Iterated local search for biclustering of microarray data

Authors:
Wassim Ayadi;Mourad Elloumi;Jin-Kao Hao
Affiliations:
LERIA, University of Angers, Angers, France and UTIC, Higher School of Sciences and Technologies of Tunis, Tunis, Tunisia;UTIC, Higher School of Sciences and Technologies of Tunis, Tunis, Tunisia;LERIA, University of Angers, Angers, France
Venue:
PRIB'10 Proceedings of the 5th IAPR international conference on Pattern recognition in bioinformatics
Year:
2010

Citing 17
Cited 3

Discovering local structure in gene expression data: the order-preserving submatrix problem

Proceedings of the sixth annual international conference on Computational biology
Biclustering of Expression Data

Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
OP-Cluster: Clustering by Tendency in High Dimensional Space

ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Stochastic Local Search: Foundations & Applications

Stochastic Local Search: Foundations & Applications
Biclustering Algorithms for Biological Data Analysis: A Survey

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Biclustering of Expression Data with Evolutionary Computation

IEEE Transactions on Knowledge and Data Engineering
Shifting and scaling patterns from gene expression data

Bioinformatics
BicAT: a biclustering analysis toolbox

Bioinformatics
A systematic comparison and evaluation of biclustering methods for gene expression data

Bioinformatics
Multi-objective evolutionary biclustering of gene expression data

Pattern Recognition
A multi-objective approach to discover biclusters in microarray data

Proceedings of the 9th annual conference on Genetic and evolutionary computation
Discovering Biclusters by Iteratively Sorting with Weighted Correlation Coefficient in Gene Expression Data

Journal of Signal Processing Systems
Microarray Biclustering: A Novel Memetic Approach Based on the PISA Platform

EvoBIO '09 Proceedings of the 7th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Next generation software for functional trend analysis

Bioinformatics
Application of reactive GRASP to the biclustering of gene expression data

ISB '10 Proceedings of the International Symposium on Biocomputing
Virtual error: a new measure for evolutionary biclustering

EvoBIO'07 Proceedings of the 5th European conference on Evolutionary computation, machine learning and data mining in bioinformatics
Application of Simulated Annealing to the Biclustering of Gene Expression Data

IEEE Transactions on Information Technology in Biomedicine

An effective measure for assessing the quality of biclusters

Computers in Biology and Medicine
BiMine+: An efficient algorithm for discovering relevant biclusters of DNA microarray data

Knowledge-Based Systems
A new measure for gene expression biclustering based on non-parametric correlation

Computer Methods and Programs in Biomedicine

Quantified Score

Hi-index	0.00

Visualization

Abstract

In the context of microarray data analysis, biclustering aims to identify simultaneously a group of genes that are highly correlated across a group of experimental conditions. This paper presents a Biclustering Iterative Local Search (BILS) algorithm to the problem of biclustering of microarray data. The proposed algorithm is highlighted by the use of some original features including a new evaluation function, a dedicated neighborhood relation and a tailored perturbation strategy. The BILS algorithm is assessed on the well-known yeast cell-cycle dataset and compared with two most popular algorithms.