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New method for functional comparison based on Gene Ontology
schlandi at mpi-inf.mpg.de
Wed Jul 5 00:21:18 PDT 2006
we have developed a new method for functional comparison of genes or gene
products based on Gene Ontology. A paper on this method is published in BMC
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.
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; simRel and funSim. One measure (simRel) is applied
in the comparison of the biological processes found in different groups of
organisms. The other measure (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.
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.
Andreas Schlicker, M.Sc.
Max-Planck-Institute for Informatics
Department 3: Computational Biology and Applied Algorithmics
Phone: +49 681 9325 321
Fax: +49 681 9325 399
Email: schlandi at mpi-inf.mpg.de
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