The ability to control gene expression during development in plants could be used for improving crop yields, resistance to disease, and environmental adaptability. It has been sug...
Christopher Maher, Marja Timmermans, Lincoln Stein...
With the recent explosion of interest in microarray technology, massive amounts of microarray images are currently being produced. The storage and the transmission of this type of...
A novel and rigorous Multi-perturbation Shapley Value Analysis (MSA) method has been recently presented [12]. The method addresses the challenge of defining and calculating the fu...
The advent of DNA microarray technologies has revolutionized the experimental study of gene expression. Clustering is the most popular approach of analyzing gene expression data a...
The soundness of clustering in the analysis of gene expression profiles and gene function prediction is based on the hypothesis that genes with similar expression profiles may imp...
Gene expression profiles with clinical outcome data enable monitoring of disease progression and prediction of patient survival at the molecular level. We present a new computatio...
Clustering is a common methodology for analyzing the gene expression data. In this paper, we present a new clustering algorithm from an information-theoretic point of view. First,...
One goal of the structural genomics initiative is the identification of new protein folds. Sequence-based structural homology prediction methods are an important means for priorit...