—A variety of clustering algorithms have recently been proposed to handle data that is not linearly separable; spectral clustering and kernel k-means are two of the main methods....
Background: Overfitting the data is a salient issue for classifier design in small-sample settings. This is why selecting a classifier from a constrained family of classifiers, on...
Jianping Hua, James Lowey, Zixiang Xiong, Edward R...
Background: Intracellular signal transduction is achieved by networks of proteins and small molecules that transmit information from the cell surface to the nucleus, where they ul...
Martin Steffen, Allegra Petti, John Aach, Patrik D...
Background: The abundant data available for protein interaction networks have not yet been fully understood. New types of analyses are needed to reveal organizational principles o...
Taner Z. Sen, Andrzej Kloczkowski, Robert L. Jerni...
Background: We consider effects of dependence among variables of high-dimensional data in multiple hypothesis testing problems, in particular the False Discovery Rate (FDR) contro...