title: Percolation of annotation errors through hierarchically structured protein sequence databases.
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.
authors.affiliation: Medical Research Council Biostatistics Unit, Institute of Public Health, University of Forvive Site, Robinson Way, Cambridge CB2 2SR, UK. wally.gilks@mrc-bsu.cam.ac.uk
authors.forename: Walter R
authors.initials: WR
authors.lastname: Gilks
authors.forename: Benjamin
authors.initials: B
authors.lastname: Audit
authors.forename: Daniela
authors.initials: D
authors.lastname: de Angelis
authors.forename: Sophia
authors.initials: S
authors.lastname: Tsoka
authors.forename: Christos A
authors.initials: CA
authors.lastname: Ouzounis
mesh_terms: D000595:Amino Acid Sequence; D030562:Databases, Protein / Q000592:standards*; D017386:Sequence Homology, Amino Acid