Quantifying Protein Function Specificity in the Gene Ontology
By Brenton Louie, Silas Bergen, R. Higdon, E. Kolker. 2010
9 citations recorded by the source corpus.
Quantitative or numerical metrics of protein function specificity made possible by the Gene Ontology are useful in that they enable development of distance or similarity measures between protein functions. Here we describe how to calculate four measures of function specificity for GO terms: 1) number of ancestor terms; 2) number of offspring terms; 3) proportion of terms; and 4) Information Content (IC). We discuss the relationship between the metrics and the strengths and weaknesses of each.
Subfields: Molecular Biology
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In Molecular Biology
- Hongzhan Huang
- Cathy H. Wu
- Yuqi Wang
- Baris E. Suzek
- Peter B. McGarvey
- The UniProt Consortium
- UniProt Consortium
- Burkhard Rost
Citations in the corpus
- UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches (2014, background): “…GO term specificity (P) metric computed based on a term’s hierarchical level: P ¼ 1 Number of Offspring Number of Offspring þNumber of Ancestors (1) (Louie et al., 2010) where a GO term is more specific (has a larger specificity metric) if the number of ancestors is greater than the number of…”