Name
Abstract | ||
|---|---|---|
This work deals with the application of Memetic Algorithms to the Microarray Gene Ordering problem, a NP-hard problem with strong implications in Medicine and Biology. It consists in ordering a set of genes, grouping together the ones with similar behavior. We propose a MA, and evaluate the influence of several features, such as the intensity of local searches and the utilization of multiple populations, in the performance of the MA. We also analyze the impact of different objective functions on the general aspect of the solutions. The instances used for experimentation are extracted from the literature and represent real biological systems. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/3-540-36605-9_3 | EvoWorkshops |
Keywords | Field | DocType |
memetic algorithms,memetic algorithm,similar behavior,multiple population,strong implication,general aspect,real biological system,np-hard problem,microarray gene ordering problem,microarray data,different objective function,local search,np hard problem,biological systems,objective function | Memetic algorithm,Data mining,Evolutionary algorithm,Computer science,Island model,Microarray analysis techniques,Artificial intelligence,Local search (optimization),DNA microarray,Distributed computing | Conference |
Volume | ISSN | ISBN |
2611 | 0302-9743 | 3-540-00976-0 |
Citations | PageRank | References |
10 | 0.76 | 7 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Carlos Cotta | 1 | 441 | 36.10 |
| Alexandre Mendes | 2 | 163 | 18.23 |
| Vinícius Garcia | 3 | 15 | 2.23 |
| Paulo França | 4 | 11 | 1.45 |
| Pablo Moscato | 5 | 334 | 37.27 |