On patterns and re-use in bioinformatics databases.

Michael J Bell,Phillip Lord,Jonathan Wren

doi:10.1093/bioinformatics/btx310

Michael J Bell, Phillip Lord + Show 1 more

Open Access

https://doi.org/10.1093/bioinformatics/btx310

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Abstract

MotivationAs 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.ResultsWe 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 implementationAnalytical software is available on request.

Highlights

It is estimated that over 1500 active databases are currently in existence (Fernandez-Suarez and Galperin, 2013)
As highly similar genes occur in many different organisms, transferred both horizontally and vertically, so the annotation about these genes is reused between different databases (Richardson and Watson, 2013)
In a previous study (Bell et al, 2013), we have shown that the level of reuse in UniProtKB is extremely high— the most reused sentence in TrEMBL occurs more than seven million times, while the most common sentence in Swiss-Prot occurs more than 91 000 times

Summary

Introduction

It is estimated that over 1500 active databases are currently in existence (Fernandez-Suarez and Galperin, 2013) While these are generally thought of as containing biological data, they often contain collected and collated information about the data they carry, which is described as annotation. As highly similar genes occur in many different organisms, transferred both horizontally and vertically, so the annotation about these genes is reused between different databases (Richardson and Watson, 2013). This form of reuse substantially reduces the work required by database annotators, and creates a problem; for most databases it is difficult to determine the source or support for a particular statement (Bolleman et al, 2010). Databases often lack a formal representation of their provenance (Bolleman et al, 2010)

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