Christian Baumgartner

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In high-dimensional feature spaces traditional clustering algorithms tend to break down in terms of efficiency and quality. Nevertheless, the data sets often contain clusters which are hidden in various subspaces of the original feature space. In this paper, we present a feature selection technique called SURFING (subspaces relevant for clustering) that(More)
Machine learning has a great potential to mine potential markers from high-dimensional metabolic data without any a priori knowledge. Exemplarily, we investigated metabolic patterns of three severe metabolic disorders, PAHD, MCADD, and 3-MCCD, on which we constructed classification models for disease screening and diagnosis using a decision tree paradigm(More)
MOTIVATION Alcoholic fatty liver disease (AFLD) and non-AFLD (NAFLD) can progress to severe liver diseases such as steatohepatitis, cirrhosis and cancer. Thus, the detection of early liver disease is essential; however, minimal invasive diagnostic methods in clinical hepatology still lack specificity. RESULTS Ion molecule reaction mass spectrometry(More)
Emerging metabolomic tools have created the opportunity to establish metabolic signatures of myocardial injury. We applied a mass spectrometry-based metabolite profiling platform to 36 patients undergoing alcohol septal ablation treatment for hypertrophic obstructive cardiomyopathy, a human model of planned myocardial infarction (PMI). Serial blood samples(More)
MOTIVATION During the Bavarian newborn screening programme all newborns have been tested for about 20 inherited metabolic disorders. Owing to the amount and complexity of the generated experimental data, machine learning techniques provide a promising approach to investigate novel patterns in high-dimensional metabolic data which form the source for(More)
OBJECTIVE Aortic complications determine the life expectancy of most patients with Marfan syndrome. To find out whether there is heterogenous aortic involvement among patients and, if there is, to characterize aortic patterns and response to long-term beta-blocker therapy, we investigated aortic elastic properties before and during beta-blocker treatment.(More)
UNLABELLED New biomarkers are needed to improve the specificity of prostate cancer detection and characterisation of individual tumors. In a proteomics profiling approach using MALDI-MS tissue imaging on frozen tissue sections, we identified discriminating masses. Imaging analysis of cancer, non-malignant benign epithelium and stromal areas of 15(More)
BACKGROUND Little is known about the effect of cardiac resynchronization therapy (CRT) on endo- and epicardial ventricular activation. Noninvasive imaging of cardiac electrophysiology (NICE) is a novel imaging tool for visualization of both epi- and endocardial ventricular electrical activation. METHODOLOGY/PRINCIPAL FINDINGS NICE was performed in ten(More)
A novel computational approach, termed Search for Modified Peptides (SeMoP), for the unrestricted discovery and verification of peptide modifications in shotgun proteomic experiments using low resolution ion trap MS/MS spectra is presented. Various peptide modifications, including post-translational modifications, sequence polymorphisms, as well as sample(More)
OBJECTIVES Cardiovascular diseases are the most frequent cause of death in industrialized countries. Non-adherence with prescribed medication and recommended lifestyle changes significantly increases the risk of major cardiovascular events. The telemonitoring programme MyCor (Myokardinfarkt und Koronarstent Programm in Tirol) is a multi-modal intervention(More)