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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 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.


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