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Updated: Jun 30, 2026

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data

Published on: December 15, 2023

Towards Healthy Aging through Semantic Enrichment.

John Beverley^1,2,3, Julie C Bowker⁴, Hollen N Reischer⁴

¹Department of Philosophy, University at Buffalo, Buffalo NY, USA.

CEUR Workshop Proceedings

|June 29, 2026

Summary

This summary is machine-generated.

This study introduces two ontologies, SOLO and GERO, to define psychological concepts for healthy aging. These formalizations aid in data integration and developing new tools for aging research and interventions.

Keywords:

Basic Formal Ontology Gerotranscendence Healthy Aging Ontology Engineering Solitude

Related Experiment Videos

Last Updated: Jun 30, 2026

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data

Published on: December 15, 2023

Area of Science:

Psychology
Gerontology
Computer Science (Ontology Engineering)

Background:

Healthy aging research requires precise definitions of psychological constructs.
Existing terminology for concepts like solitude and gerotranscendence can be ambiguous.
There is a need for formal frameworks to integrate diverse aging research data.

Purpose of the Study:

Introduce two interoperable ontologies: SOLO (Solitude Ontology) and GERO (Gerotranscendence Ontology).
Formalize key psychological constructs relevant to healthy aging.
Enable semantic reasoning and cross-disciplinary data integration in aging research.

Main Methods:

Developed SOLO and GERO ontologies based on the Behavioral Change Intervention Ontology.
Clarified distinctions between solitude, loneliness, self-transcendence, and gerotranscendence.
Integrated validated psychometric instruments and competency questions into the ontologies.

Main Results:

SOLO and GERO provide formal definitions and realization conditions for psychological constructs across the lifespan.
The ontologies facilitate semantic reasoning and data integration for aging research.
Enabled the foundation for developing ontology-driven tools for aging research and intervention design.

Conclusions:

The developed ontologies offer a standardized framework for psychological constructs in healthy aging.
SOLO and GERO support advanced data analysis and tool development in gerontology.
These ontologies are crucial for advancing cross-disciplinary aging research and intervention strategies.