Mining Fuzzy Amino Acid Associations in Peptide Sequences of Herpes Simplex Virus
Published: 2013
Author(s) Name: Rishu Gupta |
Author(s) Affiliation: M.Tech Scholar, Maulana Azad National Institute of Technology, Bhopal, Madhya Pradesh, India
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Abstract
Herpes is a usually mild recurrent skin condition in which
most infections are unrecognized and undiagnosed.
The mechanism of disease is still not well understood.
The analysis of peptide sequences of herpes can reveal
information which may be useful for understanding
the mechanism of disease. In this paper an attempt
has been made to develop a model for mining fuzzy
amino acid associations in peptide sequences of
herpes virus. The uncertainty arising due to variation in
length of sequences and this is handled by employing
fuzzy sets. Total 9160 sequences were taken from
National Centre for Biotechnology Information. After
that around 4004 non-redundant peptide sequences of
herpes virus filtered to form the dataset. This dataset
is trnasformed to fuzzy transaction dataset and their
fuzzy support and confidence have been computed.
The patterns generated from this model can be useful
in understanding the structure, function and interaction
of the protein in the disease.
Keywords: HSV, ARM, Frequent Pattern, Threshold Abbreviations: ARM-Association Rule Mining, HSVHerpes Simplex Virus
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