Abstract. Clustering still represents the most commonly used technique to analyze gene expression data—be it classical clustering approaches that aim at finding biologically rel...
Clustering problems often involve datasets where only a part of the data is relevant to the problem, e.g., in microarray data analysis only a subset of the genes show cohesive exp...
With the maturity of GPS, wireless, and Web technologies, increasing amounts of movement data collected from various moving objects, such as animals, vehicles, mobile devices, and...
Zhenhui Li, Ming Ji, Jae-Gil Lee, Lu An Tang, Yint...
The effective reverse engineering of biochemical networks is one of the great challenges of systems biology. The contribution of this paper is two-fold: 1) We introduce a new meth...
Linear Discriminant Analysis (LDA) is one of the wellknown methods for supervised dimensionality reduction. Over the years, many LDA-based algorithms have been developed to cope w...