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Evolutionary analysis of apolipoprotein E by Maximum Likelihood and complex network methods

Overview of attention for article published in Genetics and Molecular Biology, July 2016
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Title
Evolutionary analysis of apolipoprotein E by Maximum Likelihood and complex network methods
Published in
Genetics and Molecular Biology, July 2016
DOI 10.1590/1678-4685-gmb-2015-0164
Pubmed ID
Authors

Leandro de Jesus Benevides, Daniel Santana de Carvalho, Roberto Fernandes Silva Andrade, Gilberto Cafezeiro Bomfim, Flora Maria de Campos Fernandes

Abstract

Apolipoprotein E (apo E) is a human glycoprotein with 299 amino acids, and it is a major component of very low density lipoproteins (VLDL) and a group of high-density lipoproteins (HDL). Phylogenetic studies are important to clarify how various apo E proteins are related in groups of organisms and whether they evolved from a common ancestor. Here, we aimed at performing a phylogenetic study on apo E carrying organisms. We employed a classical and robust method, such as Maximum Likelihood (ML), and compared the results using a more recent approach based on complex networks. Thirty-two apo E amino acid sequences were downloaded from NCBI. A clear separation could be observed among three major groups: mammals, fish and amphibians. The results obtained from ML method, as well as from the constructed networks showed two different groups: one with mammals only (C1) and another with fish (C2), and a single node with the single sequence available for an amphibian. The accordance in results from the different methods shows that the complex networks approach is effective in phylogenetic studies. Furthermore, our results revealed the conservation of apo E among animal groups.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 20%
Student > Doctoral Student 1 10%
Professor 1 10%
Student > Ph. D. Student 1 10%
Student > Master 1 10%
Other 1 10%
Unknown 3 30%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 20%
Biochemistry, Genetics and Molecular Biology 1 10%
Computer Science 1 10%
Physics and Astronomy 1 10%
Medicine and Dentistry 1 10%
Other 0 0%
Unknown 4 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 26 August 2016.
All research outputs
#20,335,770
of 22,880,691 outputs
Outputs from Genetics and Molecular Biology
#589
of 712 outputs
Outputs of similar age
#309,117
of 355,133 outputs
Outputs of similar age from Genetics and Molecular Biology
#15
of 22 outputs
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