title: The age-phenome database.
abstract: 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.
authors.affiliation: Shraga Segal Department of Microbiology and Immunology, Faculty of Health Sciences and The National Institute for Biotechnology in the Negev, Ben Gurion University, Beersheva 84105, Israel.
authors.forename: Nophar
authors.initials: N
authors.lastname: Geifman
authors.forename: Eitan
authors.initials: E
authors.lastname: Rubin
keywords: Age; Knowledgebase; Phenotype; Text-minig