Journal
MATHEMATICAL BIOSCIENCES
Volume 193, Issue 2, Pages 223-234Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.mbs.2004.08.001
Keywords
annotation errors; biological function; database quality; hierarchical classification; homology; probability model; protein database; protein sequence
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Funding
- Medical Research Council [MC_U105260556] Funding Source: Medline
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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. (c) 2005 Elsevier Inc. All rights reserved.
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