GEE: An informatics tool for gene expression data explore

Soo Youn Lee, Chan Hee Park, Jun Hee Yoon, Sunmin Yun, Ju Han Kim

Research output: Contribution to journalArticle


Objectives: Major public high-throughput functional genomic data repositories, including the Gene Expression Omnibus (GEO) and ArrayExpress have rapidly expanded. As a result, a large number of diverse high-throughput functional genomic data retrieval systems have been developed. However, high-throughput functional genomic data retrieval remains challenging. Methods: We developed Gene Expression data Explore (GEE), the first powerful, flexible web and mobile search application for searching whole-genome epigenetic data and microarray data in public databases, such as GEO and ArrayExpress. Results: GEE provides an elaborate, convenient interface of query generation competences not available via various highthroughput functional genomic data retrieval systems, including GEO, ArrayExpress, and Atlas. In particular, GEE provides a suitable query generator using eVOC, the Experimental Factor Ontology (EFO), which is well represented with a variety of high-throughput functional genomic data experimental conditions. In addition, GEE provides an experimental design query constructor (EDQC), which provides elaborate retrieval filter conditions when the user designs real experiments. Conclusions: The web version of GEE is available at, and its app version is available from the Apple App Store.

Original languageEnglish
Pages (from-to)81-88
Number of pages8
JournalHealthcare Informatics Research
Issue number2
StatePublished - Apr 2016


  • Microarray analysis
  • Mobile applications
  • RNA sequence
  • Search engine

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