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 The European Bioinformatics Institute, EMBL Cambridge Outstation
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
Type de document :
Article dans une revue
Mathematical Biosciences, Elsevier, 2005, 2 (193), pp.223-34. 〈10.1016/j.mbs.2004.08.001〉
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https://hal-ens-lyon.archives-ouvertes.fr/ensl-00175660
Contributeur : Benjamin Audit <>
Soumis le : samedi 29 septembre 2007 - 12:54:42
Dernière modification le : samedi 6 octobre 2018 - 19:24:01

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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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