Name
Abstract | ||
|---|---|---|
In recent years, the interest in extracting useful knowledge from gene expression data has experimented an enormous increase with the development of microarray technique. Biclustering is a recent technique that aims at extracting a subset of genes that show a similar behaviour for a subset conditions. It is important, therefore, to measure the quality of a bicluster, and a way to do that would be checking if each data submatrix follows a specific trend, represented by a pattern. In this work, we present an evolutionary algorithm for finding significant shifting patterns which depict the general behaviour within each bicluster. The empirical results we have obtained confirm the quality of our proposal, obtaining very accurate solutions for the biclusters used. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11893004_160 | KES (2) |
Keywords | Field | DocType |
empirical result,data submatrix,microarray technique,gene expression data,patterns discovery,accurate solution,similar behaviour,general behaviour,recent technique,evolutionary algorithm,subset condition,recent year | Microarray,Evolutionary algorithm,Computer science,Knowledge engineering,Artificial intelligence,Knowledge extraction,Biclustering,Genetic algorithm,Machine learning,DNA microarray | Conference |
Volume | ISSN | ISBN |
4252 | 0302-9743 | 3-540-46537-5 |
Citations | PageRank | References |
1 | 0.35 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Beatriz Pontes | 1 | 67 | 5.36 |
| Raúl Giráldez | 2 | 105 | 10.26 |
| Jesús S. Aguilar–Ruiz | 3 | 7 | 1.88 |