Evidence map›Paper›PMID 20854660›Full record

ArticleBMC bioinformatics2010

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

William P Kelly, Michael P H Stumpf

Abstract read
In one paragraph

Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

William P KellyCentre for Bioinformatics, Imperial College, London, UK.
Michael P H Stumpf

Funding

Biotechnology and Biological Sciences Research Council BB/E01612X/1Biotechnology and Biological Sciences Research Council BB/F005210/1Wellcome Trust
6 · The paper itself

Abstract

backgroundPhylogenies 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.

resultsWe 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.

conclusionsWhile 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.

Indexed as

Models, StatisticalPhylogenyBiological PhenomenaClassificationDatabases, ProteinEvolution, MolecularProtein Interaction MappingProteinsSaccharomyces cerevisiaeProteins

Identifiers

PMID20854660
PMCPMC2955699

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.