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MOTIVATION The result of a typical microarray experiment is a long list of genes with corresponding expression measurements. This list is only the starting point for a meaningful biological interpretation. Modern methods identify relevant biological processes or functions from gene expression data by scoring the statistical significance of predefined(More)
BACKGROUND Gene Ontology (GO) is a standard vocabulary of functional terms and allows for coherent annotation of gene products. These annotations provide a basis for new methods that compare gene products regarding their molecular function and biological role. RESULTS We present a new method for comparing sets of GO terms and for assessing the functional(More)
Predicting subcellular localization has become a valuable alternative to time-consuming experimental methods. Major drawbacks of many of these predictors is their lack of interpretability and the fact that they do not provide an estimate of the confidence of an individual prediction. We present YLoc, an interpretable web server for predicting subcellular(More)
  • Marianna Grinberg, Regina M. Stöber, Karolina Edlund, Eugen Rempel, Patricio Godoy, Raymond Reif +34 others
  • 2014
A long-term goal of numerous research projects is to identify biomarkers for in vitro systems predicting toxicity in vivo. Often, transcriptomics data are used to identify candidates for further evaluation. However, a systematic directory summarizing key features of chemically influenced genes in human hepatocytes is not yet available. To bridge this gap,(More)
The development of multicellular organisms is controlled by differential gene expression whereby cells adopt distinct fates. A spatially resolved view of gene expression allows the elucidation of transcriptional networks that are linked to cellular identity and function. The haploid female gametophyte of flowering plants is a highly reduced organism: at(More)
SUMMARY Mixture models of mutagenetic trees constitute a class of probabilistic models for describing evolutionary processes that are characterized by the accumulation of permanent genetic changes. They have been applied to model the accumulation of chromosomal gains and losses in tumor development and the development of drug resistance-associated mutations(More)
We thank the team of the LiDO HPC cluster at the TU Dortmund for their technical support while developing and using both R packages. We also thank Heike Trautmann, Oliver Flasch and Uwe Ligges for helpful discussions and comments. Abstract Empirical analysis of statistical algorithms often demands time-consuming experiments which are best performed on high(More)
MOTIVATION Microarray images challenge existing analytical methods in many ways given that gene spots are often comprised of characteristic imperfections. Irregular contours, donut shapes, artifacts, and low or heterogeneous expression impair corresponding values for red and green intensities as well as their ratio R/G. New approaches are needed to ensure(More)
We present a statistical approach to scoring changes in activity of metabolic pathways from gene expression data. The method identifies the biologically relevant pathways with corresponding statistical significance. Based on gene expression data alone, only local structures of genetic networks can be recovered. Instead of inferring such a network, we(More)
We introduce a mixture model of trees to describe evolutionary processes that are characterized by the accumulation of permanent genetic changes. The basic building block of the model is a directed weighted tree that generates a probability distribution on the set of all patterns of genetic events. We present an EM-like algorithm for learning a mixture(More)