Evidence map›Paper›PMID 27200217›Full record

ArticleHealthcare informatics research2016

GEE: An Informatics Tool for Gene Expression Data Explore.

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

Abstract read
In one paragraph

Article in Healthcare informatics research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Soo Youn LeeSeoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul, Korea.
Chan Hee ParkSeoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul, Korea.
Jun Hee YoonSeoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul, Korea.
Sunmin YunSeoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul, Korea.
Ju Han KimSeoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul, Korea.; Systems Biomedical Informatics-National Core Research Center (SBI-NCRC), Seoul National University College of Medicine, Seoul, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesMajor 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.

methodsWe 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.

resultsGEE provides an elaborate, convenient interface of query generation competences not available via various high-throughput 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.

conclusionsThe web version of GEE is available at http://www.snubi.org/software/gee, and its app version is available from the Apple App Store.

Indexed as

Microarray AnalysisMobile ApplicationsRNA SequenceSearch Engine

Identifiers

PMID27200217
PMCPMC4871849

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.