Assessing the gain of biological data integration in gene networks inference

Background: A current challenge in gene annotation is to define the gene function in the context of the network of relationships instead of using single genes. The inference of gene networks (GNs) has emerged as an approach to better understand the biology of the system and to study how several components of this network interact with each other and keep their functions stable. However, in general there is no sufficient data to accurately recover the GNs from their expression levels leading to the curse of dimensionality, in which the number of variables is higher than samples. One way to mitigate this problem is to integrate biological data instead of using only the expression profiles in the inference process. Nowadays, the use of several biological information in inference methods had a significant increase in order to better recover the connections between genes and reduce the false positives. What makes this strategy so interesting is the possibility of confirming the known connections through the included biological data, and the possibility of discovering new relationships between genes when observed the expression data. Although several works in data integration have increased the performance of the network inference methods, the real contribution of adding each type of biological information in the obtained improvement is not clear. Methods: We propose a methodology to include biological information into an inference algorithm in order to assess its prediction gain by using biological information and expression profile together. We also evaluated and compared the gain of adding four types of biological information: (a) protein-protein interaction, (b) Rosetta stone fusion proteins, (c) KEGG and (d) KEGG+GO. Results and conclusions: This work presents a first comparison of the gain in the use of prior biological information in the inference of GNs by considering the eukaryote (P. falciparum) organism. Our results indicates that information based on direct interaction can produce a higher improvement in the gain than data about a less specific relationship as GO or KEGG. Also, as expected, the results show that the use of biological information is a very important approach for the improvement of the inference. We also compared the gain in the inference of the global network and only the hubs. The results indicates that the use of biological information can improve the identification of the most connected proteins.

Konfliktlinien und die Einstellungen zur Europäischen Integration in Norwegen : eine quantitativ-empirische Analyse basierend auf dem European Social Survey 2004/2005

In den konsultativen Referenden von 1972 und 1994 stimmte eine knappe Mehrheit der norwegischen Wählerschaft gegen einen Beitritt in die europäische Staatengemeinschaft. Regierung und Parlament zogen daraufhin ihr Aufnahmegesuch zurück. Ein erneuter Antrag auf Mitgliedschaft in der EU wird seither vermieden, da sich die Parteien des Konfliktpotenzials bewusst sind. Von der politischen Agenda ist diese Streitfrage jedoch nicht verschwunden. Die vorliegende Magisterarbeit greift den gängigen Erklärungsansatz der politikwissenschaftlichen Forschung auf: Das Scheitern der Referenden ist demnach auf die Aktualisierung traditioneller politischer Konfliktlinien zurückzuführen. Inwieweit diese Cleavages die Einstellungen norwegischer Staatsbürger zur Europäischen Integration bestimmen, wird anhand eines komplexen Konfliktlinienmodells und mittels aktueller Daten untersucht. Aufbauend auf dem klassischen Cleavage-Konzept von Seymour Lipset und Stein Rokkan (Zentrum/Peripherie, Staat/Kirche, Stadt/Land, Kapital/Arbeit), findet eine Konkretisierung von Stefano Bartolini und Peter Mair Anwendung, die jede der vier Konfliktlinien als dreidimensional (empirisch, normativ und organisatorisch) begreift. In einem historischen Überblick zeigt sich die Relevanz der tradierten Konfliktlinien für Norwegen, die sich sowohl im nationalen Parteiensystem als auch in den Standpunkten der Parteien zu einem EU-Beitritt widerspiegeln. Datengrundlage für die folgenden empirischen Analysen (Kreuztabellen, Mittelwert- und Korrelationsvergleiche, multiple lineare Regressionen) stellt die norwegische Teilstudie der zweiten Welle des European Social Survey von 2004/2005 dar. Europäische Integration wird von den meisten norwegischen Staatsbürgern, die sich empirisch, normativ und organisatorisch auf den Konfliktlinienpolen Peripherie, Kirche, Land oder Arbeit verorten lassen, negativ bewertet. Im Gegensatz dazu geht die recht häufig vertretene Kombination der empirischen Konfliktlinienpole Zentrum-Staat-Stadt-Kapital mit einer überdurchschnittlich positiven Einstellung einher. Insgesamt erweist sich der Zusammenhang mit der Zentrum/Peripherie-Konfliktlinie als am höchsten.

Multimodal Integration in Statistical Learning: Evidence from the McGurk Illusion

Recent advances in the field of statistical learning have established that learners are able to track regularities of multimodal stimuli, yet it is unknown whether the statistical computations are performed on integrated representations or on separate, unimodal representations. In the present study, we investigated the ability of adults to integrate audio and visual input during statistical learning. We presented learners with a speech stream synchronized with a video of a speaker's face. In the critical condition, the visual (e.g., /gi/) and auditory (e.g., /mi/) signals were occasionally incongruent, which we predicted would produce the McGurk illusion, resulting in the perception of an audiovisual syllable (e.g., /ni/). In this way, we used the McGurk illusion to manipulate the underlying statistical structure of the speech streams, such that perception of these illusory syllables facilitated participants' ability to segment the speech stream. Our results therefore demonstrate that participants can integrate audio and visual input to perceive the McGurk illusion during statistical learning. We interpret our findings as support for modality-interactive accounts of statistical learning.

THE IMPACTS OF MITEP ON MY CAREER IN EDUCATION

MiTEP, the Michigan Teacher Excellence Program, provides current teachers the opportunity to partner with Michigan Technological University to obtain graduate credit towards a Master’s degree in applied science education. In exchange, the university collects data on the implementation of inquiry and earth science concepts into science classrooms. This paper documents my experience within this program, including how it has affected my personal and professional learning.