Published May 26, 2022
| Version v1
Publication
A Local Search in Scatter Search for Improving Biclusters
Description
Scatter Search is a population-based metaheuristic
that emphasizes systematic processes against random proce dures. A local search procedure is added to a Scatter Search
for Biclustering in order to improve the quality of biclusters.
This local search constitutes the existing Improvement Method
in most of Scatter Search schemes which intensifies the opti mization process, and, consequently, improves the quality of
biclusters according to a fitness function. The fitness function
is based on linear correlations among genes and, therefore,
biclusters with shifting and scaling patterns are obtained. Thus,
the improvement of a bicluster consists in removing every pair
of genes of such bicluster that has a correlation lower than a
given threshold which is automatically chosen by the algorithm.
Experimental results from a Yeast microarray data set with
different stress conditions have been reported and compared to
another algorithm based on Scatter Search recently published
in the literature. Experiments show a remarkable performance
of the Biclustering algorithm with the proposed local search.
Abstract
Ministerio de Ciencia e Innovación TIN2007-68084-C02Abstract
Ministerio de Ciencia e Innovación PCI2006-A7-0575Abstract
Junta de Andalucía P07-TIC-02611Additional details
Identifiers
- URL
- https://idus.us.es/handle//11441/133674
- URN
- urn:oai:idus.us.es:11441/133674