Unsupervised identification of patterns in microarray data has been a productive approach to uncovering relationships between genes and the biological process in which they are in...
The advent of affordable, shared-nothing computing systems portends a new class of parallel database management systems (DBMS) for on-line transaction processing (OLTP) applicatio...
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...
Unsupervised sequence learning is important to many applications. A learner is presented with unlabeled sequential data, and must discover sequential patterns that characterize th...
Data sparseness is one of the factors that degrade statistical machine translation (SMT). Existing work has shown that using morphosyntactic information is an effective solution t...