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Interactive Dendrograms: The R Packages idendro and idendr0

2017, Sieger, Tomáš, Hurley, Catherine B., Fiser, Karel, Beleites, Claudia

Hierarchical cluster analysis is a valuable tool for exploring data by describing their structure using a dendrogram. However, proper visualization and interactive inspection of the dendrogram are needed to unlock the information in the data. We describe a new R package, idendro, that enables the user to inspect dendrograms interactively: to select and color clusters, to zoom and pan the dendrogram, and to visualize the clustered data not only in a built-in heat map, but also in any interactive plot implemented in the cranvas package. A lightweight version idendr0 with reduced dependencies is also available from the Comprehensive R Archive Network.

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Compomics-utilities: An open-source Java library for computational proteomics

2011, Barsnes, Harald, Vaudel, Marc, Helsens, Kenny, Sickmann, Albert, Walther, Dirk, Berven, Frode S.

The growing interest in the field of proteomics has increased the demand for software tools and applications that process and analyze the resulting data. And even though the purpose of these tools can vary significantly, they usually share a basic set of features, including the handling of protein and peptide sequences, the visualization of (and interaction with) spectra and chromatograms, and the parsing of results from various proteomics search engines. Developers typically spend considerable time and effort implementing these support structures, which detracts from working on the novel aspects of their tool.

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The quest for research information

2014, Blümel, Ina, Dietze, Stefan, Heller, Lambert, Jäschke, Robert, Mehlberg, Martin

Research information, i.e., data about research projects, organisations, researchers or research outputs such as publications or patents, is spread across the web, usually residing in institutional and personal web pages or in semi-open databases and information systems. While there exists a wealth of unstructured information, structured data is limited and often exposed following proprietary or less-established schemas and interfaces. Therefore, a holistic and consistent view on research information across organisational and national boundaries is not feasible. On the other hand, web crawling and information extraction techniques have matured throughout the last decade, allowing for automated approaches of harvesting, extracting and consolidating research information into a more coherent knowledge graph. In this work, we give an overview of the current state of the art in research information sharing on the web and present initial ideas towards a more holistic approach for boot-strapping research information from available web sources.

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RADAR-Team stellt Testsystem auf zweitem Projekt-Workshop in Frankfurt vor

2015, Potthoff, Jan, Razum, Matthias, Kraft, Angelina

Im Rahmen des Projekts "Research Data Repository" (RADAR) wurde am 23. Juni 2015 auf dem zweiten Projekt-Workshop der aktuelle Stand des Testsystems, das zur Archivierung und Publikation von Forschungsdaten genutzt werden kann, vorgestellt. Außerdem wurden weitere Anforderungen an das System und allgemeine Fragen des Forschungsdatenmanagements mit den Workshop-Teilnehmern diskutiert.

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Efficient retrieval of 3D building models using embeddings of attributed subgraphs

2011, Wessel, R., Ochmann, S., Vock, R., Blümel, Ina, Klein, R.

We present a novel method for retrieval and classification of 3D building models that is tailored to the specific requirements of architects. In contrast to common approaches our algorithm relies on the interior spatial arrangement of rooms instead of exterior geometric shape. We first represent the internal topological building structure by a Room Connectivity Graph (RCG). Each room is characterized by a node. Connections between rooms like e.g. doors are represented by edges. Nodes and edges are additionally assigned attributes reflecting room and edge properties like e.g area or window size. To enable fast and efficient retrieval and classification with RCGs, we transform the structured graph representation into a vector-based one. We first decompose the RCG into a set of subgraphs. For each subgraph, we compute the similarity to a set of codebook graphs. Aggregating all similarity values finally provides us with a single vector for each RCG which enables fast retrieval and classification. For evaluation, we introduce a classification scheme that was carefully developed following common guidelines in architecture.We finally provide comprehensive experiments showing that the introduced subgraph embeddings yield superior performance compared to state-of-the-art graph retrieval approaches.

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ISense: A portable ultracold-atom-based gravimeter

2011, de Angelis, M., Angonin, M.C., Beaufils, Q., Becker, Ch., Bertoldi, A., Bongs, K., Bourdel, T., Bouyer, P., Boyer, V., Dörscher, S., Duncker, H., Ertmer, W., Fernholz, T., Fromhold, T.M., Herr, W., Krüger, P., Kürbis, Ch., Mellor, C.J., Pereira Dos Santos, F., Peters, A., Poli, N., Popp, M., Prevedelli, M., Rasel, E.M., Rudolph, J., Schreck, F., Sengstock, K., Sorrentino, F., Stellmer, S., Tino, G.M., Valenzuela, T., Wendrich, T.J., Wicht, A., Windpassinger, P., Wolf, P.

We present iSense, a recently initiated FET project aiming to use Information and Communication Technologies (ICT) to develop a platform for portable quantum sensors based on cold atoms. A prototype of backpack-size highprecision force sensor will be built to demonstrate the concept.