In the paper we show that diagnostic classes in cancer gene expression data sets, which most often include thousands of features (genes), may be effectively separated with simple ...
Gregor Leban, Minca Mramor, Ivan Bratko, Blaz Zupa...
Background: Hidden Markov Models (HMMs) have been extensively used in computational molecular biology, for modelling protein and nucleic acid sequences. In many applications, such...
Pantelis G. Bagos, Theodore D. Liakopoulos, Stavro...
Rank correlation statistics are useful for determining whether a there is a correspondence between two measurements, particularly when the measures themselves are of less interest...
Background: The combination of genotypic and genome-wide expression data arising from segregating populations offers an unprecedented opportunity to model and dissect complex phen...
Background: The analysis of gene sets has become a popular topic in recent times, with researchers attempting to improve the interpretability and reproducibility of their microarr...