摘要
针对传统的基于距离/相关系数的相似性度量方法无法有效度量基因间的时延表达特性,为了更加准确地刻画基因间的共调控关系,提出一种基于动态时间弯曲距离(DTW)的相似性度量方法,并结合可指定类数的仿射传播聚类算法进行聚类.将该算法用于人工合成数据和真实的酵母基因数据集,实验结果表明,相对于其它经典聚类算法,本文所提算法能得到更好的聚类结果.
Cluster methods plays an important role in the gene expression data analysis,but the static similarity measure which is based on the distance or the correlation coefficient is not effective to measure the time-lagged relationship between genes.In order to mine the time-lagged gene,this paper proposes a new similarity measure which is based on the DTW algorithm.The new similarity measure is statistically analyzed by integrating it with given number of clusters by affinity propagation clustering.Additionally,experiments on synthetic dataset and real gene expression dataset show that the proposed algorithm has better clustering effect.
出处
《福州大学学报（自然科学版）》
CAS
CSCD
北大核心
2013年第2期158-163,共6页
Journal of Fuzhou University(Natural Science Edition)
基金
福建省自然科学基金资助项目(2009J01283)
