Abstracts "Mixtures at the Interface" David Scott, Rice University Mixture modeling provides an effective framework for complex, high-dimensional data. The potential of m...
Background: Several problems exist with current methods used to align DNA sequences for comparative sequence analysis. Most dynamic programming algorithms assume that conserved se...
We propose an unconventional but highly effective approach
to robust fitting of multiple structures by using statistical
learning concepts. We design a novel Mercer kernel
for t...
Background: Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks ...
Joshua J. Forman, Paul A. Clemons, Stuart L. Schre...
Background: Recently several statistical methods have been proposed to identify genes with differential expression between two conditions. However, very few studies consider the p...