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Bioinformatics
Article . 2007 . Peer-reviewed
Data sources: Crossref
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Bioinformatics
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License: CC BY NC
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Bioinformatics
Article . 2007
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Manual curation is not sufficient for annotation of genomic databases

Authors: William A. Baumgartner Jr.; K. Bretonnel Cohen; Lynne M. Fox; George K. Acquaah-Mensah; Lawrence Hunter;

Manual curation is not sufficient for annotation of genomic databases

Abstract

Abstract Motivation: Knowledge base construction has been an area of intense activity and great importance in the growth of computational biology. However, there is little or no history of work on the subject of evaluation of knowledge bases, either with respect to their contents or with respect to the processes by which they are constructed. This article proposes the application of a metric from software engineering known as the found/fixed graph to the problem of evaluating the processes by which genomic knowledge bases are built, as well as the completeness of their contents. Results: Well-understood patterns of change in the found/fixed graph are found to occur in two large publicly available knowledge bases. These patterns suggest that the current manual curation processes will take far too long to complete the annotations of even just the most important model organisms, and that at their current rate of production, they will never be sufficient for completing the annotation of all currently available proteomes. Contact: larry.hunter@uchsc.edu

Keywords

Sequence Analysis, Protein, Chromosome Mapping, Proteins, Documentation, Genomics, Databases, Protein

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
190
Top 1%
Top 1%
Top 1%
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