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Trees on networks: resolving statistical patterns of phylogenetic similarities among interacting proteins.


ABSTRACT:

Background

Phylogenies capture the evolutionary ancestry linking extant species. Correlations and similarities among a set of species are mediated by and need to be understood in terms of the phylogenic tree. In a similar way it has been argued that biological networks also induce correlations among sets of interacting genes or their protein products.

Results

We develop suitable statistical resampling schemes that can incorporate these two potential sources of correlation into a single inferential framework. To illustrate our approach we apply it to protein interaction data in yeast and investigate whether the phylogenetic trees of interacting proteins in a panel of yeast species are more similar than would be expected by chance.

Conclusions

While we find only negligible evidence for such increased levels of similarities, our statistical approach allows us to resolve the previously reported contradictory results on the levels of co-evolution induced by protein-protein interactions. We conclude with a discussion as to how we may employ the statistical framework developed here in further functional and evolutionary analyses of biological networks and systems.

SUBMITTER: Kelly WP 

PROVIDER: S-EPMC2955699 | biostudies-literature | 2010 Sep

REPOSITORIES: biostudies-literature

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Trees on networks: resolving statistical patterns of phylogenetic similarities among interacting proteins.

Kelly William P WP   Stumpf Michael P H MP  

BMC bioinformatics 20100920


<h4>Background</h4>Phylogenies capture the evolutionary ancestry linking extant species. Correlations and similarities among a set of species are mediated by and need to be understood in terms of the phylogenic tree. In a similar way it has been argued that biological networks also induce correlations among sets of interacting genes or their protein products.<h4>Results</h4>We develop suitable statistical resampling schemes that can incorporate these two potential sources of correlation into a s  ...[more]

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