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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

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

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

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 22%
Professor 1 11%
Student > Doctoral Student 1 11%
Student > Ph. D. Student 1 11%
Student > Master 1 11%
Other 1 11%
Unknown 2 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 22%
Computer Science 1 11%
Biochemistry, Genetics and Molecular Biology 1 11%
Physics and Astronomy 1 11%
Medicine and Dentistry 1 11%
Other 0 0%
Unknown 3 33%