Refine
Year of publication
- 2014 (1199) (remove)
Document Type
- Article (579)
- Part of Periodical (157)
- Working Paper (149)
- Book (134)
- Doctoral Thesis (86)
- Report (27)
- Part of a Book (23)
- Conference Proceeding (18)
- Review (10)
- Preprint (8)
- Master's Thesis (6)
- Bachelor Thesis (1)
- Habilitation (1)
Language
- English (1199) (remove)
Has Fulltext
- yes (1199) (remove)
Is part of the Bibliography
- no (1199) (remove)
Keywords
- taxonomy (21)
- new species (19)
- Syntax (11)
- Inversionsfigur (10)
- Multistability (10)
- Multistable figures (10)
- Wahrnehmungswechsel (10)
- morphology (8)
- Bantusprachen (7)
- Coleoptera (7)
Institute
- Medizin (231)
- Wirtschaftswissenschaften (149)
- Center for Financial Studies (CFS) (131)
- Physik (101)
- Biowissenschaften (88)
- Sustainable Architecture for Finance in Europe (SAFE) (86)
- House of Finance (HoF) (82)
- Biochemie und Chemie (48)
- Geowissenschaften (41)
- Gesellschaftswissenschaften (33)
Background: Simple peak-picking algorithms, such as those based on lineshape fitting, perform well when peaks are completely resolved in multidimensional NMR spectra, but often produce wrong intensities and frequencies for overlapping peak clusters. For example, NOESY-type spectra have considerable overlaps leading to significant peak-picking intensity errors, which can result in erroneous structural restraints. Precise frequencies are critical for unambiguous resonance assignments.
Results: To alleviate this problem, a more sophisticated peaks decomposition algorithm, based on non-negative matrix factorization (NMF), was developed. We produce peak shapes from Fourier-transformed NMR spectra. Apart from its main goal of deriving components from spectra and producing peak lists automatically, the NMF approach can also be applied if the positions of some peaks are known a priori, e.g. from consistently referenced spectral dimensions of other experiments.
Conclusions: Application of the NMF algorithm to a three-dimensional peak list of the 23 kDa bi-domain section of the RcsD protein (RcsD-ABL-HPt, residues 688-890) as well as to synthetic HSQC data shows that peaks can be picked accurately also in spectral regions with strong overlap.
Ribosome heterogeneity is of increasing biological significance and several examples have been described for multicellular and single cells organisms. In here we show for the first time a variation in ribose methylation within the 18S rRNA of Saccharomyces cerevisiae. Using RNA-cleaving DNAzymes, we could specifically demonstrate that a significant amount of S. cerevisiae ribosomes are not methylated at 2′-O-ribose of A100 residue in the 18S rRNA. Furthermore, using LC-UV-MS/MS of a respective 18S rRNA fragment, we could not only corroborate the partial methylation at A100, but could also quantify the methylated versus non-methylated A100 residue. Here, we exhibit that only 68% of A100 in the 18S rRNA of S.cerevisiae are methylated at 2′-O ribose sugar. Polysomes also contain a similar heterogeneity for methylated Am100, which shows that 40S ribosome subunits with and without Am100 participate in translation. Introduction of a multicopy plasmid containing the corresponding methylation guide snoRNA gene SNR51 led to an increased A100 methylation, suggesting the cellular snR51 level to limit the extent of this modification. Partial rRNA modification demonstrates a new level of ribosome heterogeneity in eukaryotic cells that might have substantial impact on regulation and fine-tuning of the translation process.
Banks' financial distress, lending supply and consumption expenditure : [version december 2013]
(2014)
The paper employs a unique identification strategy that links survey data on household consumption expenditure to bank level data in order to estimate the effects of bank financial distress on consumer credit and consumption expenditures. Specifically, we show that households whose banks were more exposed to funding shocks report significantly lower levels of non-mortgage liabilities compared to a matched sample of households. The reduced access to credit, however, does not result in lower levels of consumption. Instead, we show that households compensate by drawing down liquid assets. Only households without the ability to draw on liquid assets reduce consumption. The results are consistent with consumption smoothing in the face of a temporary adverse lending supply shock. The results contrast with recent evidence on the real effects of finance on firms' investment, where even temporary adverse credit supply shocks are associated with significant real effects.
Inflation differentials in the euro area have been persistent since the adoption of the single currency. This paper analyzes the impact of product and labor market regulation on inflation in a sample of 11 countries. The results show that, after the adoption of the euro, product market deregulation has a relevant and significant effect on the level of inflation, while higher labor market regulation increases the responsiveness of inflation to the output gap.
We propose an iterative procedure to efficiently estimate models with complex log-likelihood functions and the number of parameters relative to the observations being potentially high. Given consistent but inefficient estimates of sub-vectors of the parameter vector, the procedure yields computationally tractable, consistent and asymptotic efficient estimates of all parameters. We show the asymptotic normality and derive the estimator's asymptotic covariance in dependence of the number of iteration steps. To mitigate the curse of dimensionality in high-parameterized models, we combine the procedure with a penalization approach yielding sparsity and reducing model complexity. Small sample properties of the estimator are illustrated for two time series models in a simulation study. In an empirical application, we use the proposed method to estimate the connectedness between companies by extending the approach by Diebold and Yilmaz (2014) to a high-dimensional non-Gaussian setting.
Computational analyses of functions of gene sets obtained in microarray analyses or by topical database searches are increasingly important in biology. To understand their functions, the sets are usually mapped to Gene Ontology knowledge bases by means of over-representation analysis (ORA). Its result represents the specific knowledge of the functionality of the gene set. However, the specific ontology typically consists of many terms and relationships, hindering the understanding of the ‘main story’. We developed a methodology to identify a comprehensibly small number of GO terms as “headlines” of the specific ontology allowing to understand all central aspects of the roles of the involved genes. The Functional Abstraction method finds a set of headlines that is specific enough to cover all details of a specific ontology and is abstract enough for human comprehension. This method exceeds the classical approaches at ORA abstraction and by focusing on information rather than decorrelation of GO terms, it directly targets human comprehension. Functional abstraction provides, with a maximum of certainty, information value, coverage and conciseness, a representation of the biological functions in a gene set plays a role. This is the necessary means to interpret complex Gene Ontology results thus strengthening the role of functional genomics in biomarker and drug discovery.
Imitation paradigms are used in various domains of developmental psychological research to assess various cognitive processes such as memory (deferred imitation), action perception and action understanding (mainly direct imitation), as well as categorization and learning about objects (deferred imitation with a change in target objects and generalized imitation). Although these processes are most likely not independent from each other, their relations are still largely unclear. On the one hand, deferred imitation studies have shown that infants' performance improves with increasing age, resulting in the reproduction of more target actions after longer delay intervals. On the other hand, imitation studies focusing on infants' action understanding have found that infants do not necessarily imitate the model's exact actions – actions or action steps that seem to be irrational or irrelevant are omitted by infants under certain circumstances (selective imitation). Additionally, findings of imitation studies that require a transfer of the target actions to novel objects have demonstrated that infants do not only learn about actions, but also about objects, when they engage in imitation.
The present dissertation aims at integrating different perspectives of imitation research by testing 12- and 18-month-old infants in deferred imitation tests consisting of functional vs. arbitrary target actions, and by combining deferred imitation with eye tracking in half of the experiments. A deferred imitation paradigm was chosen to assess memory performance. Systematic variation of target action characteristics enabled the assessment of infants' imitation pattern, i.e., if they would imitate one kind of target actions more frequently than the other. Functionality was chosen as the action characteristic in focus because function is an object's most important property, thus this variation might shed some light on infants' learning about objects in the context of an imitation test. The main goal of the eye tracking experiments was to tackle the relations between infants' visual attention to, and deferred imitation of, different kinds of target actions.
The behavioral experiments revealed that both 12- and 18-month-olds imitated significantly more functional than arbitrary target actions after a delay of 30 minutes. In addition, while 12-month-olds showed a memory effect only for functional actions, 18-month-olds showed a memory effect for both kinds of actions. Thus, 12-month-olds imitated strictly selectively, and 18-month-olds imitated more exactly. This shows that the well established memory effect is modulated by target action functionality, which affects 12- and 18-month-olds' imitation differently. Furthermore, when retested after a two weeks delay, 18-month-olds' performance rates of functional and arbitrary target actions decreased parallel. This suggests that selective imitation is not affected by the duration of the retention interval, and that selection of target actions takes place at an earlier stage of action perception and memory processes.
In the eye tracking experiments, both 12- and 18-month-olds' imitation patterns replicated the findings of the behavioral experiments, showing consistently higher imitation rates of functional than arbitrary target actions. Contrary to this, infants' fixation times to the target actions were not affected by target action functionality. This contrast was supported by statistical analyses that found no clear correspondence between visual attention to and deferred imitation of target actions. This suggests that selective imitation cannot be explained by selective visual attention. Nevertheless, finer-grained analyses of gaze and imitation data in the 18 months old group suggested that infants' increased attention to the social-communicative context of the imitation task was related to more exact imitation, i.e. imitation of not only functional, but also arbitrary target actions.
The findings are discussed against the background of imitation theories, with regard to the relations between different cognitive processes underlying infants' imitation, such as memory, action perception and learning about objects.
Protein signatures of oxidative stress response in a patient specific cell line model for autism
(2014)
Background: Known genetic variants can account for 10% to 20% of all cases with autism spectrum disorders (ASD). Overlapping cellular pathomechanisms common to neurons of the central nervous system (CNS) and in tissues of peripheral organs, such as immune dysregulation, oxidative stress and dysfunctions in mitochondrial and protein synthesis metabolism, were suggested to support the wide spectrum of ASD on unifying disease phenotype. Here, we studied in patient-derived lymphoblastoid cell lines (LCLs) how an ASD-specific mutation in ribosomal protein RPL10 (RPL10[H213Q]) generates a distinct protein signature. We compared the RPL10[H213Q] expression pattern to expression patterns derived from unrelated ASD patients without RPL10[H213Q] mutation. In addition, a yeast rpl10 deficiency model served in a proof-of-principle study to test for alterations in protein patterns in response to oxidative stress.
Methods: Protein extracts of LCLs from patients, relatives and controls, as well as diploid yeast cells hemizygous for rpl10, were subjected to two-dimensional gel electrophoresis and differentially regulated spots were identified by mass spectrometry. Subsequently, Gene Ontology database (GO)-term enrichment and network analysis was performed to map the identified proteins into cellular pathways.
Results: The protein signature generated by RPL10[H213Q] is a functionally related subset of the ASD-specific protein signature, sharing redox-sensitive elements in energy-, protein- and redox-metabolism. In yeast, rpl10 deficiency generates a specific protein signature, harboring components of pathways identified in both the RPL10[H213Q] subjects' and the ASD patients' set. Importantly, the rpl10 deficiency signature is a subset of the signature resulting from response of wild-type yeast to oxidative stress.
Conclusions: Redox-sensitive protein signatures mapping into cellular pathways with pathophysiology in ASD have been identified in both LCLs carrying the ASD-specific mutation RPL10[H213Q] and LCLs from ASD patients without this mutation. At pathway levels, this redox-sensitive protein signature has also been identified in a yeast rpl10 deficiency and an oxidative stress model. These observations point to a common molecular pathomechanism in ASD, characterized in our study by dysregulation of redox balance. Importantly, this can be triggered by the known ASD-RPL10[H213Q] mutation or by yet unknown mutations of the ASD cohort that act upstream of RPL10 in differential expression of redox-sensitive proteins.
Even though fiscal sovereignty still counts as a fundamental principle of government, global and regional economic integration as well as increasing levels of sovereign debt severely limit governments’ tax policy choices. In particular the redistributive function of taxation has suffered in the pursuit of economic competitiveness. As inequality rises and attention is directed again at taxation as a means for redistribution, international cooperation appears as an avenue to enable redistribution through taxation. Yet, one of the predominant international institutions dealing with tax matters – the OECD – with its focus on economic growth and competitiveness and resulting tax policy advice prevents rather than promotes national and international debates on taxation as a question of social justice. The paper argues that questions of taxation need to be perceived as questions of social justice and thus as questions of politics, and not merely of economics. Only if taxation is not considered a mere economic instrument can a ‘political economy’ be maintained. The paper addresses the three objectives of taxation – revenue generation, redistribution and regulation -- and how they are affected as governments aim for fiscal consolidation to conclude that governments’ power to freely pursue and calibrate these objectives has come to appear rather as a myth than the core of sovereignty. It then demonstrates how the OECD’s tax policy advice and cooperation in tax matters react to the constraints on governmental taxation powers; how they aim at economic growth and competitiveness to the detriment of (other) ideas of social justice. The paper concludes with a call for (re)integrating social and global justice concerns into debates on taxation.
The work presented in this thesis is devoted to two classes of mathematical population genetics models, namely the Kingman-coalescent and the Beta-coalescents. Chapters 2, 3 and 4 of the thesis include results concerned with the first model, whereas Chapter 5 presents contributions to the second class of models.