Title
Multi-Scale Clustering for Gene Expression Profiling Data
Abstract
In cluster analyses, setting the scale parameter which is implicitly related to the complexity of the data distribution is an important issue; different scale values lead to different results and hence cause different interpretation. In this study, we discuss a framework of multi-scale clustering, where clustering is done with multiple scale values and then the obtained results are compiled into a visually appropriate form to observe overall structures of the clusters. For such purpose, a brick view method is proposed in this study. The construction of a brick view diagram consists of a re-indexing procedure of clusters obtained with various scale values and a sorting procedure of samples so as to minimize the distortion defined based on the multiple clustering results. Although some popular clustering methods, such as K-means, spherical K-means, and hierarchical clustering, have been used within the multi-scale framework, we introduce mean-shift clustering based on the kernel density estimation for directional data. We evaluate our approach and existing hierarchical clustering by using an artificial data set and a real data set of gene expression profiles. The results show global structures of distributions can be observed well and in a stable manner, in the brick view diagram.
Year
DOI
Venue
2005
10.1109/BIBE.2005.41
BIBE
Keywords
Field
DocType
popular clustering method,different scale value,gene expression profiling data,multi-scale clustering,artificial data,multiple clustering result,multiple scale value,hierarchical clustering,data distribution,brick view diagram,directional data,k means,mean shift,kernel density estimate,sorting,genetics,molecular biophysics,statistical analysis
Hierarchical clustering,Data mining,Fuzzy clustering,CURE data clustering algorithm,Correlation clustering,Computer science,Determining the number of clusters in a data set,Constrained clustering,Bioinformatics,Cluster analysis,Single-linkage clustering
Conference
ISBN
Citations 
PageRank 
0-7695-2476-1
2
0.40
References 
Authors
6
3
Name
Order
Citations
PageRank
Shigeyuki Oba129027.68
Kikuya Kato2403.49
Shin Ishii321224.55