MOTIVATION Proteomics has particularly evolved to become of high interest for the field of biomarker discovery and drug development. Especially the combination of liquid chromatography and mass spectrometry (LC/MS) has proven to be a powerful technique for analyzing protein mixtures. Clinically orientated proteomic studies will have to compare hundreds of… (More)
LC/MS is a successful analysis technique for the statistical analysis used in several branches of biology. It requires an intense screening and combination of the raw data, which is usually done with programs and libraries invoked by scripts in the domain-specific statistics language S or R. We show here how to model and implement this complex workflow in a… (More)
OBJECTIVE The Pulmonary Arterial hyperTENsion sGC-stimulator Trial-1 (PATENT-1) was a randomised, double-blind, placebo-controlled phase III trial evaluating riociguat in patients with pulmonary arterial hypertension (PAH). PATENT-2 was an open-label long-term extension to PATENT-1. Here, we explore the efficacy and safety of riociguat in the subgroup of… (More)
In this paper we address the problem of choosing a single clustering estimatê c based on an MCMC sample of clusterings c from the posterior distribution of a Bayesian cluster model. Methods to derivê c based on the posterior similarity matrix, a matrix with entries P (c i = c j |y), the posterior probabilities that the observations i and j are in the same… (More)
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Background: Subgroup analyses are commonly and increasingly performed in confirmatory clinical trials, where the treatment effect is estimated in subgroups of the overall trial population defined by certain patient characteristics, eg age, gender, region, severity of disease, or co-medications.
Current research in experimental particle physics is dominated by high profile and large scale experiments. One of the major tasks in these experiments is the selection of interesting or relevant events. In this paper we propose to use statistical classification algorithms for this task. To illustrate our method we apply it to an Monte-Carlo (MC) dataset… (More)