BowTieBuilder: modeling signal transduction pathways (2009)
Supper, Jochen, Spangenberg, Lucía, Planatscher, Hannes, Dräger, Andreas, Schröder, Adrian, Zell, Andreas
Abstract Background Sensory proteins react to changing environmental conditions by transducing signals into the cell. These signals are integrated into core proteins that activate downstream target...
Dräger, Andreas, Kronfeld, Marcel, Ziller, Michael J, Supper, Jochen, Planatscher, Hannes, Magnus, Jørgen B, ...
Abstract Background To understand the dynamic behavior of cellular systems, mathematical modeling is often necessary and comprises three steps: (1) experimental measurement of participating...
INFERRING GENE REGULATORY NETWORKS BY MACHINE LEARNING METHODS (2008)
Jochen Supper, Holger Fröhlich, Christian Spieth, Andreas Dräger, Andreas Zell
The ability to measure the transcriptional response after a stimulus has drawn much attention to the underlying gene regulatory networks. Several machine learning related methods, such as Bayesian...
GENE REGULATORY NETWORK INFERENCE VIA REGRESSION BASED TOPOLOGICAL REFINEMENT (2008)
Jochen Supper, Holger Fröhlich, Andreas Zell
Inferring the structure of gene regulatory networks from gene expression data has attracted a growing interest during the last years. Several machine learning related methods, such as Bayesian...
Dräger, Andreas, Hassis, Nadine, Supper, Jochen, Schröder, Adrian, Zell, Andreas
Abstract Background The development of complex biochemical models has been facilitated through the standardization of machine-readable representations like SBML (Systems Biology Markup Language)....
GENE REGULATORY NETWORK INFERENCE VIA REGRESSION BASED TOPOLOGICAL REFINEMENT (2008)
Jochen Supper, Holger Fröhlich, Andreas Zell
Inferring the structure of gene regulatory networks from gene expression data has attracted a growing interest during the last years. Several machine learning related methods, such as Bayesian...
INFERRING GENE REGULATORY NETWORKS BY MACHINE LEARNING METHODS (2008)
Jochen Supper, Holger Fröhlich, Christian Spieth, Andreas Dräger, Andreas Zell
The ability to measure the transcriptional response after a stimulus has drawn much attention to the underlying gene regulatory networks. Several machine learning related methods, such as Bayesian...
EDISA: extracting biclusters from multiple time-series of gene expression profiles (2007)
Supper, Jochen, Strauch, Martin, Wanke, Dierk, Harter, Klaus, Zell, Andreas
Abstract Background Cells dynamically adapt their gene expression patterns in response to various stimuli. This response is orchestrated into a number of gene expression modules consisting of...
Strauch, Martin, Supper, Jochen, Spieth, Christian, Wanke, Dierk, Kilian, Joachim, Harter, Klaus, ...
We developed an integrative approach for discovering gene modules, i.e. genes that are tightly correlated under several experimental conditions and applied it to a threedimensional Arabidopsis...
EDISA: extracting biclusters from multiple time-series of gene expression profiles
Supper, Jochen, Strauch, Martin, Wanke, Dierk, Harter, Klaus, Zell, Andreas
SBMLsqueezer: A CellDesigner plug-in to generate kinetic rate equations for biochemical networks
Dräger, Andreas, Hassis, Nadine, Supper, Jochen, Schröder, Adrian, Zell, Andreas