Background: False discovery rate (FDR) methods play an important role in analyzing highdimensional data. There are two types of FDR, tail area-based FDR and local FDR, as well as ...
Random sampling is one of the most fundamental data management tools available. However, most current research involving sampling considers the problem of how to use a sample, and...
Mining frequent itemsets from transactional datasets is a well known problem with good algorithmic solutions. In the case of uncertain data, however, several new techniques have be...
Background: Liquid chromatography coupled to mass spectrometry (LC-MS) has become a prominent tool for the analysis of complex proteomics and metabolomics samples. In many applica...
Eva Lange, Ralf Tautenhahn, Steffen Neumann, Cleme...
We have proposed replicator neural networks (RNNs) as an outlier detecting algorithm [15]. Here we compare RNN for outlier detection with three other methods using both publicly a...
Graham J. Williams, Rohan A. Baxter, Hongxing He, ...