Establishment of predictive blood-based signatures in medical large scale genomic data sets : Development of novel diagnostic tests

Increasing data has led to tremendous success in discovering molecular biomarkers based on high throughput data. However, the translation of these so-called genomic signatures into clinical practice has been limited. The complexity and volume of genomic profiling requires heightened attention to robust design, methodological details, and avoidance of bias. During this thesis, novel strategies aimed at closing the gap from initially promising pilot studies to the clinical application of novel biomarkers are evaluated. First, a conventional process for genomic biomarker development comprising feature selection, algorithm and parameter optimization, and performance assessment was established. Using this approach, a RNA-stabilized whole blood diagnostic classifier for non-small cell lung cancer was built in a training set that can be used as a biomarker to discriminate between patients and control samples. Subsequently, this optimized classifier was successfully applied to two independent and blinded validation sets. Extensive permutation analysis using random feature lists supports the specificity of the established transcriptional classifier. Next, it was demonstrated that a combined approach of clinical trial simulation and adaptive learning strategies can be used to speed up biomarker development. As a model, genome-wide expression data derived from over 4,700 individuals in 37 studies addressing four clinical endpoints were used to assess over 1,800,000 classifiers. In addition to current approaches determining optimal classifiers within a defined study setting, randomized clinical trial simulation unequivocally uncovered the overall variance in the prediction performance of potential disease classifiers to predict the outcome of a large biomarker validation study from a pilot trial. Furthermore, most informative features were identified by feature ranking according to an individual classification performance score. Applying an adaptive learning strategy based on data extrapolation led to a datadriven prediction of the study size required for larger validation studies based on small pilot trials and an estimate of the expected statistical performance during validation. With these significant improvements, exceedingly robust and clinically applicable gene signatures for the diagnosis and detection of acute myeloid leukemia, active tuberculosis, HIV infection, and non-small cell lung cancer are established which could demonstrate disease-related enrichment of the obtained signatures and phenotype-related feature ranking. In further research, platform requirements for blood-based biomarker development were exemplarily examined for micro RNA expression profiling. The performance as well as the technical sample handling to provide reliable strategies for platform implementation in clinical applications were investigated. Overall, all introduced methods improve and accelerate the development of biomarker signatures for molecular diagnostics and can easily be extended to other high throughput data and other disease settings

Roving Librarians in der Zentralbibliothek der Hochschule Hannover: ein Experiment

In der Zentralbibliothek der Hochschule Hannover wurde ab Wintersemester 2012 ein Experiment mit Roving Librarians durchgeführt, um die Auskunftsqualität zu verbessern. Die Mitarbeiterinnen und Mitarbeiter der Bibliothek liefen zu diesem Zweck mit einem Netbook ausgerüstet durch den Benutzungsbereich der Bibliothek, um Fragen der Nutzer und Nutzerinnen gleich dort aufzufangen, wo sie entstehen. Der Versuch kann nicht als erfolgreich bezeichnet werden, doch konnten während des Experiments wertvolle Einblicke in Nutzerwünsche gewonnen werden

Agenten und Komplizen : Strategische Partnerschaften zwischen Schule und Stadt in Neukölln

Zugleich gedruckt erschienen im Universitätsverlag der Technischen Universität Berlin, 2012. - ISBN 978-3-7983-2476-3Viele Schulen entwickeln sich von reinen Lernorten für Schüler zu Lebensorten für die gesamte Nachbarschaft der Schule. Können in diesem Prozess bestehende Bildungspotenziale im Quartier aufgespürt und mit der Schule verknüpft werden? Die Rixdorfer Grundschule in Nord-Neukölln soll zu einem Identifikationsort mit hoher Ausstrahlungskraft in die Nachbarschaft ausgebaut werden. Mit dem Planspiel AGENTEN & KOMPLIZEN haben Schülern, Lehrern und Nachbarn der Schule in 70 Spielrunden Zukunftsszenarien für strategische Verbindungen von Bildung und Quartier erspielt. Moderiert wurden die Spielrunden von Studierenden der Architektur, die basierend auf den Ergebnissen des Spiels eine bauliche Erweiterung der Schule entworfen haben.Many schools are currently evolving from their former role as places for learning into neighbourhood centres for educational as well as social activities. During this process, it is essential to trace and link existing local educational potential to the school. The Rixdorf Primary School in the north of Neukölln is to become a core institution with strong radiance and local identity. With the simulation game AGENTS & ACCOMLICES more than 70 future scenarios of strategic links between education and neighbourhood have been played out by pupils, teachers, neighbours and by-passers. The students of Architecture, who moderated the game rounds, designed structural extensions for the school based on the analysis of the game outcome