An effective non-parametric method for globally clustering genes from expression profiles

作者：Hou Jingyu^*; Shi Wei; Li Gang; Zhou Wanlei

来源：MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, 2007, 45(12): 1175-1185.

DOI：10.1007/s11517-007-0271-1

• bioinformatics
• microarray
• gene expression
• clustering
• data mining

Clustering is widely used in bioinformatics to find gene correlation patterns. Although many algorithms have been proposed, these are usually confronted with difficulties in meeting the requirements of both automation and high quality. In this paper, we propose a novel algorithm for clustering genes from their expression profiles. The unique features of the proposed algorithm are twofold: it takes into consideration global, rather than local, gene correlation information in clustering processes; and it incorporates clustering quality measurement into the clustering processes to implement non-parametric, automatic and global optimal gene clustering. The evaluation on simulated and real gene data sets demonstrates the effectiveness of the algorithm.

• 出版日期2007-12
• 单位河北医科大学; 迪肯大学