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Johannes Geiselmann

Researcher at University of Grenoble

Publications -  64
Citations -  3924

Johannes Geiselmann is an academic researcher from University of Grenoble. The author has contributed to research in topics: Gene & Transcription (biology). The author has an hindex of 34, co-authored 63 publications receiving 3663 citations. Previous affiliations of Johannes Geiselmann include French Institute for Research in Computer Science and Automation & Joseph Fourier University.

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Qualitative Simulation of Genetic Regulatory Networks Using Piecewise-Linear Models

TL;DR: Given a qualitative model of a genetic regulatory network, consisting of a system of PL differential equations and inequality constraints on the parameter values, the method produces a graph of qualitative states and transitions between qualitative states, summarizing the qualitative dynamics of the system.
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Improvement of pCVD442, a suicide plasmid for gene allele exchange in bacteria.

TL;DR: It is demonstrated that this new vector can be easily used to introduce various types of mutations into different genetics backgrounds: removal of IS elements, introduction of point mutations or deletions, and can be introduced into bacterial strains by either transformation or conjugation.
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Genetic Network Analyzer: qualitative simulation of genetic regulatory networks.

TL;DR: The tool is based on a qualitative simulation method that employs coarse-grained models of regulatory networks and illustrated by a case study of the network of genes and interactions regulating the initiation of sporulation in Bacillus subtilis.
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Validation of qualitative models of genetic regulatory networks by model checking: analysis of the nutritional stress response in Escherichia coli

TL;DR: The model-validation approach has been applied to the analysis of the network controlling the nutritional stress response in Escherichia coli and is supported by a new version of the computer tool Genetic Network Analyzer (GNA).
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Shared control of gene expression in bacteria by transcription factors and global physiology of the cell.

TL;DR: The results show that the transcriptional response of the network is controlled by the physiological state of the cell and the signaling metabolite cyclic AMP (cAMP), suggesting that they are not the main coordinators of gene expression changes during growth transitions, but rather that they complement the effect of global physiological control mechanisms.