Institut für Informatik und Computational Science
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KEYCIT 2014
(2015)
In our rapidly changing world it is increasingly important not only to be an expert in a chosen field of study but also to be able to respond to developments, master new approaches to solving problems, and fulfil changing requirements in the modern world and in the job market. In response to these needs key competencies in understanding, developing and using new digital technologies are being brought into focus in school and university programmes. The IFIP TC3 conference "KEYCIT – Key Competences in Informatics and ICT (KEYCIT 2014)" was held at the University of Potsdam in Germany from July 1st to 4th, 2014 and addressed the combination of key competencies, Informatics and ICT in detail. The conference was organized into strands focusing on secondary education, university education and teacher education (organized by IFIP WGs 3.1 and 3.3) and provided a forum to present and to discuss research, case studies, positions, and national perspectives in this field.
Refined elasticity sampling for Monte Carlo-based identification of stabilizing network patterns
(2015)
Motivation: Structural kinetic modelling (SKM) is a framework to analyse whether a metabolic steady state remains stable under perturbation, without requiring detailed knowledge about individual rate equations. It provides a representation of the system's Jacobian matrix that depends solely on the network structure, steady state measurements, and the elasticities at the steady state. For a measured steady state, stability criteria can be derived by generating a large number of SKMs with randomly sampled elasticities and evaluating the resulting Jacobian matrices. The elasticity space can be analysed statistically in order to detect network positions that contribute significantly to the perturbation response. Here, we extend this approach by examining the kinetic feasibility of the elasticity combinations created during Monte Carlo sampling.
Results: Using a set of small example systems, we show that the majority of sampled SKMs would yield negative kinetic parameters if they were translated back into kinetic models. To overcome this problem, a simple criterion is formulated that mitigates such infeasible models. After evaluating the small example pathways, the methodology was used to study two steady states of the neuronal TCA cycle and the intrinsic mechanisms responsible for their stability or instability. The findings of the statistical elasticity analysis confirm that several elasticities are jointly coordinated to control stability and that the main source for potential instabilities are mutations in the enzyme alpha-ketoglutarate dehydrogenase.
Pervasive educational games have the potential to transfer learning content to real-life experiences beyond lecture rooms, through realizing field trips in an augmented or virtual manner. This article introduces the pervasive educational game "RouteMe" that brings the rather abstract topic of routing in ad hoc networks to real-world environments. The game is designed for university-level courses and supports these courses in a motivating manner to deepen the learning experience. Students slip into the role of either routing nodes or applications with routing demands. On three consecutive levels of difficulty, they get introduced with the game concept, learn the basic routing mechanisms and become aware of the general limitations and functionality of routing nodes. This paper presents the pedagogical and technical game concept as well as findings from an evaluation in a university setting.
Boolean networks provide a simple yet powerful qualitative modeling approach in systems biology. However, manual identification of logic rules underlying the system being studied is in most cases out of reach. Therefore, automated inference of Boolean logical networks from experimental data is a fundamental question in this field. This paper addresses the problem consisting of learning from a prior knowledge network describing causal interactions and phosphorylation activities at a pseudo-steady state, Boolean logic models of immediate-early response in signaling transduction networks. The underlying optimization problem has been so far addressed through mathematical programming approaches and the use of dedicated genetic algorithms. In a recent work we have shown severe limitations of stochastic approaches in this domain and proposed to use Answer Set Programming (ASP), considering a simpler problem setting. Herein, we extend our previous work in order to consider more realistic biological conditions including numerical datasets, the presence of feedback-loops in the prior knowledge network and the necessity of multi-objective optimization. In order to cope with such extensions, we propose several discretization schemes and elaborate upon our previous ASP encoding. Towards real-world biological data, we evaluate the performance of our approach over in silico numerical datasets based on a real and large-scale prior knowledge network. The correctness of our encoding and discretization schemes are dealt with in Appendices A-B. (C) 2014 Elsevier B.V. All rights reserved.
Die Tagung HDI 2014 in Freiburg zur Hochschuldidaktik der Informatik HDI wurde erneut vom Fachbereich Informatik und Ausbildung / Didaktik der Informatik (IAD) in der Gesellschaft für Informatik e. V. (GI) organisiert. Sie dient den Lehrenden der Informatik in Studiengängen an Hochschulen als Forum der Information und des Austauschs über neue didaktische Ansätze und bildungspolitische Themen im Bereich der Hochschulausbildung aus der fachlichen Perspektive der Informatik.
Die HDI 2014 ist nun bereits die sechste Ausgabe der HDI. Für sie wurde das spezielle Motto „Gestalten und Meistern von Übergängen“ gewählt. Damit soll ein besonderes Augenmerk auf die Übergänge von Schule zum Studium, vom Bachelor zum Master, vom Studium zur Promotion oder vom Studium zur Arbeitswelt gelegt werden.