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Automated detection of records in biological sequence databases that are inconsistent with the literature

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journal contribution
posted on 2017-01-01, 00:00 authored by Mohamed Reda BouadjenekMohamed Reda Bouadjenek, K Verspoor, J Zobel
© 2017 Elsevier Inc. We investigate and analyse the data quality of nucleotide sequence databases with the objective of automatic detection of data anomalies and suspicious records. Specifically, we demonstrate that the published literature associated with each data record can be used to automatically evaluate its quality, by cross-checking the consistency of the key content of the database record with the referenced publications. Focusing on GenBank, we describe a set of quality indicators based on the relevance paradigm of information retrieval (IR). Then, we use these quality indicators to train an anomaly detection algorithm to classify records as “confident” or “suspicious”. Our experiments on the PubMed Central collection show assessing the coherence between the literature and database records, through our algorithms, is an effective mechanism for assisting curators to perform data cleansing. Although fewer than 0.25% of the records in our data set are known to be faulty, we would expect that there are many more in GenBank that have not yet been identified. By automated comparison with literature they can be identified with a precision of up to 10% and a recall of up to 30%, while strongly outperforming several baselines. While these results leave substantial room for improvement, they reflect both the very imbalanced nature of the data, and the limited explicitly labelled data that is available. Overall, the obtained results show promise for the development of a new kind of approach to detecting low-quality and suspicious sequence records based on literature analysis and consistency. From a practical point of view, this will greatly help curators in identifying inconsistent records in large-scale sequence databases by highlighting records that are likely to be inconsistent with the literature.

History

Journal

Journal of Biomedical Informatics

Volume

71

Pagination

229-240

Location

Amsterdam, The Netherlands

Open access

  • Yes

ISSN

1532-0464

Language

eng

Publication classification

C1.1 Refereed article in a scholarly journal

Publisher

Elsevier

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