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Bastian Robert Angermann

dblp:97/11171 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › systems biology
biochemical modeling
0.212013
The Simmune Modeler visual interface for creating signaling networks based on bi-molecular interactions · Bioinform. 2013
Bioinformatics and computational biology › biological network › network biology
signaling network modeling
0.212013
The Simmune Modeler visual interface for creating signaling networks based on bi-molecular interactions · Bioinform. 2013

Methods — techniques the papers use, named apart from their topics

bi-molecular interaction rules · 0.2ODE export · 0.2
YearPublicationVenuePosition
2013 The Simmune Modeler visual interface for creating signaling networks based on bi-molecular interactions
abstract
MOTIVATION: Biochemical modeling efforts now frequently take advantage of the possibility to automatically create reaction networks based on the specification of pairwise molecular interactions. Even though a variety of tools exist to visualize the resulting networks, defining the rules for the molecular interactions typically requires writing scripts, which impacts the non-specialist accessibility of those approaches. We introduce the Simmune Modeler that allows users to specify molecular complexes and their interactions as well as the reaction-induced modifications of the molecules through a flexible visual interface. It can take into account the positions of the components of trans-membrane complexes relative to the embedding membranes as well as symmetry aspects affecting the reactions of multimeric molecular structures. Models created with this tool can be simulated using the Simmune Simulator or be exported as SBML code or as files describing the reaction networks as systems of ODEs for import into Matlab. AVAILABILITY: The Simmune Modeler and the associated simulators as well as extensive additional documentation and tutorials are freely available for Linux, Mac and Windows: http://go.usa.gov/QeH (Note shortened case-sensitive URL!).
Fengkai Zhang, Bastian Robert Angermann, Martin Meier-Schellersheim
Bioinform.2
2007 Key Role of Local Regulation in Chemosensing Revealed by a New Molecular Interaction-Based Modeling Method
abstract
The signaling network underlying eukaryotic chemosensing is a complex combination of receptor-mediated transmembrane signals, lipid modifications, protein translocations, and differential activation/deactivation of membrane-bound and cytosolic components. As such, it provides particularly interesting challenges for a combined computational and experimental analysis. We developed a novel detailed molecular signaling model that, when used to simulate the response to the attractant cyclic adenosine monophosphate (cAMP), made nontrivial predictions about Dictyostelium chemosensing. These predictions, including the unexpected existence of spatially asymmetrical, multiphasic, cyclic adenosine monophosphate-induced PTEN translocation and phosphatidylinositol-(3,4,5)P3 generation, were experimentally verified by quantitative single-cell microscopy leading us to propose significant modifications to the current standard model for chemoattractant-induced biochemical polarization in this organism. Key to this successful modeling effort was the use of "Simmune," a new software package that supports the facile development and testing of detailed computational representations of cellular behavior. An intuitive interface allows user definition of complex signaling networks based on the definition of specific molecular binding site interactions and the subcellular localization of molecules. It automatically translates such inputs into spatially resolved simulations and dynamic graphical representations of the resulting signaling network that can be explored in a manner that closely parallels wet lab experimental procedures. These features of Simmune were critical to the model development and analysis presented here and are likely to be useful in the computational investigation of many aspects of cell biology.
Martin Meier-Schellersheim, Xuehua Xu, Bastian Robert Angermann, Eric J. Kunkel, Ronald N. Germain
PLoS Comput. Biol.3