Title :
Quality of Gene Order Calculated by Ant Colony Algorithm is Sensitive to Distance Formula
Author :
Pang, Chao-Yang ; Jiang, Gang ; Hu, Ben-Qiong
Author_Institution :
Coll. of Math. & Software Sci., Sichuan Normal Univ., Chengdu, China
Abstract :
A group of expression levels of gene generated by gene chips is represented by a vector. The smaller the distance of two vectors is, the more similar the two associated genes are. Gene order is the permutation of genes in which similar genes cluster together, which is useful for biologist. And the optimal gene order is equivalent to the shortest route of traveling salesman problem (TSP), in which the associated vectors are used as virtual cities. Ant colony optimization (ACO) is a popular method to solve TSP. In this paper, ACO is applied to calculate gene order. The experiment of this paper shows that the quality of gene order calculated by ACO is sensitive to distance formula of vectors. The contrary fact is shown by this paper that squared Euclidean distance formula generates better quality of gene order than Pearson distance formula, which is used commonly to calculated gene order.
Keywords :
biology computing; optimisation; pattern clustering; travelling salesman problems; virtual reality; ant colony optimization; gene chips; gene clustering; gene expression levels; gene order quality; squared Euclidean distance formula; traveling salesman problem; virtual city; Ant colony optimization; Cities and towns; Clustering algorithms; DNA; Educational institutions; Genetic algorithms; Mathematics; Pharmaceutical technology; Probes; Traveling salesman problems; Ant colony optimization (ACO); Distance Formula; Gene Order; TSP;
Conference_Titel :
Genetic and Evolutionary Computing, 2009. WGEC '09. 3rd International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-0-7695-3899-0
DOI :
10.1109/WGEC.2009.63