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A method for identification of highly conserved elements and evolutionary analysis of superphylum Alveolata

Overview of attention for article published in BMC Bioinformatics, September 2016
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Title
A method for identification of highly conserved elements and evolutionary analysis of superphylum Alveolata
Published in
BMC Bioinformatics, September 2016
DOI 10.1186/s12859-016-1257-5
Pubmed ID
Authors

Lev I. Rubanov, Alexandr V. Seliverstov, Oleg A. Zverkov, Vassily A. Lyubetsky

Abstract

Perfectly or highly conserved DNA elements were found in vertebrates, invertebrates, and plants by various methods. However, little is known about such elements in protists. The evolutionary distance between apicomplexans can be very high, in particular, due to the positive selection pressure on them. This complicates the identification of highly conserved elements in alveolates, which is overcome by the proposed algorithm. A novel algorithm is developed to identify highly conserved DNA elements. It is based on the identification of dense subgraphs in a specially built multipartite graph (whose parts correspond to genomes). Specifically, the algorithm does not rely on genome alignments, nor pre-identified perfectly conserved elements; instead, it performs a fast search for pairs of words (in different genomes) of maximum length with the difference below the specified edit distance. Such pair defines an edge whose weight equals the maximum (or total) length of words assigned to its ends. The graph composed of these edges is then compacted by merging some of its edges and vertices. The dense subgraphs are identified by a cellular automaton-like algorithm; each subgraph defines a cluster composed of similar inextensible words from different genomes. Almost all clusters are considered as predicted highly conserved elements. The algorithm is applied to the nuclear genomes of the superphylum Alveolata, and the corresponding phylogenetic tree is built and discussed. We proposed an algorithm for the identification of highly conserved elements. The multitude of identified elements was used to infer the phylogeny of Alveolata.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 6%
Unknown 16 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 35%
Lecturer 2 12%
Student > Doctoral Student 2 12%
Researcher 2 12%
Student > Bachelor 1 6%
Other 2 12%
Unknown 2 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 41%
Biochemistry, Genetics and Molecular Biology 5 29%
Environmental Science 2 12%
Medicine and Dentistry 1 6%
Unknown 2 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 March 2021.
All research outputs
#14,272,830
of 22,889,074 outputs
Outputs from BMC Bioinformatics
#4,741
of 7,298 outputs
Outputs of similar age
#182,646
of 320,232 outputs
Outputs of similar age from BMC Bioinformatics
#66
of 123 outputs
Altmetric has tracked 22,889,074 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,298 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 320,232 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 123 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.