ArticleBioinformatics (Oxford, England)2012
An approach to describing and analysing bulk biological annotation quality: a case study using UniProtKB.
Article in Bioinformatics (Oxford, England), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- On patterns and re-use in bioinformatics databases.Bioinformatics (Oxford, England) · 2017Article
- Assessment of genome annotation using gene function similarity within the gene neighborhood.BMC bioinformatics · 2017Article
- The self-inhibitory nature of metabolic networks and its alleviation through compartmentalization.Nature communications · 2017Article
- Human Variome Project Quality Assessment Criteria for Variation Databases.Human mutation · 2016Article
- Optimization of gene set annotations via entropy minimization over variable clusters (EMVC).Bioinformatics (Oxford, England) · 2014Article
- Can inferred provenance and its visualisation be used to detect erroneous annotation? A case study using UniProtKB.PloS one · 2013Article
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4 authors.
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Abstract
motivationAnnotations are a key feature of many biological databases, used to convey our knowledge of a sequence to the reader. Ideally, annotations are curated manually, however manual curation is costly, time consuming and requires expert knowledge and training. Given these issues and the exponential increase of data, many databases implement automated annotation pipelines in an attempt to avoid un-annotated entries. Both manual and automated annotations vary in quality between databases and annotators, making assessment of annotation reliability problematic for users. The community lacks a generic measure for determining annotation quality and correctness, which we look at addressing within this article. Specifically we investigate word reuse within bulk textual annotations and relate this to Zipf's Principle of Least Effort. We use the UniProt Knowledgebase (UniProtKB) as a case study to demonstrate this approach since it allows us to compare annotation change, both over time and between automated and manually curated annotations.
resultsBy applying power-law distributions to word reuse in annotation, we show clear trends in UniProtKB over time, which are consistent with existing studies of quality on free text English. Further, we show a clear distinction between manual and automated analysis and investigate cohorts of protein records as they mature. These results suggest that this approach holds distinct promise as a mechanism for judging annotation quality. AVAILABILITY: Source code is available at the authors website: http://homepages.cs.ncl.ac.uk/m.j.bell1/annotation. CONTACT: phillip.lord@newcastle.ac.uk.
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