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Frank Rügheimer

Researcher at Pasteur Institute

Publications -  13
Citations -  1116

Frank Rügheimer is an academic researcher from Pasteur Institute. The author has contributed to research in topics: Graphical model & Bayesian network. The author has an hindex of 5, co-authored 13 publications receiving 991 citations. Previous affiliations of Frank Rügheimer include Columbia University & Otto-von-Guericke University Magdeburg.

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Journal ArticleDOI

Condition-Dependent Transcriptome Reveals High-Level Regulatory Architecture in Bacillus subtilis

TL;DR: The transcriptomes of Bacillus subtilis exposed to a wide range of environmental and nutritional conditions that the organism might encounter in nature are reported, offering an initial understanding of why certain regulatory strategies may be favored during evolution of dynamic control systems.
Journal ArticleDOI

Global Network Reorganization During Dynamic Adaptations of Bacillus subtilis Metabolism

TL;DR: The responses of a bacterium to changing nutritional conditions are explored and an initial understanding of why certain regulatory strategies may be favored during evolution of dynamic control systems is offered.
Book ChapterDOI

Graphical Models for Industrial Planning on Complex Domains

TL;DR: Probabilistic graphical models, which have successfully been used for handling complex dependency structures and reasoning tasks in the presence of uncertainty, are dealt with.
Journal ArticleDOI

The Cyni framework for network inference in Cytoscape

TL;DR: Cyni, an open-source 'fill-in-the-algorithm' framework that provides common network inference functionality and user interface elements that allows the rapid transformation of Java-based network inference prototypes into apps of the popular open- source Cytoscape network analysis and visualization ecosystem.
Journal ArticleDOI

Fragmentation-free LC-MS can identify hundreds of proteins.

TL;DR: The results suggest that additional developments in retention time prediction, measurement technology, and scoring algorithms may render fragmentation‐free approaches an interesting complement or an alternative to fragmentation‐based approaches.