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The age-phenome database
Nophar Geifman
,
Eitan Rubin
The Shraga Segal Department of Microbiology, Immunology and Genetics
Ben-Gurion University of the Negev
Research output
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Contribution to journal
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Article
›
peer-review
Overview
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Keyphrases
Phenomics
100%
Knowledge Base
75%
Disease Relationships
50%
Cluster Analysis
25%
Overall Accuracy
25%
Age-related
25%
Information Retrieval
25%
Browsing
25%
Phenotypic Patterns
25%
Text Mining
25%
Computational Platform
25%
Data Linking
25%
Information Storage
25%
Unique Resources
25%
Biomedical Literature
25%
PubMed Abstracts
25%
Computer Science
Knowledge Base
100%
Information Retrieval
33%
Text Mining
33%
Clustering Analysis
33%
Linking Data
33%
Biomedical Literature
33%
Computational Platform
33%