A mock examination is an exam that does not count for credit. It is taken before an official examination and gives students the opportunity to practice for the later, important exam. The mock examination provides students with information on their actual learning progress and gives them in this way the opportunity to fill knowledge gaps. An electronic mock examination is the online variant usually taken unsupervised in the students' own time. In this work we present the setup of an electronic mock exam in the course "Basics of Computer Science". We discuss question types other than multiple-choice that allow for fully automated marking. Furthermore, we present an in-depth analysis of the results of the mock exam. These results demonstrate that students consider the electronic mock exam as valuable help for exam preparation. Half of the students take the mock exam even more than once and use different strategies to make the most out of it. On the other hand, lecturers get invaluable feedback from the results of the mock exam. This feedback covers all learning objectives of the entire course, comes at the right time, and is ideally suited for planning the contents of a recapitulation lecture.

For us a lecturers, it is important to assess early on in a class whether we effectively reach our students and create the desired teaching outcome. Usually, the major assessment is some kind of exam which takes place at the end of term - and thus at a time when it is generally too late to change anything. Instead, lecturers need a toolset of different feedback and evaluation techniques that provide feedback as required, at different intervals throughout term, adequate for different teaching settings and group sizes, and with a reasonable amount of time and effort required from all parties involved. To help choose a suitable feedback technique for a specific teaching context, we introduce a classification scheme for feedback techniques. On this basis, we rate a variety of well-established feedback techniques, thus making it possible to select those feedback techniques that best suit one's individual needs.

To secure their access to water, light, and nutrients, many plant species have developed allelopathic strategies to suppress competitors. To this end, they release into the rhizosphere phytotoxic substances that inhibit the germination and growth of neighbors. Despite the importance of allelopathy in shaping natural plant communities and for agricultural production, the underlying molecular mechanisms are largely unknown. Here, we report that allelochemicals derived from the common class of cyclic hydroxamic acid root exudates directly affect the chromatin-modifying machinery in Arabidopsis thaliana. These allelochemicals inhibit histone deacetylases both in vitro and in vivo and exert their activity through locus-specific alterations of histone acetylation and associated gene expression. Our multilevel analysis collectively shows how plant-plant interactions interfere with a fundamental cellular process, histone acetylation, by targeting an evolutionarily highly conserved class of enzymes.

Just-in-Time Teaching (JiTT) is an activating teaching method that is highly popular in today's university education systems. In this paper, we use the experience we made using JiTT during two semesters to analyze the effectiveness of this teaching method.

Over the recent years, we experienced that a significant percentage of first-year students shows difficulties in acquiring even introductory software development knowledge, as well as in coping with the study process itself. In most cases, the core problem is not a lack of general intellectual capacity, but rather significant deficiencies in certain base competencies (i.e. self-, practical and cognitive as well as social competencies). We imply that these base competencies are crucial for successfully studying computer science or related topics. In order to identify these base competencies, we collected a superset of competencies from literature, structured this set, and performed filtering and clustering steps, resulting in almost 100 remaining base competencies that are relevant in our teaching context. As it is impossible for any lecturer to develop all these competencies in a single effort, we finally boiled this set down to a selection of those competencies that we deem to be most relevant for successfully studying software related topics at university level. Towards this end, for each competence, we defined what we the lecturers expect from our incoming freshmen students. In addition, we specified the skill level expected by the job market. Furthermore, we assessed the skill level of those 70% of our students that have obvious difficulties in coping with study requirements. Finally, we selected those competencies with a large difference between what is expected from our graduates and what we find in our incoming cohort. This analysis resulted in a selection of 27 competencies that we deem to be highly essential prerequisites for software engineering education, and which are not sufficiently well developed in the vast majority of freshmen students. For each of these base competencies we provide definitions and denote reasons for their selection.

In this paper we describe experiences using improvisational theater (improv) techniques in teaching acitivities. The educational setting where we aim to profit from these experiences are software engineering courses. The usefulness of improvisational theater in different contexts was discussed in the literature during the last few years. We conducted two sessions of improvisational theater with two objectives: (a) enhancing creativity and (b) enabling the process of team building. This paper describes our motivation, the goals, the educational setting and the different improv exercises performed. Results of our evaluation indicate that the majority of students enjoyed the improv sessions. Exercises focused on team building gained better results than those focusing on creativity. Our overall impression was that the success of using improv depends on careful planning and performance on the one hand and on the students' individual comfort zone on the other hand.

Fragestellung: Epigenetische Wirkstoffe stehen aktuell im Fokus neuer innovativer Therapiekonzepte in der klinischen Onkologie. Hierbei weisen insbesondere Histondeacetylase Inhibitoren (HDACi) ein potenziell breites Anwendungsspektrum bei gleichzeitig geringer Toxizität auf. Erste Hinweise deuten drauf hin, dass HDACi speziell bei Chemotherapie-resistenten Tumoren eingesetzt werden können; daher wird intensiv nach neuen Substanzen mit HDACi Aktivität gesucht.

BACKGROUND:Accurate prediction of peptide immunogenicity and characterization of relation between peptide sequences and peptide immunogenicity will be greatly helpful for vaccine designs and understanding of the immune system. In contrast to the prediction of antigen processing and presentation pathway, the prediction of subsequent T-cell reactivity is a much harder topic. Previous studies of identifying T-cell receptor (TCR) recognition positions were based on small-scale analyses using only a few peptides and concluded different recognition positions such as positions 4, 6 and 8 of peptides with length 9. Large-scale analyses are necessary to better characterize the effect of peptide sequence variations on T-cell reactivity and design predictors of a peptide's T-cell reactivity (and thus immunogenicity). The identification and characterization of important positions influencing T-cell reactivity will provide insights into the underlying mechanism of immunogenicity.RESULTS:This work establishes a large dataset by collecting immunogenicity data from three major immunology databases. In order to consider the effect of MHC restriction, peptides are classified by their associated MHC alleles. Subsequently, a computational method (named POPISK) using support vector machine with a weighted degree string kernel is proposed to predict T-cell reactivity and identify important recognition positions. POPISK yields a mean 10-fold cross-validation accuracy of 68% in predicting T-cell reactivity of HLA-A2-binding peptides. POPISK is capable of predicting immunogenicity with scores that can also correctly predict the change in T-cell reactivity related to point mutations in epitopes reported in previous studies using crystal structures. Thorough analyses of the prediction results identify the important positions 4, 6, 8 and 9, and yield insights into the molecular basis for TCR recognition. Finally, we relate this finding to physicochemical properties and structural features of the MHC-peptide-TCR interaction.CONCLUSIONS:A computational method POPISK is proposed to predict immunogenicity with scores which are useful for predicting immunogenicity changes made by single-residue modifications. The web server of POPISK is freely available at http://iclab.life.nctu.edu.tw/POPISK.

Fragestellung: Epigenetische Wirkstoffe sind in den letzten Jahren zunehmend in den Fokus innovativer Therapiekonzepte der Tumorforschung gerückt. Insbesondere Inhibitoren der zellulären Histondeacetylase (HDAC) zeigen ein breites Anwendungsspektrum bei gleichzeitig geringer Toxizität. Speziell Chemotherapie-resistente Tumore sprechen sensibel auf diese Wirkstoffklasse an; daher wird aktuell intensiv nach neuen Substanzen gesucht, die eine HDAC-inhibitorische Aktivität aufweisen.

The accurate modeling of metal coordination geometries plays an important role for structure-based drug design applied to metalloenzymes. For the development of a new metal interaction model, we perform a statistical analysis of metal interaction geometries that are relevant to protein-ligand complexes. A total of 43,061 metal sites of the Protein Data Bank (PDB), containing amongst others magnesium, calcium, zinc, iron, manganese, copper, cadmium, cobalt, and nickel, were evaluated according to their metal coordination geometry. Based on statistical analysis, we derived a model for the automatic calculation and definition of metal interaction geometries for the purpose of molecular docking analyses. It includes the identification of the metal-coordinating ligands, the calculation of the coordination geometry and the superposition of ideal polyhedra to identify the optimal positions for free coordination sites. The new interaction model was integrated in the docking software FlexX and evaluated on a data set of 103 metalloprotein-ligand complexes, which were extracted from the PDB. In a first step, the quality of the automatic calculation of the metal coordination geometry was analyzed. In 74% of the cases, the correct prediction of the coordination geometry could be determined on the basis of the protein structure alone. Secondly, the new metal interaction model was tested in terms of predicting protein-ligand complexes. In the majority of test cases, the new interaction model resulted in an improved docking accuracy of the top ranking placements.

Goitre operations were done in 2114 patients; 1648 patients had a simple solitary nodule or multinodular goitre with regressive changes. Malignancies were found in 54 cases with a clear-cut predominance of papillary carcinomas. Nearly half of the goitres diagnosed as solitary nodules preoperatively were shown to be multinodular. This discrepancy was taken into account in the determination of the rate of malignancy. Malignomas were found in 4.6% of "true" solitary nodules and in 2.8% in multinodular goitres. These findings confirm our liberal indications for operation in multinodular goitres with regressive changes also in the area of endemic goitre. The high incidence of microcarcinomas in our patients can thus be explained.

In this work we report on a novel scoring function that is based on the LUDI model and focuses on the prediction of binding affinities. AIScore extends the original FlexX scoring function using a chemically diverse set of hydrogen-bonded interactions derived from extensive quantum chemical ab initio calculations. Furthermore, we introduce an algorithmic extension for the treatment of multifurcated hydrogen bonds (XFurcate). Charged and resonance-assisted hydrogen bond energies and hydrophobic interactions as well as a scaling factor for implicit solvation were fitted to experimental data. To this end, we assembled a set of 101 protein-ligand complexes with known experimental binding affinities. Tightly bound water molecules in the active site were considered to be an integral part of the binding pocket. Compared to the original FlexX scoring function, AIScore significantly improves the prediction of the binding free energies of the complexes in their native crystal structures. In combination with XFurcate, AIScore yields a Pearson correlation coefficient of R P = 0.87 on the training set. In a validation run on the PDBbind test set we achieved an R P value of 0.46 for 799 attractively scored complexes, compared to a value of R P = 0.17 and 739 bound complexes obtained with the FlexX original scoring function. The redocking capability of AIScore, on the other hand, does not fully reach the good performance of the original FlexX scoring function. This finding suggests that AIScore should rather be used for postscoring in combination with the standard FlexX incremental ligand construction scheme.

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We report the computer-aided optimization of a synthetic receptor for a given guest molecule, based on inverse virtual screening of receptor libraries. As an example, a virtual set of beta-cyclodextrin (beta-CD) derivatives was generated as receptor candidates for the anticancer drug camptothecin. We applied the two docking tools AutoDock and GlamDock to generate camptothecin complexes of every candidate receptor. Scoring functions were used to rank all generated complexes. From the 10 % top-ranking candidates nine were selected for experimental validation. They were synthesized by reaction of heptakis-[6-deoxy-6-iodo]-beta-CD with a thiol compound to form the hepta-substituted beta-CDs. The stabilities of the camptothecin complexes obtained from solubility measurements of five of the nine CD derivatives were significantly higher than for any other CD derivative known from literature. The remaining four CD derivatives were insoluble in water. In addition, corresponding mono-substituted CD derivatives were synthesized that also showed improved binding constants. Among them the 9-H-purine derivative was the best, being comparable to the investigated hepta-substituted beta-CDs. Since the measured binding free energies correlated satisfactorily with the calculated scores, the applied scoring functions appeared to be appropriate for the selection of promising candidates for receptor synthesis.

We describe a similarity-based screening approach combined with a quantitative prediction of affinity based on physicochemical descriptors, for the efficient identification of new, high affinity guest molecules of beta-cyclodextrin (beta-CD). Four known beta-CD guest molecules were chosen as query molecules. A subset of the ZINC database with 117 695 molecular entries served as the screening library. For each query the 150 most similar molecules were identified by virtual screening against this library with a graph-based similarity algorithm. Subsequently these molecules were scored by means of a QSPR model. The best-scoring, commercially available molecules were selected for experimental verification ( 14 in total). Binding free energies were determined by isothermal microcalorimetry (ITC). For three of the four queries, at least one ligand with a higher binding affinity than the corresponding query was found. The approach is a promising high throughput alternative to structure-based virtual screening. While beta-CD was chosen as a test case because of its technical relevance and the availability of many binding data, the applied methodology is transferable to other host-guest systems.

We present a new algorithm for the fast and reliable structure prediction of synthetic receptor-ligand complexes. Our method is based on the protein-ligand docking program FlexX and extends our recently introduced docking technique for synthetic receptors, which has been implemented in the program FlexR. To handle the flexibility of the relevant molecules, we apply a novel docking strategy that uses an adaptive two-sided incremental construction algorithm which incorporates the structural flexibility of both the ligand and synthetic receptor. We follow an adaptive strategy, in which one molecule is expanded by attaching its next fragment in all possible torsion angles, whereas the other (partially assembled) molecule serves as a rigid binding partner. Then the roles of the molecules are exchanged. Geometric filters are used to discard partial conformations that cannot realize a targeted interaction pattern derived in a graph-based precomputation phase. The process is repeated until the entire complex is built up. Our algorithm produces promising results on a test data set comprising 10 complexes of synthetic receptors and ligands. The method generated near-native solutions compared to crystal structures in all but one case. It is able to generate solutions within a couple of minutes and has the potential of being used as a virtual screening tool for searching for suitable guest molecules for a given synthetic receptor in large databases of guests and vice versa.