Background: Data clustering analysis has been extensively applied to extract information from gene expression profiles obtained with DNA microarrays. To this aim, existing cluster...
distributed shared-memory (SDSM) provides the abstraction necessary to run shared-memory applications on cost-effective parallel platforms such as clusters of workstations. Howeve...
Clustering is to identify densely populated subgroups in data, while correlation analysis is to find the dependency between the attributes of the data set. In this paper, we combin...
Although very widely used in unsupervised data mining, most clustering methods are affected by the instability of the resulting clusters w.r.t. the initialization of the algorithm ...
The spatial clustering of genes across different genomes has been used to study important problems in comparative genomics, from identification of operons to detection of homologo...