Percolation of annotation errors through hierarchically structured protein sequence databases.

Walter R Gilks 1 Benjamin Audit 2, 3 Daniela de Angelis 1 Sophia Tsoka 2 Christos A Ouzounis 2
1 Medical Research Council Biostatistics Unit
2 EMBL-EBI - European Bioinformatics Institute [Hinxton]
3 Laboratoire Joliot Curie
Abstract : Databases of protein sequences have grown rapidly in recent years as a result of genome sequencing projects. Annotating protein sequences with descriptions of their biological function ideally requires careful experimentation, but this work lags far behind. Instead, biological function is often imputed by copying annotations from similar protein sequences. This gives rise to annotation errors, and more seriously, to chains of misannotation. [Percolation of annotation errors in a database of protein sequences (2002)] developed a probabilistic framework for exploring the consequences of this percolation of errors through protein databases, and applied their theory to a simple database model. Here we apply the theory to hierarchically structured protein sequence databases, and draw conclusions about database quality at different levels of the hierarchy.
Keywords : Automated annotation hierarchical protein classification
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Journal articles
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https://hal-ens-lyon.archives-ouvertes.fr/ensl-00175660
Contributor : Benjamin Audit <>
Submitted on : Saturday, September 29, 2007 - 12:54:42 PM
Last modification on : Friday, December 13, 2019 - 6:52:04 PM

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Walter R Gilks, Benjamin Audit, Daniela de Angelis, Sophia Tsoka, Christos A Ouzounis. Percolation of annotation errors through hierarchically structured protein sequence databases.. Mathematical Biosciences, Elsevier, 2005, 2 (193), pp.223-34. ⟨10.1016/j.mbs.2004.08.001⟩. ⟨ensl-00175660⟩

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