%0 Journal Article
%T Trees on networks: resolving statistical patterns of phylogenetic similarities among interacting proteins
%A William P Kelly
%A Michael PH Stumpf
%J BMC Bioinformatics
%D 2010
%I BioMed Central
%R 10.1186/1471-2105-11-470
%X 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.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.The biological structure and function of organisms at the cellular level are the product of interactions between proteins and other molecules. The resulting networks of biological interactions found in an organism have been studied using concepts from graph theory, and the quantitative analysis of biological networks has become important for the description of biological systems [1-3]. While protein-protein interaction (PPI) data are incomplete, and in most instances suffer from either abundant noise or potential experimental bias as a consequence of prior biological knowledge [4,5], there have been numerous reports over the last decade highlighting the use of PPI network data, including how these can be used to understand molecular processes, disease phenotypes, and evolutionary properties of biological systems (e.g. [6,7]).In addition to their functional role, protein interaction networks (PINs) have also been analyzed from an evolutionary perspective. A host of analyses have studied, e.g. the potential link between the evolutionary rate of a protein and its degree or position in PINs [8-16]. Similarly, properties of interacting proteins have been investigated in order to determi
%U http://www.biomedcentral.com/1471-2105/11/470