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Many real world problems can be mapped onto graphs and solved with well-established efficient algorithms studied in graph theory. One such problem is to find large sets of points satisfying some mutual relationship. This problem can be transformed to the problem of finding all cliques of an undirected graph by mapping each point onto a vertex of the graph and connecting any two vertices by an edge whose corresponding points satisfy our desired relationship. Clique detection has been widely studied and there exist efficient algorithms. In this paper we study a related problem, where all points have a set of binary attributes, each of which is either 0 or 1. This is only a small limitation, since all discrete properties can be mapped onto binary attributes. In our case, we want to find large sets of points not only satisfying some mutual relationship; but, in addition, all points of a set also need to have at least one common attribute with value 1. The problem we described can be mapped onto a set of induced subgraphs, where each subgraph represents a single attribute. For attribute $i$, its associated subgraph contains those vertices corresponding to the points with attribute $i$ set to 1. We introduce the notion of a maximal clique of a family, $\mathcal{G}$, of induced subgraphs of an undirected graph, and show that determining all maximal cliques of $\mathcal{G}$ solves our problem. Furthermore, we present an efficient algorithm to compute all maximal cliques of $\mathcal{G}$. The algorithm we propose is an extension of the widely used Bron-Kerbosch algorithm.

One crucial step in virtual drug design is the identification of new lead structures with respect to a pharmacological target molecule. The search for new lead structures is often done with the help of a pharmacophore, which carries the essential structural as well as physico-chemical properties that a molecule needs to have in order to bind to the target molecule. In the absence of the target molecule, such a pharmacophore can be established by comparison of a set of active compounds. In order to identify their common features,a multiple alignment of all or most of the active compounds is necessary. Moreover, since the “outer shape” of the molecules plays a major role in the interaction between drug and target, an alignment algorithm aiming at the identification of common binding properties needs to consider the molecule’s “outer shape”, which can be approximated by the solvent excluded surface. In this thesis, we present a new approach to molecular surface alignment based on a discrete representation of shape as well as physico-chemical properties by points distributed on the solvent excluded surface. We propose a new method to distribute points regularly on a surface w.r.t. a smoothly varying point density given on that surface. Since the point distribution algorithm is not restricted to molecular surfaces, it might also be of interest for other applications. For the computation of pairwise surface alignments, we extend an existing point matching scheme to surface points, and we develop an efficient data structure speeding up the computation by a factor of three. Moreover, we present an approach to compute multiple alignments from pairwise alignments, which is able to handle a large number of surface points. All algorithms are evaluated on two sets of molecules: eight thermolysin inhibitors and seven HIV-1 protease inhibitors. Finally, we compare the results obtained from surface alignment with the results obtained by applying an atom alignment approach.

We present iCon.text, a kiosk platform for the iPad centered around artefacts, whose content and layout can be tailored without programming skills for specific museum exhibitions. The central metaphor to access information is a virtual postcard with one front and a customizable number of back sides that provide details about exhibits to museum visitors in textual and image form. Back sides can link to others cards. Access to these postcards is possible through one or more navigation views that can be navigated to from a navigation bar.
The entry point to the application is designed as a multitouch interactive pile of cards in a playful manner that allows visitors of any age an easy approach to the presentation and interaction metaphor. To directly access a certain postcard, a mosaic view can be uitilized to provide an overview about all available exhibits. A category view groups postcards into themes. Locating artefacts on a zoomable map or exhibition floor plan allows for conveying information about spatial contexts between different objects and their location. Furthermore, contexts can be illustrated with a two stage view comprising an overview and corresponding detail views to provide further insights into the spatial, temporal, and thematic contexts of artefacts. The application scaffolding allows the design of bilingual presentations to support exhibitions with an international audience. The logo of the presenting institution or exhibition can be incorporated to display the the kiosk's corporate design branding and to access an imprint or further informations. Usage is logged into files to provide a basis for extracting statistical information about the usage.
The details about the exhibits are presented as images and as such impose no limit to the design choices made by the content provider or exhibition designer.
The application (enhanced with a panoramic view) has been integrated successfully into a large special exhibition about the ancient city of Pergamon 2011/2012 at the Pergamon Museum Berlin within the interdisciplinary project "Berlin Sculpture Network".

In this paper we describe a new algorithm for multiple semi-flexible superpositioning of drug-sized molecules. The algorithm identifies structural similarities of two or more molecules. When comparing a set of molecules on the basis of their three-dimensional structures, one is faced with two main problems. (1) Molecular structures are not fixed but flexible, i.e., a molecule adopts different forms. To address this problem, we consider a set of conformers per molecule. As conformers we use representatives of conformational ensembles, generated by the program ZIBMol. (2) The degree of similarity may vary considerably among the molecules. This problem is addressed by searching for similar substructures present in arbitrary subsets of the given set of molecules. The algorithm requires to preselect a reference molecule. All molecules are compared to this reference molecule. For this pairwise comparison we use a two-step approach. Clique detection on the correspondence graph of the molecular structures is used to generate start transformations, which are then iteratively improved to compute large common substructures. The results of the pairwise comparisons are efficiently merged using binary matching trees. All common substructures that were found, whether they are common to all or only a few molecules, are ranked according to different criteria, such as number of molecules containing the substructure, size of substructure, and geometric fit. For evaluating the geometric fit, we extend a known scoring function by introducing weights which allow to favor potential pharmacophore points. Despite considering the full atomic information for identifying multiple structural similarities, our algorithm is quite fast. Thus it is well suited as an interactive tool for the exploration of structural similarities of drug-sized molecules.