Refine
Document Type
- Master's Thesis (78)
- Bachelor Thesis (41)
- Diploma Thesis (1)
Year of publication
Language
- English (120) (remove)
Keywords
- Maschinelles Lernen (23)
- Blockchain (9)
- Vektorquantisierung (9)
- Algorithmus (7)
- Bioinformatik (5)
- Deep learning (5)
- Graphentheorie (5)
- Neuronales Netz (5)
- Kryptologie (4)
- Softwareentwicklung (4)
Institute
- Angewandte Computer‐ und Biowissenschaften (120) (remove)
Cancer is one of the main causes of death in developed countries, and cancer treatment heavily depends on successful early detection and diagnosis. Tumor biomarkers are helpful for early diagnose. The goal of this discovery method is to identify genetic variations as well as changes in gene expression or activity that can be linked to a typical cancer state.
First, several cancer gene signaling pathways were introduced and then combined. 27 candidate genes were selected, through the analysis of several data sets in the GEO database, a few expression difference matrices were established. Those candidate genes were tested in the matrices and found five genes PLA1A, MMP14, CCND1, BIRC5 and MYC that have the potential to be tumor biomarkers. Two of these genes have been further discussed, PLA1A is a potential biomarker for prostate cancer, and MMP14 can be considered as a biomarker for NSC lung cancer.
Finally, the significance of this study and the potential value of the two genes are discussed, and the future research in this direction is a prospect.
The loss of photoreceptors is a major course for visual impairment and blindness with no cure currently established. Photoreceptor replacement into mouse models of retinal degeneration is currently investigated as a potential future therapy. To evaluate visual function in mice before and after treatment two vision-based behavioral tests (optomotor tracking and the light/dark box) were investigated including their feasibility to distinguish between rod and cone photoreceptor function. Both methods turned out to be an objective and reliable readout for vision ability in wildtype mice and mice with vision impairment due to retinal degeneration. The capability of the methods to assess slight vision improvements have to be further evaluated.
Therefore options for improvement of the established tests and an idea for a new test paradigm have been introduced.
Genetic sex determination of ancient DNA samples based on one simple mathematical algorithm, which considers the number of mapped reads on autosomal, X, and Y chromosomes. The algorithm is implemented in one command line tool - SiD. SiD is used to deter-mine the sex of 16 samples, which have been shotgun sequenced and captured with a 1240k panel.
Large bone defects are a major clinical problem affecting elderly disproportionally, particularly indeveloped countries where this population is the fastest growing. Current treatments include autologous and allogenous bone grafts, bone elongation with the Ilizarov technique, bone graft substitutes, and electrical stimulation. Each of these approaches enjoys varying degrees of success, however, each also has its associated problems and complications. A new, still experimental, treatment is Tissue Engineering that combines scaffolds, osteogenic stem cells and growth factors, and is showing encouraging early results in preclinical and initial clinical studies.
Electrical stimulation has been shown to enhance bone healing by promoting mesenchymal stem cell migration, proliferation, and differentiation. In the present study we combine Tissue Engineering with Electrical Stimulation and hypothesize that this combined approach will have a synergistic effect resulting in enhanced new bone formation. In our in vitro experiments we observed that the levels of electrical stimulation we tested had no cytotoxic effect, instead increased osteogenic differentiation, as determined by enhanced expression of the osteogenic marker, Alkaline Phosphatase. These findings support our hypothesis by demonstrating that in the tissue-engineering environment electrical stimulation promotes bone formation. The bioinformatics part of this project consisted of gene network analysis, identification of the top 10 osteogenic markers and analyzis of genegene interactions. We observed that in studies of stem cells from both human and rat the genes, BMPR1A, BMP5, TGFßR1, SMAD4, SMAD2, BMP4, BMP7, RUNX3, and CDKN1A, are associated with osteogenesis and interact with each other. We observed a total of 31 interactions for human and 29 interactions for rat stem cells. While this approach needs to be proven experimentally, we believed that these in vitro and in silico analyses could compliment each other and in doing so contribute to the field of bone healing research.
Classification of time series has received an important amount of interest over the past years due to many real-life applications, such as environmental modeling, speech recognition, and computer vision.
In my thesis, I focus on classification of time series by LVQ classifiers. To learn a classifiers, we need a training set. In our case, every data point in the training set contains a sequence (an ordered set) of feature vectors. Thus, the first task is to construct a new feature vector (or matrix) for each sequence.
Inspired by [2], I use Hankel matrices to construct the new feature vectors. This choice comes from a basic assumption that each time series is generated by a single or a set of unknown Linear Time Invariant (LTI) systems.
After generating new feature vectors by Hankel matrices, I use two approaches to learn a classifier: Generalized Learning Vector Quntization (GLVQ) and Median variant of Generalized Learning Vector Quantization (mGLVQ).
Stability of control systems is one of the central subjects in control theory. The classical asymptotic stability theorem states that the norm of the residual between the state trajectory and the equilibrium is zero in limit. Unfortunately, it does not in general allow computing a concrete rate of convergence particularly due to algorithmic uncertainty which is related to numerical imperfections of floating-point arithmetic. This work proposes to revisit the asymptotic stability theory with the aim of computation of convergence rates using constructive analysis which is a mathematical tool that realizes equivalence between certain theorems and computation algorithms. Consequently, it also offers a framework which allows controlling numerical imperfections in a coherent and formal way. The overall goal of the current study also matches with the trend of introducing formal verification tools into the control theory. Besides existing approaches, constructive analysis, suggested within this work, can also be considered for formal verification of control systems. A computational example is provided that demonstrates extraction of a convergence certificate for example dynamical systems.
It is possible to obtain a common updating rule for k-means and Neural Gas algorithms by using a generalized Expectation Maximization method. This result is used to derive two variants of these methods. The use of a similarity measure, specifically the gaussian function, provides another clustering alternative to the before mentioned methods. The main benefit of using the gaussian function is that it inherently looks for a common cluster center for similar data points (depending on the value of the parameter s ). In different experiments we report similar behaviour of batch and proposed variants. Also we show some useful results for the “alternative” similarity method, specifically when there is no clue about the number of clusters in the data sets.
The endogen steroid hormone 17b-estradiol is a central player in a wide range of physiologic, behavioral processes and diseases in vertebrates. As a consequence, it is a main target for molecular design and drug discovery efforts in medicine and environmental sciences, which requires in-depth knowledge of protein-ligand binding processes. This work develops a bioinformatic framework based on local and global structure similarity for the characterization of E2-protein interactions in all 35 publicly available three-dimensional structures of estradiol-protein complexes. Subsequently, it uses gained data to identify four geometrically conserved estradiol binding residue motifs, against which the Protein Data Bank is queried. As result of this database query, 15 hits present in seven protein structures are found. Five of these structures do not contain E2 as ligand and had thus not been included in this work’s initial data set. One of these newly detected structures is structurally and functionally dissimilar, as well as evolutionarily distant from all other proteins analyzed in this work. Nevertheless, the ability of this protein to actually bind estradiol must be further analyzed. Finally, geometrically conserved E2-protein interactions are identified and a new research direction using these conserved interaction ensembles for the detection of novel estradiol targets is proposed.
Brassica oleracea like all crucifers plants have a defense mechanism against natural enemies, which are chemical compounds formed form the enzymatic degradation of glucosinolates. In the presence of epithiospecifier proteins (ESP), the hydrolysis of glucosinolates will form epithionitriles or nitriles depending on the glucosinolate structure, This research proved that three predicted sequences (ESP) taken from NCBI database has a role in the enzymatic hydrolysis of glucosinolates in Brassica oleracea.
The following is a description and outline of the work done at the Cornell Lab of Ornithology developing Nation Feathers VR, a virtual reality game for learning about bird calls and songs. The goal was to develop a game which is intuitive, educational and entertaining. Furthermore, the software needed to be structured in a way that allows for feasible future expansion. This required careful data saving and retrieval. The game gives the player an opportunity to learn and apply that knowledge, all while maintaining a shorter runtime in order to reduce the total time spent in the virtual world. This is meant to prevent any discomfort to the player that may result from extended use of the VR headset.