Article

Unified AI framework to uncover deep interrelationships between gene expression and Alzheimer’s disease neuropathologies

2020-12-01

Abstract excerpt

<h4>ABSTRACT</h4> Deep neural networks offer a promising approach for capturing complex, non-linear relationships among variables. Because they require immense sample sizes, their potential has yet to be fully tapped for understanding complex relationships between gene expression and human phenotypes. Encouragingly, a growing number of diseases are being studied through consortium efforts. Here we introduce a new...

Topics

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

Identifiers and source

Literature Corpus work: 10bdcc02-bee1-5de8-b5e6-4400d8c4033c
DOI: 10.1101/2020.11.30.404087

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Unified AI framework to uncover deep interrelationships between gene expression and Alzheimer’s disease neuropathologiesDOI 10.1101/2020.11.30.404087Read

Interpretable deep learning framework for understanding molecular changes in human brains with Alzheimer’s disease: implications for microglia activation and sex differencesSemantic proximity Read

Deep learning-based brain transcriptomic signatures associated with the neuropathological and clinical severity of Alzheimer’s diseaseSemantic proximity Read

MD-AD: Multi-task deep learning for Alzheimer’s disease neuropathologySemantic proximity Read

Deep learning-based brain transcriptomic signatures associated with the neuropathological and clinical severity of Alzheimer’s diseaseSemantic proximity Read

HINN: Hierarchical Input Neural Network identifies multi-omics biomarker for cognitive declineSemantic proximity Read

Integrating GWAS and Transcriptomic Data Using PrediXcan and Multimodal Deep Learning Reveals Genetic Basis and Drug Repositioning Opportunities for Alzheimer’s DiseaseSemantic proximity Read

A Pathway-Based Machine Learning Approach Identifies Region-Specific Markers and Patterns in Alzheimer’s Disease Patients Based on Spatial and Severity MetadataSemantic proximity Read

A Network-based Deep Learning Framework Catalyzes GWAS and Multi-Omics Findings to Biology and Drug Repurposing for Alzheimer’s DiseaseSemantic proximity Read

An interpretable deep learning framework identifies proteomic drivers of Alzheimer’s diseaseSemantic proximity Read

Predicting gene regulatory networks from multi-omics to link genetic risk variants and neuroimmunology to Alzheimer’s disease phenotypesSemantic proximity Read

Integrative multi-omics approaches identify molecular pathways and improve Alzheimer’s Disease risk predictionSemantic proximity Read

Deep Trans-Omic Network Fusion for Molecular Mechanism of Alzheimer's Disease.Semantic proximity Read