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GEE: An Informatics Tool for Gene Expression Data Explore.

Soo Youn Lee1, Chan Hee Park1, Jun Hee Yoon1

  • 1Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul, Korea.

Healthcare Informatics Research
|May 21, 2016
PubMed
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Gene Expression data Explore (GEE) simplifies searching large functional genomic datasets from public repositories like GEO and ArrayExpress. This tool offers advanced query features for efficient data retrieval and experimental design.

Area of Science:

  • Genomics
  • Bioinformatics
  • Data Science

Background:

  • Public functional genomic data repositories like Gene Expression Omnibus (GEO) and ArrayExpress have grown significantly.
  • The increasing volume of data necessitates improved retrieval systems.
  • Current high-throughput functional genomic data retrieval methods present challenges.

Purpose of the Study:

  • To introduce Gene Expression data Explore (GEE), a novel search application for functional genomic data.
  • To provide a powerful and flexible tool for accessing microarray and whole-genome epigenetic data.

Main Methods:

  • Development of GEE as a web and mobile application.
  • Integration with public databases such as GEO and ArrayExpress.
  • Implementation of an Experimental Factor Ontology (EFO) based query generator and an experimental design query constructor (EDQC).
Keywords:
Microarray AnalysisMobile ApplicationsRNA SequenceSearch Engine

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Main Results:

  • GEE offers advanced query generation capabilities beyond existing systems like GEO, ArrayExpress, and Atlas.
  • The EFO integration facilitates precise querying based on experimental conditions.
  • The EDQC assists users in defining detailed retrieval filters for experimental design.

Conclusions:

  • GEE enhances the accessibility and usability of public functional genomic data.
  • The tool provides a superior interface for data exploration and experimental planning.
  • GEE is available as a web application and a mobile app.