Cleaning by clustering: methodology for addressing data quality issues in biomedical metadata

Cleaning by clustering: methodology for addressing data quality issues in biomedical metadata

Abstract Background The ability to efficiently search and filter datasets depends on access to high quality metadata. While most biomedical repositories require data submitters to provide a minimal set of metadata, some such as the Gene Expression Omnibus (GEO) allows users to specify additional met...

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Bibliographic Details
Main Authors: Wei Hu, Amrapali Zaveri, Honglei Qiu, Michel Dumontier
Format: Article
Language:English
Published: BMC 2017-09-01
Series:BMC Bioinformatics
Subjects:
GEO
Metadata
Data quality
Clustering
Biomedical
Experimental data
Online Access:http://link.springer.com/article/10.1186/s12859-017-1832-4

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http://link.springer.com/article/10.1186/s12859-017-1832-4

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