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An Entity Resolution Framework for Deduplicating Proteins

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Data Integration in the Life Sciences (DILS 2008)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 5109))

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Abstract

An important prerequisite to successfully integrating protein data is detecting duplicate records spread across different databases. In this paper, we describe a new framework for protein entity resolution, called PERF, which deduplicates protein mentions using a wide range of protein attributes. A mention refers to any recorded information about a protein, whether it is derived from a database, a high-throughput study, or literature text mining, among others. PERF can be easily extended to deduplicate protein-protein interactions (PPIs) as well. This framework translates mentions into instances of a reference schema to facilitate mention comparisons. PERF also uses “virtual attribute dependencies” to “enhance” mentions with additional attribute values. PERF computes a likelihood measure based upon the textual value similarity of mention attributes. A prototype implementation of the framework was tested, and these tests indicate that PERF can clearly separate duplicate mentions from non-duplicate mentions.

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Authors and Affiliations

  1. Department of Computer Science, University of Toronto,  

    Lucas Lochovsky & Thodoros Topaloglou

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  1. Lucas Lochovsky
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  2. Thodoros Topaloglou
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Amos Bairoch Sarah Cohen-Boulakia Christine Froidevaux

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Lochovsky, L., Topaloglou, T. (2008). An Entity Resolution Framework for Deduplicating Proteins. In: Bairoch, A., Cohen-Boulakia, S., Froidevaux, C. (eds) Data Integration in the Life Sciences. DILS 2008. Lecture Notes in Computer Science(), vol 5109. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69828-9_9

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  • DOI: https://doi.org/10.1007/978-3-540-69828-9_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69827-2

  • Online ISBN: 978-3-540-69828-9

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