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Related Experiment Video

Updated: Jun 1, 2026

High-Throughput Behavioral Aging and Lifespan Assays Using the Lifespan Machine
08:53

High-Throughput Behavioral Aging and Lifespan Assays Using the Lifespan Machine

Published on: January 26, 2024

Towards an Age-Phenome Knowledge-base.

Nophar Geifman1, Eitan Rubin

  • 1Shraga Segal Department of Microbiology and Immunology, The National Institute for Biotechnology in the Negev, Ben Gurion University, Israel.

BMC Bioinformatics
|June 10, 2011
PubMed
Summary
This summary is machine-generated.

The Age-Phenome Knowledge-base (APK) organizes age-phenotype associations, enabling systematic study of how traits and diseases change with age. This resource facilitates research into age-related health patterns.

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Area of Science:

  • Biomedical Informatics
  • Gerontology
  • Computational Biology

Background:

  • Existing data on age-phenotype associations are not systematically organized, hindering methodical study.
  • Difficulty in searching scientific literature for age-specific phenotypic changes limits research.
  • Lack of a centralized resource for age-related health information.

Purpose of the Study:

  • To develop a structured knowledge base for age-related phenotypic patterns and events.
  • To enable systematic retrieval and study of age-phenotype associations.
  • To create a platform for collaborative curation of age-related health knowledge.

Main Methods:

  • Development of the Age-Phenome Knowledge-base (APK) for modeling and storing age-phenotype data.
  • Utilized a text mining tool to extract age-phenotype associations from scientific abstracts (e.g., non-insulin-dependent Diabetes Mellitus).
  • Integrated age-phenotype links from clinical data (NHANES III survey).

Main Results:

  • The APK successfully stores evidence connecting specific ages or age groups with phenotypes.
  • Age-Phenome Knowledge-base (APK) provides 'Age-Cards' summarizing information for each age.
  • Data is accessible via a wiki for community review and contribution, alongside complex database queries.

Conclusions:

  • The APK serves as a valuable repository for collecting and curating knowledge on age-phenotype connections.
  • Combining a knowledge model with community participation enhances the knowledge base's utility and refinement.
  • The platform supports systematic research into the biological and clinical implications of aging.