Greedy Search-Binary PSO Hybrid for Biclustering Gene Expression Data
نویسندگان
چکیده
As a useful data mining technique biclustering identifies local patterns from gene expression data. A bicluster of a gene expression dataset is a subset of genes which exhibit similar expression patterns along a subset of conditions. In this paper a new method is introduced based on greedy search algorithm combined with the evolutionary technique particle swarm optimization for the identification of biclusters. Greedy methods have the possibility of getting trapped in local minima. Metaheuristic methods like particle swarm optimization have features for escaping from local minima and can find global optimal solutions. In this algorithm biclusters are identified in three steps. In the first step small disjoint tightly coregulated submatrices are generated using K-Means clustering algorithm. Then greedy search algorithm is used to enlarge the seeds. Output of greedy search algorithm is used as initial population of binary PSO. The result obtained on Yeast dataset shows that this method can generate high quality biclusters.
منابع مشابه
Comparative Study on Swarm Intelligence Techniques for Biclustering of Microarray Gene Expression Data
Microarray gene expression data play a vital in biological processes, gene regulation and disease mechanism. Biclustering in gene expression data is a subset of the genes indicating consistent patterns under the subset of the conditions. Finding a biclustering is an optimization problem. In recent years, swarm intelligence techniques are popular due to the fact that many real-world problems are...
متن کاملApplication of Cardinality based GRASP to the Biclustering of Gene Expression Data
Biclustering algorithms perform simultaneous row and column clustering of a given data matrix. In gene expression dataset a bicluster is a subset of genes that exhibit similar expression patterns through a subset of conditions. Biclustering is a useful data mining technique for identifying local patterns from gene expression data. In this paper biclusters are identified in two steps. In the fir...
متن کاملApplication of Greedy Randomized Adaptive Search Procedure to the Biclustering of Gene Expression Data
Microarray technology demands the development of data mining algorithms for extracting useful and novel patterns. A bicluster of a gene expression dataset is a local pattern such that the genes in the bicluster exhibit similar expression patterns through a subset of conditions. In this study biclusters are detected in two steps. In the first step high quality bicluster seeds are generated using...
متن کاملGene Expression Biclustering Using Random Walk Strategies
A biclustering algorithm, based on a greedy technique and enriched with a local search strategy to escape poor local minima, is proposed. The algorithm starts with an initial random solution and searches for a locally optimal solution by successive transformations that improve a gain function, combining the mean squared residue, the row variance, and the size of the bicluster. Different strateg...
متن کاملA hybrid metaheuristic using fuzzy greedy search operator for combinatorial optimization with specific reference to the travelling salesman problem
We describe a hybrid meta-heuristic algorithm for combinatorial optimization problems with a specific reference to the travelling salesman problem (TSP). The method is a combination of a genetic algorithm (GA) and greedy randomized adaptive search procedure (GRASP). A new adaptive fuzzy a greedy search operator is developed for this hybrid method. Computational experiments using a wide range of...
متن کامل