An efficient approach for generating frequent patterns without candidate generation

  • Authors:
  • G. LakshmiPriya;Shanmugasundaram Hariharan

  • Affiliations:
  • Oxford Engineering College Tiruchirappalli, Tamil Nadu, India;TRP Engineering college (SRM Group) Tiruchirappalli, Tamil Nadu, India

  • Venue:
  • Proceedings of the International Conference on Advances in Computing, Communications and Informatics
  • Year:
  • 2012

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Abstract

Research on biological science is an emerging and critical task to solve crucial problems, especially in prediction of diseases, drug discovery, etc. Our approach aims at extracting the hidden and the most dominating amino acids among the infected protein sequence which causes some infections in human. We handle this problem by predicting patterns without using candidate generation and apply strong association rules over the predicted patterns. The dominating amino acids have been identified using support and confidence measure threshold. We found that association rules can reveal biologically relevant associations between different gene and gene expressions, protein and protein sequences. We have applied this technique over the chromaffin tumor found in the adrenal glands of a human kidney and found the results to be positive.