Fröhlich, Holger, Sahin, Özgür, Arlt, Dorit, Bender, Christian, Beißbarth, Tim
Abstract Background Modern gene perturbation techniques, like RNA interference (RNAi), enable us to study effects of targeted interventions in cells efficiently. In combination with mRNA or protein...
Sahin, Özgür, Fröhlich, Holger, Löbke, Christian, Korf, Ulrike, Burmester, Sara, Majety, Meher, ...
Abstract Background In breast cancer, overexpression of the transmembrane tyrosine kinase ERBB2 is an adverse prognostic marker, and occurs in almost 30% of the patients. For therapeutic...
A Bayesian Network View on Nested Effects Models (2009)
Cordula Zeller, Holger Fröhlich, Achim Tresch
Nested effects models (NEMs) are a class of probabilistic models that were designed to reconstruct a hidden signalling structure from a large set of observable effects caused by active interventions...
Holger Fröhlich, Jörg K. Wegner, Florian Sieker, Andreas Zell
Full Paper Kernel methods, like the well-known Support Vector Machine (SVM), have gained a growing interest during the last years for designing QSAR/QSPR models having a high predictive strength. One...
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...
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...
Holger Fröhlich, Jörg K. Wegner, Andreas Zell, Regularized Risk Minimization
Abstract. In this paper we present a novel method for selecting descriptor subsets by means of Support Vector Machines in classification and regression – the Incremental Regularized Risk...
Holger Fröhlich, Jörg K. Wegner, Florian Sieker, Andreas Zell
Full Paper Kernel methods, like the well-known Support Vector Machine (SVM), have gained a growing interest during the last years for designing QSAR/QSPR models having a high predictive strength. One...
Predicting pathway membership via domain signatures (2008)
Fröhlich, Holger, Fellmann, Mark, Sültmann, Holger, Poustka, Annemarie, Beißbarth, Tim
Motivation: Functional characterization of genes is of great importance for the understanding of complex cellular processes. Valuable information for this purpose can be obtained from pathway...
Fröhlich, Holger, Fellmann, Mark, Sültmann, Holger, Poustka, Annemarie, Beissbarth, Tim
Motivation: Targeted interventions using RNA interference in combination with the measurement of secondary effects with DNA microarrays can be used to computationally reverse engineer features of...
Analyzing gene perturbation screens with nested effects models in R and bioconductor (2008)
Fröhlich, Holger, Beißbarth, Tim, Tresch, Achim, Kostka, Dennis, Jacob, Juby, Spang, Rainer, ...
Summary: Nested effects models (NEMs) are a class of probabilistic models introduced to analyze the effects of gene perturbation screens visible in high-dimensional phenotypes like microarrays or...
Fröhlich, Holger, Speer, Nora, Poustka, Annemarie, Beißbarth, Tim
Abstract Background With the increased availability of high throughput data, such as DNA microarray data, researchers are capable of producing large amounts of biological data. During the analysis of...
Bmc Bioinformatics, Holger Fröhlich, Nora Speer, Annemarie Poustka, Tim Beißbarth, Biomed Central, ...
Software GOSim – an R-package for computation of information theoretic
Vibration-based terrain classification using support vector machines (2006)
Christian Weiss, Holger Fröhlich, Andreas Zell
Abstract — In outdoor environments, there is a variety of different types of ground surfaces. If some of them are slippery or bumpy, for example, the ground surface itself is a possible hazard for...
Functional Grouping of Genes Using Spectral Clustering And Gene Ontology (2005)
Nora Speer, Holger Fröhlich, Christian Spieth, Andreas Zell
With the invention of high throughput methods, researchers are capable of producing large amounts of biological data. During the analysis of such data the need for a functional grouping of genes...
Which Features Trigger Action Potentials in (2005)
Cortical Neurons In, Holger Fröhlich, Maxim Volgushev
We study the initiation of action potentials (APs) in in vivo recordings of cortical neurons from cat visual cortex. Recently, it was shown that cortical neurons are not simple threshold devices,...
Optimal assignment kernels for attributed molecular graphs (2005)
Holger Fröhlich, Jörg K. Wegner, Florian Sieker, Andreas Zell
We propose a new kernel function for attributed molecular graphs, which is based on the idea of computing an optimal assignment from the atoms of one molecule to those of another one, including...
Functional Distances for Genes Based on GO Feature Maps and their Application to (2005)
Nora Speer, Holger Fröhlich, Christian Spieth, Andreas Zell
Abstract — With the invention of high throughput methods, researchers are capable of producing large amounts of biological data. During the analysis of such data, the need for a functional grouping...
Gas Source Declaration with a Mobile Robot (2004)
Achim Lilienthal, Holger Ulmer, Holger Fröhlich, Andreas Stützle, Felix Werner, Andreas Zell
Abstract — As a sub-task of the general gas source localisation problem, gas source declaration is the process of determining the certainty that a source is in the immediate vicinity. Due to the...
Feature Selection for Support Vector Machines by Means of Genetic Algorithms (2002)
Holger Fröhlich, A. Ultsch, Prof Dr, Prof Dr, B. Scholkopf
Contents 1 Introduction 3 2 Theoretical Background 6 2.1 General Prerequisites --- Pattern Recognition in Statistical Learning Theory . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.2 What are...
Predicting pathway membership via domain signatures
Fröhlich, Holger, Fellmann, Mark, Sültmann, Holger, Poustka, Annemarie, Beißbarth, Tim
Motivation: Functional characterization of genes is of great importance for the understanding of complex cellular processes. Valuable information for this purpose can be obtained from pathway...
Fröhlich, Holger, Fellmann, Mark, Sültmann, Holger, Poustka, Annemarie, Beissbarth, Tim
Motivation: Targeted interventions using RNA interference in combination with the measurement of secondary effects with DNA microarrays can be used to computationally reverse engineer features of...
A Bayesian Network View on Nested Effects Models
Zeller, Cordula, Fröhlich, Holger, Tresch, Achim
Nested effects models (NEMs) are a class of probabilistic models that were designed to reconstruct a hidden signalling structure from a large set of observable effects caused by active interventions...
Analyzing gene perturbation screens with nested effects models in R and bioconductor
Fröhlich, Holger, Beißbarth, Tim, Tresch, Achim, Kostka, Dennis, Jacob, Juby, Spang, Rainer, ...
Summary: Nested effects models (NEMs) are a class of probabilistic models introduced to analyze the effects of gene perturbation screens visible in high-dimensional phenotypes like microarrays or...