Evidence map›Paper›PMID 20041191›Full record

ArticlePloS one2009

Covariation of branch lengths in phylogenies of functionally related genes.

Wai Lok Sibon Li, Allen G Rodrigo

Abstract read
In one paragraph

Article in PloS one, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
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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.

Wai Lok Sibon LiBioinformatics Institute, University of Auckland, Auckland, New Zealand.
Allen G Rodrigo

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent studies have shown evidence for the coevolution of functionally-related genes. This coevolution is a result of constraints to maintain functional relationships between interacting proteins. The studies have focused on the correlation in gene tree branch lengths of proteins that are directly interacting with each other. We here hypothesize that the correlation in branch lengths is not limited only to proteins that directly interact, but also to proteins that operate within the same pathway. Using generalized linear models as a basis of identifying correlation, we attempted to predict the gene ontology (GO) terms of a gene based on its gene tree branch lengths. We applied our method to a dataset consisting of proteins from ten prokaryotic species. We found that the degree of accuracy to which we could predict the function of the proteins from their gene tree varied substantially with different GO terms. In particular, our model could accurately predict genes involved in translation and certain ribosomal activities with the area of the receiver-operator curve of up to 92%. Further analysis showed that the similarity between the trees of genes labeled with similar GO terms was not limited to genes that physically interacted, but also extended to genes functioning within the same pathway. We discuss the relevance of our findings as it relates to the use of phylogenetic methods in comparative genomics.

Indexed as

PhylogenyAnimalsBacteriaDatabases, GeneticGenesHumansLinear ModelsRibosomesROC Curve

Identifiers

PMID20041191
PMCPMC2793527

What OpenQuestion holds

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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.