Sebastian Dümcke

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To obtain rates of mRNA synthesis and decay in yeast, we established dynamic transcriptome analysis (DTA). DTA combines non-perturbing metabolic RNA labeling with dynamic kinetic modeling. DTA reveals that most mRNA synthesis rates are around several transcripts per cell and cell cycle, and most mRNA half-lives range around a median of 11 min. DTA can(More)
Nonerosive reflux disease (NERD) is commonly diagnosed in patients with symptoms of reflux. The aim of the present study was to determine whether high-definition endoscopy (HD) plus equipped with the iScan function or chromoendoscopy with Lugol's solution might permit the differentiation of NERD patients from those without reflux symptoms, proven by(More)
AIM To evaluate the diagnostic yield (inflammatory activity) and efficiency (size of the biopsy specimen) of SpyGlass(TM)-guided biopsy vs standard brush cytology in patients with and without primary sclerosing cholangitis (PSC). METHODS At the University Medical Center Mainz, Germany, 35 consecutive patients with unclear biliary lesions (16 patients) or(More)
Standard transcriptomics measures total cellular RNA levels. Our understanding of gene regulation would be greatly improved if we could measure RNA synthesis and decay rates on a genome-wide level. To that end, the Dynamic Transcriptome Analysis (DTA) method has been developed. DTA combines metabolic RNA labeling with standard transcriptomics to measure RNA(More)
MOTIVATION For biological pathways, it is common to measure a gene expression time series after various knockdowns of genes that are putatively involved in the process of interest. These interventional time-resolved data are most suitable for the elucidation of dynamic causal relationships in signaling networks. Even with this kind of data it is still a(More)
We present One Hand Clapping (OHC), a method for the detection of condition-specific interactions between transcription factors (TFs) from genome-wide gene activity measurements. OHC is based on a mapping between transcription factors and their target genes. Given a single case-control experiment, it uses a linear regression model to assess whether the(More)
Dependence measures and tests for independence have recently attracted a lot of attention, because they are the cornerstone of algorithms for network inference in probabilistic graphical models. Pearson’s product moment correlation coefficient is still by far the most widely used statistic yet it is largely constrained to detecting linear relationships. In(More)
Hidden Markov models (HMMs) have been extensively used to dissect the genome into functionally distinct regions using data such as RNA expression or DNA binding measurements. It is a challenge to disentangle processes occurring on complementary strands of the same genomic region. We present the double-stranded HMM (dsHMM), a model for the strand-specific(More)
Dependence measures and tests for independence have recently attracted a lot of attention, because they are the cornerstone of algorithms for network inference in probabilistic graphical models. Pearson's product moment correlation coefficient is still by far the most widely used statistic yet it is largely constrained to detecting linear relationships. In(More)
Total RNA levels in a cell are the consequence of two opposing mechanisms, namely RNA synthesis and RNA degradation. DTA allows monitoring these contributions in a non-perturbing manner. It is provided with a kinetic modeling approach capable of the precise determination of synthesisand decay rates, which is implemented in this package (see supplementary(More)
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