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A new measure for functional similarity of gene products based on Gene Ontology

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons45392

Schlicker,  Andreas
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44341

Domingues,  Francisco S.
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45241

Rahnenführer,  Jörg
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44907

Lengauer,  Thomas
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society;

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Zitation

Schlicker, A., Domingues, F. S., Rahnenführer, J., & Lengauer, T. (2006). A new measure for functional similarity of gene products based on Gene Ontology. BMC Bioinformatics, 7, 1-16.

Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000F-2206-E
Zusammenfassung
\paragraph*{Background:} Gene Ontology (GO) is a standard vocabulary of functional terms and allows for coherent annotation of gene products. These annotations provide a basis for new methods that compare gene products regarding their molecular function and biological role. \paragraph*{Results:} We present a new method for comparing sets of GO terms and for assessing the functional similarity of gene products. The method relies on two semantic similarity measures; ${\textit sim_{Rel}}$ and ${\textit funSim}$. One measure (${\textit sim_{Rel}}$) is applied in the comparison of the biological processes found in different groups of organisms. The other measure (${\textit funSim}$) is used to find functionally related gene products within the same or between different genomes. Results indicate that the method, in addition to being in good agreement with established sequence similarity approaches, also provides a means for the identification of functionally related proteins independent of evolutionary relationships. The method is also applied to estimating functional similarity between all proteins in Saccharomyces cerevisiae and to visualizing the molecular function space of yeast in a map of the functional space. A similar approach is used to visualize the functional relationships between protein families. \paragraph*{Conclusions:} The approach enables the comparison of the underlying molecular biology of different taxonomic groups and provides a new comparative genomics tool identifying functionally related gene products independent of homology. The proposed map of the functional space provides a new global view on the functional relationships between gene products or protein families.