Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
In this research we introduce the problem of the binary matrix partitioning in a biological context. Our idea is to use SNP matrix to construct a set of phylogenetic networks to r...
In systems consisting of multiple clusters of processors which are interconnected by relatively slow communication links and which employ space sharing for scheduling jobs, such a...
Terms used in search queries often have multiple meanings. Consequently, search results corresponding to different meanings may be retrieved, making identifying relevant results in...
Nearest neighborhood consistency is an important concept in statistical pattern recognition, which underlies the well-known k-nearest neighbor method. In this paper, we combine th...