Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Sep 1;33(17):2731-2736.
doi: 10.1093/bioinformatics/btx310.

On patterns and re-use in bioinformatics databases

Michael J Bell  1 , Phillip Lord  1
Affiliations

On patterns and re-use in bioinformatics databases

Michael J Bell et al. Bioinformatics. .

Abstract

Motivation: As the quantity of data being depositing into biological databases continues to increase, it becomes ever more vital to develop methods that enable us to understand this data and ensure that the knowledge is correct. It is widely-held that data percolates between different databases, which causes particular concerns for data correctness; if this percolation occurs, incorrect data in one database may eventually affect many others while, conversely, corrections in one database may fail to percolate to others. In this paper, we test this widely-held belief by directly looking for sentence reuse both within and between databases. Further, we investigate patterns of how sentences are reused over time. Finally, we consider the limitations of this form of analysis and the implications that this may have for bioinformatics database design.

Results: We show that reuse of annotation is common within many different databases, and that also there is a detectable level of reuse between databases. In addition, we show that there are patterns of reuse that have previously been shown to be associated with percolation errors.

Availability and implementation: Analytical software is available on request.

Contact: phillip.lord@newcastle.ac.uk.

PubMed Disclaimer

Figures

Fig. 1.
Fig. 1.
Figure showing the percentage of singleton (red/right hand column) and unique (blue/left hand column) sentences in each analyzed database. The line graph represents the total number of sentences in the database (shown on log scales). Within this graph we can broadly see that the larger the database, the more redundant its annotation (Color version of this figure is available at Bioinformatics online.)
Fig. 2.
Fig. 2.
Example of sentence which follows the missing origin pattern. Here, the sentence originates in InterPro entry IPR004086 before later appearing in entry IPR005430. It remains in this entry even when then sentence is removed from IPR004086. Interestingly, we note that the sentence occurs in PRINTS both before and after it exists in InterPro
Fig. 3.
Fig. 3.
An example of a sentence in InterPro which does not follow any propagation pattern. However, if you also consider PRINTS, and the sentence was copied from PRINTS into InterPro, then the sentence technically follows the missing origin pattern. This would have significant impact on the potential correctness of sentences in all databases
See this image and copyright information in PMC

References

    1. Attwood T.K. et al. (2003) Prints and its automatic supplement, preprints. Nucleic Acids Res., 31, 400–402. - PMC - PubMed
    1. Baumgartner W.A. et al. (2007) Manual curation is not sufficient for annotation of genomic databases. Bioinformatics, 23, i41–i48. - PMC - PubMed
    1. Bell M. et al. (2012) An approach to describing and analysing bulk biological annotation quality: a case study using UniProtKB. Bioinformatics, 28, i562–i568. - PMC - PubMed
    1. Bell M.J. (2015). Provenance, propagation and quality of biological annotation. Ph.D. thesis, Newcastle University.
    1. Bell M.J. et al. (2013) Can inferred provenance and its visualisation be used to detect erroneous annotation? a case study using uniprotkb. Plos One, 8, e75541.. - PMC - PubMed