Universitätspublikationen
Refine
Year of publication
- 2009 (612) (remove)
Document Type
- Article (180)
- Doctoral Thesis (116)
- Part of Periodical (101)
- Book (64)
- Review (49)
- Conference Proceeding (26)
- Working Paper (17)
- Report (13)
- Diploma Thesis (11)
- Bachelor Thesis (9)
Language
- German (367)
- English (228)
- French (7)
- Portuguese (7)
- Spanish (2)
- Multiple languages (1)
Is part of the Bibliography
- no (612)
Keywords
- Europa (7)
- Deutschland (4)
- Lambda-Kalkül (4)
- China (3)
- Forschung (3)
- Frankfurt <Main> / Universität (3)
- Frankreich (3)
- Zeitschrift (3)
- reactive oxygen species (3)
- Adorno (2)
Institute
- Medizin (122)
- Präsidium (75)
- Biochemie und Chemie (47)
- Gesellschaftswissenschaften (46)
- Rechtswissenschaft (41)
- Geowissenschaften (34)
- Physik (33)
- Biowissenschaften (32)
- E-Finance Lab e.V. (24)
- Informatik (24)
Understanding the dynamics of recurrent neural networks is crucial for explaining how the brain processes information. In the neocortex, a range of different plasticity mechanisms are shaping recurrent networks into effective information processing circuits that learn appropriate representations for time-varying sensory stimuli. However, it has been difficult to mimic these abilities in artificial neural network models. Here we introduce SORN, a self-organizing recurrent network. It combines three distinct forms of local plasticity to learn spatio-temporal patterns in its input while maintaining its dynamics in a healthy regime suitable for learning. The SORN learns to encode information in the form of trajectories through its high-dimensional state space reminiscent of recent biological findings on cortical coding. All three forms of plasticity are shown to be essential for the network's success. Keywords: synaptic plasticity, intrinsic plasticity, recurrent neural networks, reservoir computing, time series prediction
Diese Arbeit untersuchte die Epidemiologie und den Einfluss verschiedener Faktoren (Grunderkrankung, empirische Therapie, Schweregrad der Sepsis und Erreger mit Resistenz) auf das Überleben von Patienten mit Septikämien. Die häufigsten Grunderkrankungen dieses Kollektivs waren Leukämien (33%), solide Neoplasien (14%) sowie kardiale Vorerkrankungen (14%). Knapp die Hälfte der Patienten erwarb die Septikämie im Krankenhaus (47%). ...
The pictorial art of the Church, as a spiritual product of the Christian civilisation, has continually received great influences from its ecclesiastical tradition and it was defined by its formal aesthetical standards and its iconographic preferences. A more nuanced reading of the parallels can be attained by placing the images in their visual context, which would allow a better appreciation of the meanings within. The biblical story of Adam and Eve, which is the theme of the following thesis, reflects the differentiation between the Eastern and the Western understanding of the events of the history of the holy Oikonomia, a point, which is the major ground for the development of the relative pictorial motifs. The protoplasts are the protagonists from their creation and life in paradise, the fall and expulsion until their resurrection through Christ. Their story is visualised in a number of scenes and episodes, having thus their original sin and resurrection for specific reasons centralised. This doctoral thesis attempts to collect as many parallels of the scenes is possible, trying to collate the Eastern with the Western visual approach in a deductive way, in order to reach our constructive conclusions and make available the combination of the art, theology and liturgy in the scenes of Adam and Eve in Genesis and in Resurrection (Anastasis). The reading we tried to perform was based upon the specific iconographical elements, which were worth to be commented. Our aim was to detect the direct bond between the production of art and the relevant patristic and apocryphal writings or even the theological theories, by quoting texts from the ecclesiastical literature, as well as the liturgical praxis.
Background: Pathogenic bacteria infecting both animals as well as plants use various mechanisms to transport virulence factors across their cell membranes and channel these proteins into the infected host cell. The type III secretion system represents such a mechanism. Proteins transported via this pathway (‘‘effector proteins’’) have to be distinguished from all other proteins that are not exported from the bacterial cell. Although a special targeting signal at the N-terminal end of effector proteins has been proposed in literature its exact characteristics remain unknown. Methodology/Principal Findings: In this study, we demonstrate that the signals encoded in the sequences of type III secretion system effectors can be consistently recognized and predicted by machine learning techniques. Known protein effectors were compiled from the literature and sequence databases, and served as training data for artificial neural networks and support vector machine classifiers. Common sequence features were most pronounced in the first 30 amino acids of the effector sequences. Classification accuracy yielded a cross-validated Matthews correlation of 0.63 and allowed for genome-wide prediction of potential type III secretion system effectors in 705 proteobacterial genomes (12% predicted candidates protein), their chromosomes (11%) and plasmids (13%), as well as 213 Firmicute genomes (7%). Conclusions/Significance: We present a signal prediction method together with comprehensive survey of potential type III secretion system effectors extracted from 918 published bacterial genomes. Our study demonstrates that the analyzed signal features are common across a wide range of species, and provides a substantial basis for the identification of exported pathogenic proteins as targets for future therapeutic intervention. The prediction software is publicly accessible from our web server ( www.modlab.org ).
Bacterial autotransporters represent a diverse family of proteins that autonomously translocate across the inner membrane of Gram-negative bacteria via the Sec complex and across the outer bacterial membrane. They often possess exceptionally long N-terminal signal sequences. We analyzed 90 long signal sequences of bacterial autotransporters and members of the two-partner secretion pathway in silico and describe common domain organization found in 79 of these sequences. The domains are in agreement with previously published experimental data. Our algorithmic approach allows for the systematic identification of functionally different domains in long signal sequences. Keywords: bacterial autotransporter, sequence analysis, pattern, protein targeting, signal peptide, protein trafficking
Streptomyces coelicolor ist der Modellorganismus der GC reichen, Gram+ Actinomyceten, die mehr als zwei Drittel aller bekannten Antibiotika produzieren. Phänotypisch zeichnet er sich durch die Bildung eines Substrat- und eines Luftmyzels aus, welches im Laufe der weiteren Differenzierung Sporen bildet. Streptomyceten produzieren neben Antibiotika noch eine Vielzahl biotechnologisch interessanter Metaboliten. Der komplexe Lebenszyklus und Stoffwechsel erfordern eine genaue Regulation der Genexpression. Die letzten Jahre haben gezeigt, dass neben Proteinen auch die RNA eine regulatorische Funktion hat. Verschiedene regulatorisch aktive RNA Elemente wie Riboswitche, RNA-Thermometer und kleine nicht kodierende RNAs (small noncoding RNAs – sRNAs) wurden identifiziert. sRNAs wirken meist als antisense Riboregulatoren, indem sie ihre Ziel-mRNA binden und dadurch die Translation hemmen oder fördern. In dieser Arbeit wurden verschiedene bioinformatische Methoden verwendet, um sRNAs im Genom von S. coelicolor vorherzusagen. Es wurden Terminatorstrukturen und konservierte Sekundärstrukturen in den intergenen Regionen vorhergesagt, die keinem Gen zuzuordnen waren. In einem weiteren Ansatz wurden Bindestellen des Regulatorproteins DasR vorhergesagt, um DasR kontrollierte sRNAs zu identifizieren. Zusätzlich wurde mittels 454 Sequenzierung erstmalig das Transkriptom von S. coeliocolor analysiert. Auf diese Weise konnten etwa 500 sRNAs vorhergesagt werden. Eine der beiden charakterisierten sRNAs, sc32, ist 139 nt lang. Ihr Promoter liegt im kodierenden Bereich des Gens bldC und sie wird spezifisch durch Kälteschock induziert. Die zweite charakterisierte sRNA, sc1, ist 159 nt lang und in allen sequenzierten Streptomyceten konserviert. Ihre Expression wird nur bei Stickstoffmangel in der Stationärphase reprimiert. Durch molekularbiologische Analysen konnte ein Zielgen von sc1 identifiziert werden, die extrazelluläre Agarase DagA. Es konnte gezeigt werden, dass sc1 an die dagA-mRNA bindet und dadurch die Translation inhibiert. Als zweites mögliches Ziel von sc1 konnte die Histidinkinase SCO5239 identifiziert werden. Hier wurde gezeigt, dass Koexpression von sc1 die Expression einer SCO5239 Reportergenfusion um den Faktor acht steigert. Durch Analyse des Proteoms von sc1 Mutanten, konnte die differenzierte Expression von elf weiteren Proteinen gezeigt werden. Sc1 scheint als Regulator zu agieren, indem es auf die Stickstoffversorgung der Zelle reagiert und den Sekundärmetabolismus deaktiviert.
Atmospheric observation-based global SF6 emissions - comparison of top-down and bottom-up estimates
(2009)
Emissions of sulphur hexafluoride (SF6), one of the strongest greenhouse gases on a per molecule basis, are targeted to be collectively reduced under the Kyoto Protocol. Because of its long atmospheric lifetime (≈3000 years), the accumulation of SF6 in the atmosphere is a direct measure of its global emissions. Examination of our extended data set of globally distributed high-precision SF6 observations shows an increase in SF6 abundance from near zero in the 1970s to a global mean of 6.7 ppt by the end of 2008. In-depth evaluation of our long-term data records shows that the global source of SF6 decreased after 1995, most likely due to SF6 emission reductions in industrialised countries, but increased again after 1998. By subtracting those emissions reported by Annex I countries to the United Nations Framework Convention of Climatic Change (UNFCCC) from our observation-inferred SF6 source leaves a surprisingly large gap of more than 70–80% of non-reported SF6 emissions in the last decade.