup Roy View a PDF of the paper titled Graph Attention Based Prioritization of Disease Responsible Genes from Multimodal Alzheimer's Network, by Binon Teji and 2 other authors View PDF HTML (experimental) Abstract:Prioritizing disease-associated genes is central to understanding the molecular mechanisms of complex disorders such as Alzheimer's disease (AD). Traditional network-based approaches rely on static centrality measures and often fail to capture cross-modal biological heterogeneity. We propose NETRA (Node Evaluation through Transformer-based Representation and Attention), a multimodal graph transformer framework that replaces heuristic centrality metrics with attention-driven relevance scoring. Using AD as a case study, gene regulatory networks are independently constructed from microarray, single-cell RNA-seq, and single-nucleus RNA-seq data. Random-walk sequences derived from these networks are used to train a BERT-based model for learning global gene embeddings, while modality-specific gene expression profiles are compressed using variational autoencoders. These representations are integrated with auxiliary biological networks, including protein-protein interactions, Gene Ontology semantic similarity, and diffusion-based gene s...