Background: One of the goals of global metabolomic analysis is to identify metabolic markers that are hidden within a large background of data originating from high-throughput ana...
Peter Meinicke, Thomas Lingner, Alexander Kaever, ...
Background: Biological information is commonly used to cluster or classify entities of interest such as genes, conditions, species or samples. However, different sources of data c...
Background: Several supervised and unsupervised learning tools are available to classify functional genomics data. However, relatively less attention has been given to exploratory...
In this paper, we explore modeling overlapping biological processes. We discuss a probabilistic model of overlapping biological processes, gene membership in those processes, and ...
Background: The most common method of identifying groups of functionally related genes in microarray data is to apply a clustering algorithm. However, it is impossible to determin...
Matthew A. Hibbs, Nathaniel C. Dirksen, Kai Li, Ol...