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OJBTM
Online Journal of
Bioinformatics ©
Volume 15 (1): 141-156, 2014
Mining quantitative associations in peptide sequences of mosquito borne
flavivirus
Priyanka Rajput and Dr. Usha Chouhan
Department of Bioinformatics.Manit,Bhopal,India
ABSTRACT
Rajput
P, Chouhan U., Mining quantitative associations in
peptide sequences of mosquito borne flavivirus, Onl J Bioinform., 15
(1): 141-156, 2014. Flavivirus mosquito vector causes Japanese, Murray Valley, St
Louis encephalitis and West Nile and Ilheus virus
disease. Knowledge of the relationships between amino acids and other
parameters in molecular sequences of this virus may assist in control of the
diseases. A model for mining quantitative association patterns in the amino
acid sequence of flavivirus is described. Sequences were
retrieved from NCBI but due to the enormous amount of data a quantitative
approach was used to generate association relationships for 5 sub-families of the
mosquito. The results generated were analyzed for similarities and differences
in association in the amino-acids. Association
rules were generated for redundant and non-redundant protein sequences using
frequent and un-frequent patterns.
Key words:-dataset, item set, Threshold, Support, Confidence, Pattern , quantitative association mining.