Usually time series prediction is done with regularly sampled data. In practice, however, the data available may be irregularly sampled. In this case the conventional prediction me...
Abstract—In the analysis of spatially-referenced timedependent
data, gaining an understanding of the spatiotemporal
distributions and relationships among the attributes
in the...
Background: High throughput gene expression experiments yield large amounts of data that can augment our understanding of disease processes, in addition to classifying samples. He...
Several microarray technologies that monitor the level of expression of a large number of genes have recently emerged. Given DNA-microarray data for a set of cells characterized b...
This research explores the feasibility of semantic similarity approaches to supporting predictive tasks in functional genomics. It aims to establish potential relationships betwee...