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Background: Computational tools for the investigation of transcriptional regulation, in particular of transcription factor binding sites (TFBS), in evolutionary context are developed. Existing sequence based tools prediction such binding sites do not consider their actual functionality, although it is known that besides the base sequence many other aspects are relevant for binding and for the effects of that binding. In particular in Eukaryotes a perfectly matching sequence motif is neither necessary nor sufficient for a functional transcription factor binding site. Published work in the field of transcriptional regulation frequently focus on the prediction of putative transcription factor binding sites based on sequence similarity to known binding sites. Furthermore, among the related software, only a small number implements visualization of the evolution of transcription factor binding sites or the integration of other regulation related data. The interface of many tools is made for computer scientists, although the actual interpretation of their outcome needs profound biological background knowledge. Results and Discussion: The tool presented in this thesis, "ReXSpecies" is a web application. Therefore, it is ready to use for the end user without installation providing a graphical user interface. Besides extensive automation of analyses of transcriptional regulation (the only necessary input are the genomic coordinates of a regulatory region), new techniques to visualize the evolution of transcription factor binding sites were developed. Furthermore, an interface to genome browsers was implemented to enable scientists to comprehensively analyze their regulatory regions with respect to other regulation relevant data. ReXSpecies contains a novel algorithm that searches for evolutionary conserved patterns of transcription factor binding sites, which could imply functionality. Such patterns were verified using some known transcription factor binding sites of genes involved in pluripotency. In the appendix, efficiency and correctness of the used algorithm are discussed. Furthermore, a novel algorithm to color phylogenetic trees intuitively is presented. In the thesis, new possibilities to render evolutionary conserved sets of transcription factor binding sites are developed. The thesis also discusses the evolutionary conservation of regulation and its context dependency. An important source of errors in the analysis of regulatory regions using comparative genetics is probably to find and to align homologous regulatory regions. Some alternatives to using sequence similarity alone are discussed. Outlook: Other possibilities to find (functional) homologous regulatory regions (besides whole-genome-alignments currently used) are BLAST searches, local alignments, homology databases and alignment-free approaches. Using one ore more of these alternatives could reduce the number of artifacts by reduction of the number of regions that are erroneously declared homologous. To achieve more robust predictions of transcription, the author suggests to use other regulation related data besides sequence data only. Therefore, the use and extension of existing tools, in particular of systems biology, is proposed.
Interactive Visualization for the Exploration of Aligned Biological Networks and Their Evolution
(2011)
Network Visualization is a widely used tool in biology. The biological networks, as protein-interaction-networks are important for many aspects in life. Today biologists use the comparison of networks of different species (network alignment) to understand the networks in more detail and to understand the underlying evolution. The goal of this work is to develop a visualization software that is able to visualize network alignments and also their evolution. The presented software is the first software for such visualization tasks. It uses 3D graphics and also animations for the dynamic visualization of evolution. This work consists of a review of the Related Work, a chapter about our Graph-based Approach for Interactive Visualization of Evolving Network Alignments, an explanation of the Graph Layout Algorithm and some hints for the Software System.
Self-similar sets are a class of fractals which can be rigorously defined and treated by mathematical methods. Their theory has been developed in n-dimensional space, but we have just a few good examples of self-similar sets in three-dimensional space. This thesis has two different aims. First, to extend fractal constructions from two-dimensional space to three-dimensional space. Second, to study some of the properties of these fractals such as finite type, disk-likeness, ball-likeness, and the Hausdorff dimension of boundaries. We will use the neighbor graph tool for creating new fractals, and studying their properties.