Title
Correlation–based scatter search for discovering biclusters from gene expression data
Abstract
Scatter Search is an evolutionary method that combines existing solutions to create new offspring as the well–known genetic algorithms. This paper presents a Scatter Search with the aim of finding biclusters from gene expression data. However, biclusters with certain patterns are more interesting from a biological point of view. Therefore, the proposed Scatter Search uses a measure based on linear correlations among genes to evaluate the quality of biclusters. As it is usual in Scatter Search methodology an improvement method is included which avoids to find biclusters with negatively correlated genes. Experimental results from yeast cell cycle and human B-cell lymphoma datasets are reported showing a remarkable performance of the proposed method and measure.
Year
DOI
Venue
2010
10.1007/978-3-642-12211-8_11
EvoBIO
Keywords
Field
DocType
biclustering,evolutionary computation
Data mining,Computer science,Evolutionary computation,Correlation,Artificial intelligence,Bioinformatics,Biclustering,Machine learning,Genetic algorithm
Conference
Volume
ISSN
ISBN
6023
0302-9743
3-642-12210-8
Citations 
PageRank 
References 
2
0.37
12
Authors
3
Name
Order
Citations
PageRank
Juan A. Nepomuceno1577.10
Alicia Troncoso215320.88
Jesús S. Aguilar–Ruiz371.88