Literature consistency of bioinformatics sequence databases is effective for assessing record quality.

ABSTRACT: Bioinformatics sequence databases such as Genbank or UniProt contain hundreds of millions of records of genomic data. These records are derived from direct submissions from individual laboratories, as well as from bulk submissions from large-scale sequencing centres; their diversity and scale means that they suffer from a range of data quality issues including errors, discrepancies, redundancies, ambiguities, incompleteness and inconsistencies with the published literature. In this work, we seek to investigate and analyze the data quality of sequence databases from the perspective of a curator, who must detect anomalous and suspicious records. Specifically, we emphasize the detection of inconsistent records with respect to the literature. Focusing on GenBank, we propose a set of 24 quality

SUBMITTER: Bouadjenek MR 

PROVIDER: S-EPMC5467556 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature