Unsupervised sequence learning is important to many applications. A learner is presented with unlabeled sequential data, and must discover sequential patterns that characterize th...
Background: High-throughput technologies like functional screens and gene expression analysis produce extended lists of candidate genes. Gene-Set Enrichment Analysis is a commonly...
Florian Hahne, Alexander Mehrle, Dorit Arlt, Annem...
Determination of the functions of all expressed proteins represents one of the major upcoming challenges in computational molecular biology. Since subcellular location plays a cru...
Robert F. Murphy, Michael V. Boland, Meel Velliste
The induction of knowledge from a data set relies in the execution of multiple data mining actions: to apply filters to clean and select the data, to train different algorithms (...
Background: Analysis of sequence composition is a routine task in genome research. Organisms are characterized by their base composition, dinucleotide relative abundance, codon us...