University of Hamburg

About: University of Hamburg is a education organization based out in Hamburg, Germany. It is known for research contribution in the topics: Population & Laser. The organization has 45564 authors who have published 89286 publications receiving 2850161 citations. The organization is also known as: Hamburg University.

Mitochondrial portraits of human populations using median networks.

Abstract: Analysis of variation in the hypervariable region of mitochondrial DNA (mtDNA) has emerged as an important tool for studying human evolution and migration. However, attempts to reconstruct optimal intraspecific mtDNA phylogenies frequently fail because parallel mutation events partly obscure the true evolutionary pathways. This makes it inadvisable to present a single phylogenetic tree at the expense of neglecting equally acceptable ones. As an alternative, we propose a novel network approach for portraying mtDNA relationships. For small sample sizes (< approximately 50), an unmodified median network contains all most parsimonious trees, displays graphically the full information content of the sequence data, and can easily be generated by hand. For larger sample sizes, we reduce the complexity of the network by identifying parallelisms. This reduction procedure is guided by a compatibility argument and an additional source of phylogenetic information: the frequencies of the mitochondrial haplotypes. As a spin-off, our approach can also assist in identifying sequencing errors, which manifest themselves in implausible network substructures. We illustrate the advantages of our approach with several examples from existing data sets.

From noncoding variant to phenotype via SORT1 at the 1p13 cholesterol locus

Abstract: Recent genome-wide association studies (GWASs) have identified a locus on chromosome 1p13 strongly associated with both plasma low-density lipoprotein cholesterol (LDL-C) and myocardial infarction (MI) in humans. Here we show through a series of studies in human cohorts and human-derived hepatocytes that a common noncoding polymorphism at the 1p13 locus, rs12740374, creates a C/EBP (CCAAT/enhancer binding protein) transcription factor binding site and alters the hepatic expression of the SORT1 gene. With small interfering RNA (siRNA) knockdown and viral overexpression in mouse liver, we demonstrate that Sort1 alters plasma LDL-C and very low-density lipoprotein (VLDL) particle levels by modulating hepatic VLDL secretion. Thus, we provide functional evidence for a novel regulatory pathway for lipoprotein metabolism and suggest that modulation of this pathway may alter risk for MI in humans. We also demonstrate that common noncoding DNA variants identified by GWASs can directly contribute to clinical phenotypes.

Benchmarking Classification Models for Software Defect Prediction: A Proposed Framework and Novel Findings

Abstract: Software defect prediction strives to improve software quality and testing efficiency by constructing predictive classification models from code attributes to enable a timely identification of fault-prone modules. Several classification models have been evaluated for this task. However, due to inconsistent findings regarding the superiority of one classifier over another and the usefulness of metric-based classification in general, more research is needed to improve convergence across studies and further advance confidence in experimental results. We consider three potential sources for bias: comparing classifiers over one or a small number of proprietary data sets, relying on accuracy indicators that are conceptually inappropriate for software defect prediction and cross-study comparisons, and, finally, limited use of statistical testing procedures to secure empirical findings. To remedy these problems, a framework for comparative software defect prediction experiments is proposed and applied in a large-scale empirical comparison of 22 classifiers over 10 public domain data sets from the NASA Metrics Data repository. Overall, an appealing degree of predictive accuracy is observed, which supports the view that metric-based classification is useful. However, our results indicate that the importance of the particular classification algorithm may be less than previously assumed since no significant performance differences could be detected among the top 17 classifiers.

Phylogeny of All Recognized Species of Ammonia Oxidizers Based on Comparative 16S rRNA and amoA Sequence Analysis: Implications for Molecular Diversity Surveys

Abstract: The current perception of evolutionary relationships and the natural diversity of ammonia-oxidizing bacteria (AOB) is mainly based on comparative sequence analyses of their genes encoding the 16S rRNA and the active site polypeptide of the ammonia monooxygenase (AmoA). However, only partial 16S rRNA sequences are available for many AOB species and most AOB have not yet been analyzed on the amoA level. In this study, the 16S rDNA sequence data of 10 Nitrosomonas species and Nitrosococcus mobilis were completed. Furthermore, previously unavailable 16S rRNA sequences were determined for three Nitrosomonas sp. isolates and for the gamma-subclass proteobacterium Nitrosococcus halophilus. These data were used to revaluate the specificities of published oligonucleotide primers and probes for AOB. In addition, partial amoA sequences of 17 AOB, including the above-mentioned 15 AOB, were obtained. Comparative phylogenetic analyses suggested similar but not identical evolutionary relationships of AOB by using 16S rRNA and AmoA as marker molecules, respectively. The presented 16S rRNA and amoA and AmoA sequence data from all recognized AOB species significantly extend the currently used molecular classification schemes for AOB and now provide a more robust phylogenetic framework for molecular diversity inventories of AOB. For 16S rRNA-independent evaluation of AOB species-level diversity in environmental samples, amoA and AmoA sequence similarity threshold values were determined which can be used to tentatively identify novel species based on cloned amoA sequences. Subsequently, 122 amoA sequences were obtained from 11 nitrifying wastewater treatment plants. Phylogenetic analyses of the molecular isolates showed that in all but two plants only nitrosomonads could be detected. Although several of the obtained amoA sequences were only relatively distantly related to known AOB, none of these sequences unequivocally suggested the existence of previously unrecognized species in the wastewater treatment environments examined.