Evidence map›Paper›PMID 22151086›Full record

ArticleBMC bioinformatics2011

A method for computing an inventory of metazoan mitochondrial gene order rearrangements.

Matthias Bernt, Martin Middendorf

Abstract read
In one paragraph

Article in BMC bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Matthias BerntParallel Computing and Complex Systems Group, Institute of Computer Science, University Leipzig, Leipzig, 04103, Germany. bernt@informatik.uni-leipzig.de
Martin Middendorf

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChanges in the order of mitochondrial genes are a good source of information for phylogenetic investigations. Phylogenetic hypotheses are often supported by parsimonious mitochondrial gene order rearrangement scenarios. CREx is a heuristic for computing short pairwise rearrangement scenarios for metazoan mitochondrial gene orders. Different from other methods, CREx considers four types of rearrangement operations: inversions, transpositions, inverse transpositions, and tandem duplication random loss operations.

resultsAn extensive analysis of the CREx reconstructions for artificial data has been presented and it is shown how the quality of the reconstructed rearrangement scenarios depends on the type of rearrangement model and additional parameter values. Moreover, a fast method is proposed to apply CREx to a large number of gene orders to find likely rearrangement scenarios and store them in a graph structure called RI-Graph. This method is applied to analyse all known metazoan mitochondrial gene orders. It is shown that the obtained RI-Graph contains many rearrangement scenarios that are described in the literature.

conclusionsThe prospects and limitations of CREx have been analysed empirically and a comparison with the literature on gene order evolution highlights its benefits. The newly developed method to apply CREx to a large number of gene orders is successful in computing an RI-graph that contains many rearrangement scenarios for metazoan gene orders that have also been described in the literature. This shows that the new method is very helpful for a fast analysis of a large number of gene orders which is relevant due to the strongly increasing number of known gene orders.

Indexed as

Gene OrderGenes, MitochondrialPhylogenyAnimalsArthropodsEvolution, MolecularGene RearrangementMollusca

Identifiers

PMID22151086
PMCPMC3283314

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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.