Abstract
Clustering is regarded as a consortium of concepts and algorithms that are aimed at revealing a structure in highly dimensional data and arriving at a collection of meaningful relationships in data and information granules. The objective of this paper is to propose a DNA computing to support the development of clustering techniques. This approach is of particular interest when dealing with huge data sets, unknown number of clusters and encountering a heterogeneous character of available data. We present a detailed algorithm and show how the essential components of the clustering technique are realized through the corresponding mechanisms of DNA computing. Numerical examples offer a detailed insight into the performance of the DNA-based clustering.
Original language | English |
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Pages (from-to) | 1-12 |
Number of pages | 12 |
Journal | BioSystems |
Volume | 91 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2008 Jan |
Keywords
- Cluster validity
- Clustering
- DNA computing and optimization
ASJC Scopus subject areas
- Ecology, Evolution, Behavior and Systematics
- Biotechnology
- Drug Discovery