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Composition-based features

SG Sudheer Gupta
MM Midhun K. Madhu
AS Ashok K. Sharma
VS Vineet K. Sharma
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Amino acid composition (AAC) is the percentages of each amino acid in the given length of amino acid sequence. AAC has widely been applied in different peptide and protein composition based classification method [28, 29]. Since there are 20 amino acids, each peptide/protein is represented by 20 types of compositions or a vector size of 20.

where, AAC(i) is the amino acid composition of the amino acid (i) and amino acid (i) is one of the 20 amino acids.

Similar to the AAC, dipeptide composition (DPC) has also been extensively applied in sequence-based classifications, particularly in the immune epitope prediction algorithms [30, 31]. DPC differs from AAC in having pair of amino acids and thus also provides information on local arrangement. The percentage of every possible pair (dipeptide) of amino acids was calculated. The following equation has been used for this calculation:

where, DPC(i) is the dipeptide frequency of dipeptide (i) and the dipeptide (i) is one out of 400 dipeptides.

Copyright and License information: The Author(s) ©2016
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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