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pmid:30649296

Restructured GEO: restructuring Gene Expression Omnibus metadata for genome dynamics analysis.

Guocai Chen · Juan Camilo Ramírez · Nan Deng · Xing Qiu · Canglin Wu · W Jim Zheng · Hulin Wu

Database : the journal of biological databases and curation · 2019 doi:10.1093/database/bay145

Paper

complete

Experiment

partial

Data

partial

Analysis

absent

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:30649296
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title
Restructured GEO: restructuring Gene Expression Omnibus metadata for genome dynamics analysis.
doi
10.1093/database/bay145
pmid
30649296
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[0]
Guocai Chen
[1]
Juan Camilo Ramírez
[2]
Nan Deng
[3]
Xing Qiu
[4]
Canglin Wu
[5]
W Jim Zheng
[6]
Hulin Wu
journal
Database : the journal of biological databases and curation
year
2019
abstract
Motivation: Gene Expression Omnibus (GEO) and other publicly available data store their metadata in the format of unstructured English text, which is very difficult for automated reuse. Results: We employed text mining techniques to analyze the metadata of GEO and developed Restructured GEO database (ReGEO). ReGEO reorganizes and categorizes GEO series and makes them searchable by two new attributes extracted automatically from each series' metadata. These attributes are the number of time points tested in the experiment and the disease being investigated. ReGEO also makes series searchable by other attributes available in GEO, such as platform organism, experiment type, associated PubMed ID as well as general keywords in the study's description. Our approach greatly expands the usability of GEO data, demonstrating a credible approach to improve the utility of vast amount of publicly available data in the era of Big Data research.
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We obtained metadata and the titles of samples for Gene Series Expression (GSE) data from GEO and GEOmetadb (14).
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We obtained metadata and the titles of samples for Gene Series Expression (GSE) data from GEO and GEOmetadb (14).
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