Pattern clustering with statistical methods using a DNA-based algorithm

Ikno Kim, Junzo Watada, Witold Pedrycz, Jui Yu Wu

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Clustering is commonly exploited in engineering, management, and science fields with the objective of revealing structure in pattern data sets. In this article, through clustering we construct meaningful collections of information granules (clusters). Although the underlying goal is obvious, its realization is fully challenging. Given their nature, clustering is a well-known NP-complete problem. The existing algorithms commonly produce some suboptimal solutions. As a vehicle of pattern clustering, we discuss in this article how to use a DNA-based algorithm. We also discuss the details of encoding being used here with statistical methods combined with the DNA-based algorithm for pattern clustering.

Original languageEnglish
Article number6208882
Pages (from-to)100-110
Number of pages11
JournalIEEE Transactions on Nanobioscience
Volume11
Issue number2
DOIs
Publication statusPublished - 2012

Keywords

  • DNA-based algorithm
  • ordering method
  • pattern clustering
  • splicing operation
  • statistical method

ASJC Scopus subject areas

  • Bioengineering
  • Electrical and Electronic Engineering
  • Biotechnology
  • Biomedical Engineering
  • Medicine (miscellaneous)
  • Computer Science Applications
  • Pharmaceutical Science

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