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Bacteria adapt to environmental stimuli by adjusting their transcriptomes in a complex manner, the full potential of which has yet to be established for any individual bacterial species. Here, we report the transcriptomes of Bacillus subtilis exposed to a wide range of environmental and nutritional conditions that the organism might encounter in nature. We(More)
Adaptation of cells to environmental changes requires dynamic interactions between metabolic and regulatory networks, but studies typically address only one or a few layers of regulation. For nutritional shifts between two preferred carbon sources of Bacillus subtilis, we combined statistical and model-based data analyses of dynamic transcript, protein, and(More)
MOTIVATION Research on methods for the inference of networks from biological data is making significant advances, but the adoption of network inference in biomedical research practice is lagging behind. Here, we present Cyni, an open-source 'fill-in-the-algorithm' framework that provides common network inference functionality and user interface elements.(More)
In collected data information about a single property may be presented with variable resolution and focus. The present paper describes how hierarchically structured attribute domains support the transfer of knowledge between alternative frames of discernment allowing to flexibly serve information needs and facilitate the processing of in-homogeneous data.(More)
In real world applications planners are frequently faced with complex variable dependencies in high dimensional domains. In addition to that, they typically have to start from a very incomplete picture that is expanded only gradually as new information becomes available. In this contribution we deal with proba-bilistic graphical models, which have(More)
Graphical models provide a compact approach to analysing and modeling the interaction between attributes. By exploiting marginal and conditional independence relations, high-dimensional distributions are factorized into a set of distributions over lower dimensional subdomains, allowing for a compact representation and efficient reasoning. In this paper, we(More)
One of the most common approaches for large-scale protein identification is LC, followed by MS. If more than a few proteins are to be identified, the additional fragmentation of individual peptides has so far been considered as indispensable, and thus, the associated costs, in terms of instrument time and infrastructure, as unavoidable. Here, we present(More)
With the widespread use of annotations in biological databases efficient models for statistical properties of set-valued attributes become increasingly relevant. In this work we introduce condensed random sets (CRS) as compact representations of distributions over annotation sets. The approach is discussed for both unorganized term vocabularies and term(More)