We propose a manifold learning approach to fiber tract clustering using a novel similarity measure between fiber tracts constructed from dual-rooted graphs. In particular, to gene...
Andy Tsai, Carl-Fredrik Westin, Alfred O. Hero, Al...
We introduce a model-based analysis technique for extracting and characterizing rhythmic expression pro les from genome-wide DNA microarray hybridization data. These patterns are ...
Christopher James Langmead, Anthony K. Yan, C. Rob...
Background: The definition of a distance measure plays a key role in the evaluation of different clustering solutions of gene expression profiles. In this empirical study we compa...
Discovering mappings between concept hierarchies is widely regarded as one of the hardest and most urgent problems facing the Semantic Web. The problem is even harder in domains w...
Risto Gligorov, Warner ten Kate, Zharko Aleksovski...
— With the invention of high throughput methods, researchers are capable of producing large amounts of biological data. During the analysis of such data, the need for a functiona...