Given its importance, the problem of predicting rare classes in large-scale multi-labeled data sets has attracted great attentions in the literature. However, the rare-class probl...
One of the inherent problems in pattern recognition is the undersampled data problem, also known as the curse of dimensionality reduction. In this paper a new algorithm called pai...
We review some recent progress in improving the speed of electron microscope tomography through highly parallel algorithms implemented on parallel computers, clusters and graphics...
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...
Background: This paper presents a unified framework for finding differentially expressed genes (DEGs) from the microarray data. The proposed framework has three interrelated modul...