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Martin von Bergen

Researcher at Helmholtz Centre for Environmental Research - UFZ

Publications -  395
Citations -  19405

Martin von Bergen is an academic researcher from Helmholtz Centre for Environmental Research - UFZ. The author has contributed to research in topics: Medicine & Biology. The author has an hindex of 58, co-authored 346 publications receiving 15305 citations. Previous affiliations of Martin von Bergen include Max Planck Society & Leipzig University.

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Improving protein extraction and separation methods for investigating the metaproteome of anaerobic benzene communities within sediments.

Dirk Benndorf, +9 more
- 21 Apr 2009 - 
TL;DR: The identification of several proteins confirmed that this procedure has the capacity to analyse the metaproteome of an anoxic living microbial community.
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Relationship between sources and patterns of VOCs in indoor air

Carolin Rösch, +5 more
- 01 Jan 2014 - 
TL;DR: In this article, a study of flats in Leipzig (Germany) is based on measurements of 60 different VOCs and is unique in the field of indoor air quality due to its enormous size of samples (n = 2 242) and questionnaire data.
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Metabolomic biomarkers correlating with hepatic lipidosis in dairy cows

Sandro Imhasly, +8 more
- 02 Jun 2014 - 
TL;DR: This proof-of-concept study indicates that metabolomic profiles, including both amino acids and lipids, distinguish hepatic lipidosis from other peripartal disorders and, hence, provide a promising new tool for the diagnosis of hepatic cholesterolosis.
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Structure, stability, and aggregation of paired helical filaments from tau protein and FTDP-17 mutants probed by tryptophan scanning mutagenesis.

Li Li, +3 more
- 01 Nov 2002 - 
TL;DR: The stability of PHF stability increases with the number of repeats and with tau mutants promoting β-structure, arguing for a gain of toxic function in frontotemporal dementias.
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Random Survival Forest in practice: a method for modelling complex metabolomics data in time to event analysis

Stefan Dietrich, +17 more
- 01 Oct 2016 - 
TL;DR: The demonstrated RSF approach provides comparable findings as the generally used Cox regression, but also addresses the problem of multicollinearity and is suitable for high-dimensional data.