NDLI: Construction of protein dendrograms based on amino acid indices and Discrete Fourier Transform

Content Provider	IEEE Xplore Digital Library
Author	Chrysostomou, C. Seker, H.
Copyright Year	2014
Description	Author affiliation: Dept. of Genetics, Univ. of Leicester, Leicester, UK (Chrysostomou, C.) \|\| Bio-Health Inf. Res. Group, De Montfort Univ., Leicester, UK (Seker, H.)
Abstract	From the literature, existing methods use pairwise percent identity to identify the percentage of similarity between two protein sequences, in order to create a dendrogram. As this is a parametric method of measuring the similarities between proteins, and different parameter may yield different results, this method does not guarantee that the global optimal similarity values will be found. As protein dendrogram construction is used in other areas, such as multiple protein sequence alignments, it is very important that the most related protein sequences to be identified and align first. Furthermore, by using the pairwise percent identity of the protein sequences to construct the dendrograms, the physical characteristics of protein sequences and amino acids are not considered. In this paper, a new method was proposed for constructing protein sequence dendrograms. For this method, Discrete Fourier Transform, was used to construct the distance matrix in combination with the multiple amino acid indices that were used to encode protein sequences into numerical sequences. In order to show the applicability and robustness of the proposed method, a case study was presented by using nine Cluster of Differentiation 4 protein sequences extracted from the UniProt online database.
Sponsorship	IEEE Eng. Med. Biol. Soc.
Starting Page	816
Ending Page	819
File Size	679531
Page Count	4
File Format	PDF
ISBN	9781424479290
ISSN	1557170X
DOI	10.1109/EMBC.2014.6943716
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Amino acids Protein engineering Protein sequence Discrete Fourier transforms Bioinformatics
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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