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MOTIVATION In recent years, there have been various efforts to overcome the limitations of standard clustering approaches for the analysis of gene expression data by grouping genes and samples simultaneously. The underlying concept, which is often referred to as biclustering, allows to identify sets of genes sharing compatible expression patterns across(More)
SUMMARY Besides classical clustering methods such as hierarchical clustering, in recent years biclustering has become a popular approach to analyze biological data sets, e.g. gene expression data. The Biclustering Analysis Toolbox (BicAT) is a software platform for clustering-based data analysis that integrates various biclustering and clustering techniques(More)
We investigate the protection of migrating agents against the untrusted sites they traverse. The resulting calculus provides a formal framework to reason about protection policies and security protocols over distributed, mobile infrastructures, and aims to stand to ambients as the spi calculus stands to π. We present a type system that separates trusted and(More)
— In recent years, several biclustering methods have been suggested to identify local patterns in gene expression data. Most of these algorithms represent greedy strategies that are heuristic in nature: an approximate solution is found within reasonable time bounds. The quality of a biclustering, though, is often considered more important than the(More)
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