Name
Abstract | ||
|---|---|---|
As DNA chips are becoming increasingly popular as a convenient way to perform vast amounts of experiments related to genes on a single chip, the importance of analyzing the data that is provided by such DNA chips is becoming significant. A very important analysis on DNA chip data would be clustering genes to identify gene groups which have similar properties. Clustering data for DNA chips usually deal with a large search space and has a very fuzzy characteristic. This task can be achieved by applying a clustering technique that mimics the biological world. One such algorithm is the Particle Swarm Optimization algorithm which was recently proposed as a very good candidate to solve such problems. In this paper, we propose a clustering mechanism that is based on the Particle Swarm Optimization algorithm. Our experiments show that the PSO-based clustering algorithm developed can efficiently cluster DNA chip data, and thus be used to extract valuable information from DNA chip data in an accurate yet timely manner. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1145/1516241.1516358 | ICUIMC |
Keywords | Field | DocType |
particle swarm optimization,dna chip data,dna chip data analysis,dna chip,clustering data,particle swarm optimization algorithm,single chip,clustering technique,clustering gene,pso-based clustering algorithm,cluster dna chip data,clustering mechanism,clustering,search space,data analysis,chip | Particle swarm optimization,Data mining,Correlation clustering,Computer science,Fuzzy logic,Multi-swarm optimization,Chip,Real-time computing,Artificial intelligence,Cluster analysis,Machine learning,DNA microarray | Conference |
Citations | PageRank | References |
3 | 0.46 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Minsoo Lee | 1 | 315 | 31.33 |
| Yoonkyoung Lee | 2 | 3 | 0.46 |
| Boyeon Meang | 3 | 3 | 0.46 |
| Okju Choi | 4 | 3 | 0.46 |