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A number of real time PCR approaches have been published in the literature. In this thesis, the suitability of different real time PCR approaches using hydrolysis probes have been evaluated regarding PCR performance, cost effectiveness as well as handling. The effect of double-quenched probes as well as the impact of the increase of relative Flap endonuclease amount in quantitative real time PCR has been examined. In terms of genotyping a TaqMan™ assay, considered to be the gold-standard in this application, has been tested and compared to phosphorothioate modified probes, allele specific primers, SNAKE primers, an allele specific probe and primer assays as well as an assay using minor groove binder probes. Promising observations have been made in the case of double-quenched probes, phosphorothioate modified probes, SNAKE primers as well as minor groove binder probes.
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.
The cultivation of mammalian cells in the third dimension has a great potential for a
wide application in regenerative medicine, pharmaceutical industry or cancer research.
An overview about actual 3-D cultivation techniques like hydrogels and porous scaffolds as well as their various materials and modifications is given in this thesis. Also different products and their implementation for a new application of 3-D cell
culture in a laboratory are described.
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.
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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.
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).
The main purpose of this Bachelor thesis was to find and to compile comprehensive information on barley genes expressed in the context of pollen embryogen esis. In the present study, this approach was confined to genes that were previously known to be associated with the initiation of embryogenesis in different plant species. First, candidate transcript sequences were identified in barley. Second, transcript and associated genomic sequences were analyzed in silico to provide suitable structural and functional annotations. Finally, the results of one representative example are presented and interpreted in detail. This work aims to contribute to a significantly improved understanding of pollen embryogenesis - a biological phenomenon broadly used for haploid technology in crop improvement.
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.
The study “Proteomic and systems biological database analysis of changed proteins from rat brain tissue after diving “ is about system biological testing of proteomic data obtained by rat brain after experimental diving in a pressure chamber. Basically, brain tissue from animal decompression sickness (DCS) was analyzed by mass spectrometry and has given two larger sets of modified proteins. Thereupon, the resulting up- and down-regulated proteins wereidentified and later compared by means of systems of biological databases, in this case GeneGo MetaCoreTM, in order to find similar or various affected cell biological signaling pathways when two different mass-spectrometry methods were compared.
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.
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This Bachelor thesis provides an experimental validation of the “si-Fi” software, which was designed for RNAi off-target searches and silencing efficiency predictions. The experimental approach is based on using synthetic DNA as RNAi-target as well as RNAi-trigger sequence. The data was generated by two different types of experiments using a transient gene silencing system in bombarded barley epidermal cells. The efficiency of RNAi was estimated by scoring the effect of silencing of the susceptibility-related gene Mlo on resistance of transformed cells to the powdery mildew fungus Blumeria graminis f. sp. hordei by observing reduction of fluorescent signals coming from an RNAi target fused to the green fluorescent protein. The aim of this work was a comparison between in silicio prediction of RNAi efficiency and off-target effects in barley and experimental data.
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.
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.
Proteins are involved in almost every aspect of life, mediating a wide range of cellular tasks. The protein sequence dictates the spatial arrangement of the residues and thus ultimately the function of a rotein. Huge effort is put into cumbersome structure eludication experiments which obtain models describing the observed spatial conformation of a protein, enabling users to predict their function, to understand their mode of action or to design tailored drugs to cure disease caused by misfolded or misregulated proteins.
However, the result of structure determination experiments are merely models of reality, made under simplifying assumptions - sometimes containing major undetected errors. On the other hand, such experiments are resource demanding and they cannot supply the actual demand.
Thus, scientists are predicting the structure of proteins in silico, resulting in models that are even
more prone to error.
In consequence, the structure biologists search after a practicable definition of structure quality and over the last two decades several model quality assessment programs emerged, measuring the local and global quality of peculiar structures. Seven representatives were studied, regarding the paradigms they follow and the features they use to describe the quality of residues. Their predications were compared, showing that there is almost no common ground among the tools.
Is there a way to combine their statements anyway?
Finally, the accumulated knowledge was used to design a novel evaluation tool, addressing problems previously spotted. Thereby, high quality of its predication as well as superior usability was
key. The strategy was compared to existing approaches and evaluated on suitable datasets.
The larval zebrafish mutant Knörf has got a not yet identified gen, which is lethal after 14 dpf in a homozygous state. The mutation courses various degenerations and the loss of the regeneration ability. One of these degenerations was first discovered in the retina by a histological section. The mutants retinas show gaps in the IPL at 7 and 8 dpf which number increases during the maturation of the larva. In recent studies a pax 6 staining was performed, which showed that amacrine cells areaffected. Different types of amacrine cells were tested and it was shown that the parvalbuminergic amacrine cells disappear. The staining was performed in a time course. At 5 dpf is no difference between the number of parvalbuminergic amacrine cells in siblings and mutants but then the degeneration starts. At 2 dpa there is thefirst significant difference which increases at later stages and leads nearly to a full disappearance of these cells in the eye. Parvalbumin is not only present in the retina, therefore the brain as another central nervous system structure was examined. In the telencephalon these cells disappear already at 2 dpa. The parvalbuminergic cells are also present in the skeletal muscle of the tail. Here the degeneration starts approximately at the half of the tail and intensifies to distal areas. It was shown, that parvalbuminergic cells in the muscle disappear until 4dpa. The role of parvalbumin is seemed in the binding ofcalcium and therefore it supports the adjustment of the resting potential after an excitation in the central nervous system. In muscles it assists in the slowing of relaxing after a contraction of a muscle.
Proteins are macromolecules that consist of linear-bonded amino acids. They are essential elements in various metabolic processes. The three-dimensional structure of a protein is determined by the order of amino acids, also referred to as the protein sequence. This conformation corresponds to the structural state in which the protein is functionally active. However, relationships between protein sequence, structure and function have not been fully understood yet. Additionally, information about structural properties or even the entire protein structure are crucial for understanding the dynamics that define protein functionality and mechanisms. From this, the role of a protein in its molecular context can be described closely. For instance, interactions can be investigated and comprehended as a biological dynamic network that is sensitive to alternations, i.e. changes which are caused by diseases. Such knowledge can aid in drug design, whereas compounds need to be specifically tailored and adjusted to their molecular targets. Protein energy profile-basedmethods can be applied to investigate protein structures concerning dynamics and alternations. The publications enclosed to this work discuss in general the scientific potentials of energy profilebased techniques and algorithms. On the one hand, changes in stability caused by protein mutations and proteinligand interactions are discussed in the context of energy profiles. On the other hand, energetic relations to protein sequence, structure and function are elucidated in detail. Finally, the presented discussions focus on recent enhancements of the eProS (energy profile suite) database and toolbox. eProS freely provides all elucidated methodologies to the scientific community. Thus, one can address biological questions with the presented methods at hand. Additionally, eProS provides annotations related to foreign databases. This ensures a broad view on biological data and information. In particular, energetic characteristics can be identified which contribute to a protein’s structure and function.