The analysis of microarray data is essential for large amounts of gene expression data. In
this review we focus on clustering techniques. The biological rationale for this approach is …

Variable neighbourhood search (VNS) is a metaheuristic, or a framework for building
heuristics, based upon systematic changes of neighbourhoods both in descent phase, to …

Background Data clustering analysis has been extensively applied to extract information
from gene expression profiles obtained with DNA microarrays. To this aim, existing …

Clustering is ubiquitously applied in bioinformatics with hierarchical clustering and k-means
partitioning being the most popular methods. Numerous improvements of these two …

Variable neighbourhood search (VNS) is a metaheuristic, or a framework for building
heuristics, based upon systematic changes of neighbourhoods both in descent phase, to …

The purpose of this paper is to present a general view of the current applications of fuzzy
logic in medicine and bioinformatics. We particularly review the medical literature using …

Within the field of genomics, microarray technologies have become a powerful technique for
simultaneously monitoring the expression patterns of thousands of genes under different …

Lingras et al. proposed a rough cluster algorithm and successfully applied it to web mining.
In this paper we analyze their algorithm with respect to its objective function, numerical …

Traditional and fuzzy cluster analyses are applicable to variables whose values are
uncorrelated. Hence, in order to cluster time series data which are usually serially …

We propose a novel semi-supervised clustering method called GO Fuzzy c-means, which
enables the simultaneous use of biological knowledge and gene expression data in a …