Gene and Protein Nomenclature in Public Databases
Author Information
Author(s): Katrin Fundel, Ralf Zimmer
Primary Institution: Institut für Informatik, Ludwig-Maximilians-Universität München
Hypothesis
How do different public databases compare in terms of gene and protein name ambiguity and overlap?
Conclusion
Combining data from different databases results in larger and less ambiguous gene and protein name dictionaries.
Supporting Evidence
- The number of genes/proteins and synonyms varies significantly across databases.
- Ambiguity of synonyms differs between organisms.
- Curation of combined dictionaries increases size and decreases ambiguity.
Takeaway
This study shows that different databases have different names for the same genes and proteins, and combining them helps make a better list of names.
Methodology
The study compiled gene and protein name dictionaries from various databases and analyzed their ambiguity and overlap.
Limitations
The study does not establish a gold standard for gene name dictionaries and relies on existing databases.
Digital Object Identifier (DOI)
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