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The age-phenome database
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 retri...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3581109/ https://www.ncbi.nlm.nih.gov/pubmed/23984222 http://dx.doi.org/10.1186/2193-1801-1-4 |
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author | Geifman, Nophar Rubin, Eitan |
author_facet | Geifman, Nophar Rubin, Eitan |
author_sort | Geifman, Nophar |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3581109 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Springer |
record_format | MEDLINE/PubMed |
spelling | pubmed-35811092013-08-27 The age-phenome database Geifman, Nophar Rubin, Eitan Springerplus Research 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. Springer 2012-04-23 /pmc/articles/PMC3581109/ /pubmed/23984222 http://dx.doi.org/10.1186/2193-1801-1-4 Text en Copyright ©2012 Geifman and Rubin; licensee Springer. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Geifman, Nophar Rubin, Eitan The age-phenome database |
title | The age-phenome database |
title_full | The age-phenome database |
title_fullStr | The age-phenome database |
title_full_unstemmed | The age-phenome database |
title_short | The age-phenome database |
title_sort | age-phenome database |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3581109/ https://www.ncbi.nlm.nih.gov/pubmed/23984222 http://dx.doi.org/10.1186/2193-1801-1-4 |
work_keys_str_mv | AT geifmannophar theagephenomedatabase AT rubineitan theagephenomedatabase AT geifmannophar agephenomedatabase AT rubineitan agephenomedatabase |