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The almost complete transcription of the human genome yield in a high number of transcripts, that do not encode proteins. However, the functional elucidation of especially long non cod-ing RNAs is still difficult. Secondary structure analysis is assumed to be a possible method to detect functional relationships of lncRNAs on a large scale, but it is still time consuming and error-prone. GRAPHCLUST, the currently most suitable clustering tool based on RNA secondary structure analysis, lacks mainly in an efficient method for the interpretation of its results. Hence, an independent and interactive RNA clustering interpretation tool was developed to allow visu-alisation and an efficient analysis of RNA clustering results.
In this work a novelty detection framework provided by M. Filippone and G. Sanguinetti is considered, which is useful especially when only few training samples are available. It is restricted to Gaussian mixture models and makes use of information theory, applying the Kullback-Leibler divergence. In this work two variations of the framework are presented, applying the symmetric Hellinger divergence and a statistical likelihood approach.
For the first time it was discovered that ultraviolet radiation with a wavelength of 200 to 400 nm (maximum 365 nm) radiated from a distance of 40 cm (intensity: 3500 mW/cm²) to PMMA altered its surface wettability as well as a roughness at the nanoscale that was observed with an atomic force microscope (AFM). The roughness rises and falls again in a short time ( 1-2days ) after 75 min and 180 min irradiation time. However , during the next 10 days roughness became stabilized and there was no influence of UV if PMMA was stored in air or in a Petri dish out of glass.
When entering waterways that are restricted either in height, width or by another vessel, the behaviour of a ship changes. The most evident effect of navigating in shallow water is the squat which has led to several groundings. Because of pressure differences the vessel is pulled down into the water and the trim is changed. Another shallow water effect is the speed loss due to an increase in resistance which can reduce the maximal speed by upto 50 percent. In general the behaviour of a ship in shallow water is said to be sluggish, meaning that it is more difficult to navigate which affects the radius of the turning circle among others. Sailing parallel to a close-by bank affects the lateral force and the yaw moment. The interaction with other ships has similar effects as bank effects, but is more sophisticated since more parameters play a major role. In this thesis each of these effects is researched by studying several papers by renowned researchers.
Several models are developed which are correspondent with the inherent model of forces and moments of the simulation program. The challenges and obstacles that arised during modelling and implementation are pointed out and solutions or approaches are given.
This master thesis investigates a new method for the feature extraction of gray scale images, the so called „Non-Euclidean Principal Component Analysis“ 1. Thereby the standard inner product of the Euclidean space is substituted by a semi inner product in the well known learning rule of Oja and Sanger. The new method is compared with the standard principal component analysis (PCA) by extracting features (feature vectors) of different databases with class labels and judged regarding the accuracies of „Border Sensitive Generalized Learning Vector Quantization“ (BSGLVQ), „Feed Forward Neural Networks“ (FFNN) and the „Support Vector Machines“ (SVM).
This thesis investigated the generation of laser induced periodic surface structures (LIPSS) using femtosecond laser irradiation at a central wavelength of 775 nm.
The metals stainless steel and copper as well as a semiconducting thin film, ITO on glass substrate were investigated. The impact of the processing parameters was studied for single and multiple pulse irradiation to determine the ablation threshold of the materials
and the different types of LIPSS. These observations allowed the optimisation of area structuring with regards to processing speed and LIPSS quality.
The feasibility of the LIPSS generation in dynamic, real time polarisation control was then explored. By using a fast response, liquid-crystal polarisation rotation device, the direction of the linear polarisation of the laser beam could be dynamically controlled and synchronised to the scanning during laser processing. As a result, a range of complex micro- and nano-scale patterns with orthogonal direction of LIPSS were created. The samples were analysed using optical and electron microscopy. The orientation of the LIPSS was determined also from detection of light diffracted by the LIPSS.
Finally, two applications of large area LIPSS patterning were demonstrated, information encoding on metals and periodic structuring of a thin film conducting oxide for solar cells.
Protein structures are essential elements in every biological system evolved on earth, where they function as stabilizing elements, signaltransducers or replication machin eries. They are consisting of linear-bonded amino acids, which determine the three-dimensional structure of the protein, whereas the structure in turn determines the function. The native and biological active structure ofa protein can be understood as the folding state of a polypeptide chain at the global minimum of free energy.
By means of protein energy profiling, which is an approach derived from statistical physics it is possible to assign a so called energy profile to a protein structure. Such an energy profile describes the local energetic interaction features of every amino acid within the structure and introduces an energetic point of view, instead of a structural or sequential onto proteins.
This work aims to give a perspective to the question of how we may gain pattern information out of energy profiles. The concrete subjects are energy-mapped Pfam family alignments and investigations on finding motifs or patterns indiscretizised energy profile segments.
A variety of methods have been used to describe natural systems and cellular functions. Most use continuous systems with differential equations. Based upon the neighbourhood relations in graphs and the complex interactions in cellular automata a mathematical model was designed and implemented as an application user interface. This discrete approach called graph automata was utilised to simulate diffusion processes and chemical kinetics. The progression of diffusion in cellular environments was described and resulted in a discrepancy of 20% in comparison to experimental results. Different chemical kinetics were simulated and found to be as accurate as their continuous counterparts. The proposed model appears to be a highly scalable and modular
approach to simulate natural systems.
As widely discussed in literature spatial patterns of amino acids, so-called structural motifs, play an important role in protein function. The functional responsible part of a protein often lies in an evolutionary highly conserved spatial arrangement of only few amino acids, which are held in place tightly by the rest of the structure. In general, these motifs can mediate various functional interactions, such as DNA/RNA targeting and binding, ligand interactions, substrate catalysis, and stabilization of the protein structure.
Hence, characterizing and identifying such conserved structural motifs can contribute to understanding of structurefunction relationships in diverse protein families. Therefore and because of the rapidly increasing number of solved protein structures, it is highly desirable to identify, understand and moreover to search for structural scattered amino acid motifs. The aim of this work was the development and the implementation of a matching algorithm to search for such small structural motifs in large sets of target structures. Furthermore, motif matches were extensively analyzed, statistically assessed and functionally classified. Following a novel approach, hierarchical clustering was combined with functional classification and used to deduce evolutionary structure-function relationships. The proposed methods were combined and implemented to a feature-rich and easy-to-use command line software tool, which is freely available and contributes to the field of structural bioinformatic research.