Article

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

2023-12-19

Abstract excerpt

<h4>INTRODUCTION</h4> The objective of this study is to characterize the dysregulation of gene expression in AD affected brain tissues through an interpretable deep learning framework. <h4>METHODS</h4> We trained multi-layer perceptron models for the classification of neuropathologically confirmed AD vs. controls using transcriptomic data from three brain regions of ROSMAP study. The disease spectrum was then mo...

Topics

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

Identifiers and source

Literature Corpus work: ce8f2eb0-7cd0-55f8-89fb-8a5c89a99cd9
DOI: 10.1101/2023.12.18.572226

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Interpretable deep learning framework for understanding molecular changes in human brains with Alzheimer’s disease: implications for microglia activation and sex differencesDOI 10.1101/2023.12.18.572226Read

Unified AI framework to uncover deep interrelationships between gene expression and Alzheimer’s disease neuropathologiesSemantic proximity Read

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

Single-cell multiomics reveals disrupted glial gene regulatory programs in Alzheimer’s disease via interpretable machine learningSemantic proximity Read

c-Triadem: A constrained, explainable deep learning model to identify novel biomarkers in Alzheimer’s diseaseSemantic proximity Read

Interpretable machine learning-driven biomarker identification and validation 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

BrainBridge Characterizes Key Factors affecting Alzheimer’s Disease and Associated PhenotypesSemantic 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

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

Cell-Type-Resolved Pseudobulk Classification Across Independent Cohorts Identifies Microglial PTPRG as a Transcriptional Hub in Alzheimer’s DiseaseSemantic proximity Read

Single Cell Landscape of Sex-specific Drivers of Alzheimer’s DiseaseSemantic proximity Read