The age-phenome database

Nophar Geifman, Eitan Rubin

Research output: Contribution to journalArticlepeer-review


Data linking specific ages or age ranges with disease are abundant in biomedical literature. However, these data are organized such that searching for age-phenotype relationships is difficult. Recently, we described the Age- Phenome Knowledge-base (APK), a computational platform for storage and retrieval of information concerning age-related phenotypic patterns. Here, we report that data derived from over 1.5 million human-related PubMed abstracts have been added to APK. Using a text-mining pipeline, 35,683 entries which describe relationships between age and phenotype (such as disease) have been introduced into the database. Comparing the results to those obtained by a human reader reveals that the overall accuracy of these entries is estimated to exceed 80%. The usefulness of these data for obtaining new insight regarding age-disease relationships is demonstrated using clustering analysis, which is shown to capture obvious, as well as potentially interesting relationships between diseases. In addition, a new tool for browsing and searching the APK database is presented. We thus present a unique resource and a new framework for studying age-disease relationships and other phenotypic processes.

Original languageAmerican English
Article number4
Pages (from-to)1-8
Number of pages8
Issue number1
StatePublished - 1 Jan 2012


  • Age
  • Knowledgebase
  • Phenotype
  • Text-minig

All Science Journal Classification (ASJC) codes

  • General

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