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Global protein function prediction in protein-protein interaction networks
The determination of protein functions is one of the most challenging
problems of the post-genomic era. The sequencing of entire genomes and the
possibility to access gene's co-expression patterns has moved the attention
from the study of single proteins or small complexes to that of the entire
proteome. In this context, the search for reliable methods for proteins'
function assignment is of uttermost importance. Previous approaches to deduce
the unknown function of a class of proteins have exploited sequence
similarities or clustering of co-regulated genes, phylogenetic profiles,
protein-protein interactions, and protein complexes. We propose to assign
functional classes to proteins from their network of physical interactions, by
minimizing the number of interacting proteins with different categories. The
function assignment is made on a global scale and depends on the entire
connectivity pattern of the protein network. Multiple functional assignments
are made possible as a consequence of the existence of multiple equivalent
solutions. The method is applied to the yeast Saccharomices Cerevisiae
protein-protein interaction network. Robustness is tested in presence of a high
percentage of unclassified proteins and under deletion/insertion of
interactions.Comment: 5 pages, 2 figures, 2 supplementary table
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