Article

DeepDrug2: A Germline-focused Graph Neural Network Framework for Alzheimer’s Drug Repurposing Validated by Electronic Health Records

2025-05-14

Abstract excerpt

Alzheimer’s disease (AD) is a complex neurodegenerative disorder with limited therapeutic options. The original DeepDrug framework by Li et al. (2025) relied on somatic mutation data and emphasized long genes to guide AD drug repurposing. However, emerging evidence suggests that germline genetic variants play a more central role in AD pathogenesis. In response, we develop DeepDrug2, an enhanced AI-driven framework...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: bbe8353e-4edb-527c-8182-703d008a7bf2
DOI: 10.1101/2025.05.13.25327570

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

DeepDrug2: A Germline-focused Graph Neural Network Framework for Alzheimer’s Drug Repurposing Validated by Electronic Health RecordsDOI 10.1101/2025.05.13.25327570Read

DeepDrug: An Expert-led Domain-specific AI-Driven Drug-Repurposing Mechanism for Selecting the Lead Combination of Drugs for Alzheimer’s DiseaseSemantic proximity Read

An Integrated Knowledge Graph and Network Medicine Pipeline for Drug Repurposing: Benchmarking Across Human Diseases and Application to Amyotrophic Lateral SclerosisSemantic proximity Read

Synthesize Heterogeneous Biological Knowledge via Representation Learning for Alzheimer’s Disease Drug RepurposingSemantic proximity Read

Interpretable deep learning translation of GWAS and multi-omics findings to identify pathobiology and drug repurposing in Alzheimer’s diseaseSemantic proximity Read

Multi-Task Graph Neural Network For Alzheimer’s Disease Drug Repurposing Using Knowledge Graph And Multi-Level EvidenceSemantic proximity Read

Integrating genetically predicted transcriptomic signatures with longitudinal real-world data enables scalable drug repurposing for Alzheimer’s diseaseSemantic proximity Read

Multilayered validation of graph attention autoencoder–derived drug repurposing candidates for COVID-19Semantic proximity Read

Phenome-wide identification of therapeutic genetic targets, leveraging knowledge graphs, graph neural networks, and UK Biobank data.Semantic proximity Read

<i>MedGraphNet</i> : Leveraging Multi-Relational Graph Neural Networks and Text Knowledge for Biomedical PredictionsSemantic proximity Read

Drug repurposing for rare diseases via a gene-bridged heterogeneous knowledge graph and graph attention networkSemantic proximity Read

Novel graph attention autoencoder framework with multilayered validation identifies drug repurposing candidates for COVID-19 treatmentSemantic proximity Read

Integrating explainable AI with multiomics systems biology and EHR data mining for personalized drug repurposing in Alzheimer’s diseaseSemantic proximity Read