Rene Hussong

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Mass spectrometry is an essential analytical technique for high-throughput analysis in proteomics and metabolomics. The development of new separation techniques, precise mass analyzers and experimental protocols is a very active field of research. This leads to more complex experimental setups yielding ever increasing amounts of data. Consequently, analysis(More)
MOTIVATION Mass spectrometry (MS) is one of the most important techniques for high-throughput analysis in proteomics research. Due to the large number of different proteins and their post-translationally modified variants, the amount of data generated by a single wet-lab MS experiment can easily exceed several gigabytes. Hence, the time necessary to analyze(More)
The human neuroblastoma cell line, SH-SY5Y, is a commonly used cell line in studies related to neurotoxicity, oxidative stress, and neurodegenerative diseases. Although this cell line is often used as a cellular model for Parkinson’s disease, the relevance of this cellular model in the context of Parkinson’s disease (PD) and other neurodegenerative diseases(More)
Liquid chromatography combined with mass spectrometry (LC-MS) has become the prevalent technology in high-throughput proteomics research. One of the aims of this discipline is to obtain accurate quantitative information about all proteins and peptides in a biological sample. Due to size and complexity of the data generated in these experiments, this problem(More)
Liquid chromatography coupled to mass spectrometry (LC-MS) has become a major tool for the study of biological processes. High-throughput LC-MS experiments are frequently conducted in modern laboratories, generating an enormous amount of data per day. A manual inspection is therefore no longer a feasible task. Consequently, there is a need for computational(More)
Computational proteomics applications are often imagined as a pipeline, where information is processed in each stage before it flows to the next one. Independent of the type of application, the first stage invariably consists of obtaining the raw mass spectrometric data from the spectrometer and preparing it for use in the later stages by enhancing the(More)
Computational proteomics is one of today’s foremost challenges in bioinformatics with applications in fields as diverse as toxicology, diagnostics, or target identification and validation. The current de-facto standard for high-throughput proteomics studies, HPLC-MS, is capable of generating huge amounts of data for a single analysis: the LC-MS maps, which(More)
The robust identification of isotope patterns originating from peptides being analyzed through mass spectrometry (MS) is often significantly hampered by noise artifacts and the interference of overlapping patterns arising e.g. from post-translational modifications. As the classification of the recorded data points into either ‘noise’ or ‘signal’ lies at the(More)
This is the vignette of the Bioconductor add-on package IPPD which implements automatic isotopic pattern extraction from a raw protein mass spectrum. Basically, the user only has to provide mass/charge channels and corresponding intensities, which are automatically decomposed into a list of monoisotopic peaks. IPPD can handle several charge states as well(More)