Frank Rügheimer

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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 inhomogeneous data.(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)
Knowledge discovery and information mining have long been recognized as important tools for prediction and decision making. But the process – from data preparation and selection of appropriate methods to a properly configured, well-tested analysis setup – can be time-consuming. In recent years easy to use software that supports experts in model construction(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 probabilistic graphical models, which have(More)
A significant number of scientific and economic problems is characterised by a large number of interrelated variables. But with larger variable number, the domain under consideration may grow fast, so that analyses and reasoning become increasingly difficult. Graphical models allow to represent the combined distributions compactly and are suitable for(More)