http://dl.gi.de/handle/20.500.12116/30177 2026-07-21T13:26:29Z http://dl.gi.de/handle/20.500.12116/30193 Graph drawing algorithms for bioinformatics Kaufmann, Michael Schubert, Sigrid E.; Reusch, Bernd; Jesse, Norbert Graph drawing has recently received growing attention as various techniques have been developed for applications in areas ranging from software technology to business modeling, from network administration to cognitive sciences. Recently, we have designed and realized the tool yWays to support the analysis of biochemical pathways by visualization. In the talk, we will use this tool as a example to discuss to what extend the standard layout algorithms can be used, and what the challenges are to achieve 'real' applicability. 2002-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/30191 Geometric problems and algorithms in computer-aided molecular design Rarey, Matthias Schubert, Sigrid E.; Reusch, Bernd; Jesse, Norbert Computer-Aided Molecular Design describes a research area covering all kinds of computer applications in the design of molecules having desired properties. It is widely applied for the design of bioactive molecules like pharmaceuticals or agricultural products. From the computer scientists perspective, computer-aided molecular design contains a large variety of computational problems, often geometric and/or combinatorial in nature. In the introductory part of this talk, a short overview of these problems is given. The main focus in this talk will be on protein-ligand docking. The aim of a docking calculation is to predict, whether two molecules bind to each other (i.e. form an energetically favorable complex). If they do so, one is interested in the geometry of the molecular complex and in the binding energy. The most prominent variant is protein-ligand docking. Here the first molecule is a protein while the second molecule is a small compound. Since most drug targets are proteins and most drugs are small compounds, software for protein-ligand docking is extensively used in pharmaceutical research. Since 1993, we are developing the software package FlexX which belongs to the most widely used codes for protein-ligand docking. An outline of the underlying models, the applied algorithms as well as some examples will be presented. 2002-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/30192 Machine learning approaches for deciphering complex pathomechanismsin cancer Eils, Roland Schubert, Sigrid E.; Reusch, Bernd; Jesse, Norbert Recent years have seen a dramatic increase in the amount of genetic information stored in electronic format. It has been estimated that the amount of information in genomics and proteomics doubles every 20 months and the size and number of databases are increasing even faster. It is widely accepted that a sophisticated exploration of such data is crucial in a variety of fields such as disease genetics and pharmacogenomics. While both corporate and institutional efforts have concentrated on the integration of heterogeneous data in genomics and proteomics, a systematic data exploration is still at its beginning. Although data mining has celebrated many successes in business operations applications as retail and marketing (see e.g. [1]), its application to scientific and engineering data is not straightforward. Data sets in life sciences are often significantly larger in volume, structurally more complex then traditional business data, and often rapidly changing in time. In contrast to business environments, the body of existing background knowledge in life sciences is extensive. I will report on our recent efforts [2,3] to adapt data mining technology in particular from the field of machine learning for effective knowledge discovery in tumour genetics. To exemplify the power of this approach, we will describe how complex concepts such as survival or therapy response [4,5] can be learnt from heterogeneous clinical or molecular data. 2002-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/30190 Fachdatenbanken und Internet-Quellen: Rechercheüberstieg durch Anfragetransfer Strötgen, Robert Schubert, Sigrid E.; Reusch, Bernd; Jesse, Norbert Die Sonderfördermaßnahme CARMEN1 zielte unter anderem darauf ab, die Erweiterung von Recherchen in bibliographischen Fachdatenbanken ins Internet zu verbessern. Dabei war das Problem der semantischen Heterogenität zu behandeln, die durch unterschiedliche Inhaltserschließung in verschiedenen Datenbeständen auftritt. Dazu wurden verschiedene Ansätze wie Metadatenextraktion aus Internetquellen und Anfragetransfers über Cross-Konkordanzen und statistisch erzeugte Relationen gewählt. Dieser Aufsatz stellt das Konzept und die Implementierung der Anfragetransfers sowie die Evaluation der Auswirkungen auf das Retrievalergebnis vor. 2002-01-01T00:00:00Z