This paper presents the application of iterative solution techniques to large sparse equation systems derived from PEEC modeling. The PEEC method (partial element equivalent circuit) is an approach to transform conduc...
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This paper presents the application of iterative solution techniques to large sparse equation systems derived from PEEC modeling. The PEEC method (partial element equivalent circuit) is an approach to transform conducting objects into linear networks with basic electrical elements. Such equivalent circuit models can be simulated by conventional circuit solvers such as SPICE (simulation program for integrated circuit emphasis) based on the MNA (modified nodal analysis) approach. By applying appropriate sparsification techniques sparse system matrices can be obtained, adequate for iterative solvers. By using multilevel approaches linear complexity in time and memory requirements can be achieved in the best case. The suitability of different iterative methods as applied to such systems is compared by means of examples
Switching operations in integrated circuits are often the reason for electromagnetic disturbances which can spread over the whole system. This is especially important for automotive applications where many control sys...
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Switching operations in integrated circuits are often the reason for electromagnetic disturbances which can spread over the whole system. This is especially important for automotive applications where many control systems are connected together via cable harnesses. Although model order reduction techniques help to reduce the computational effort resulting from realistic automotive simulation problems suitable solver strategies are indispensable. Their efficiency highly depends on the matrix properties which are directly affected by the kind of modeling and simulation approach. In this paper it is shown that hybrid solver strategies are most advantageous for flexible EM simulation. Analysis of the matrix properties helps to identify the most appropriate solver
Access to relevant information and knowledge is essential for all steps of the drug discovery process. However, keeping track of relevant information in publications and patents becomes a real challenge for scientists...
In this paper we treat the cell-centred multigrid approach, which distinguishes itself from the classical vertex-centred multigrid by a non-nested hierarchy of grid nodes and the use of constant, problem-independent t...
In this paper we treat the cell-centred multigrid approach, which distinguishes itself from the classical vertex-centred multigrid by a non-nested hierarchy of grid nodes and the use of constant, problem-independent transfer operators even in complicated situations. We demonstrate, that the tool of Local Fourier Analysis can also be profitably applied in this setting. We consider in detail the standard transfer operators from literature and their respective polynomial and Fourier orders, paying special attention to the combination of piecewise constant interpolation and its adjoint. Furthermore, we give several numerical examples for model problems and an application from biomedical engineering.
The present paper describes two cooperative projects (AUTOBENCH and AUTO-OPT) carried out with partners in the automotive industries (AUDI, BMW, DaimlerChrysler, Karmann and Porsche), software vendors of simulation so...
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We propose a specification language ProML for protein sequences, structures, and families based on the open XML standard. The language allows for portable, system-independent, machine-parsable and human-readable repre...
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We propose a specification language ProML for protein sequences, structures, and families based on the open XML standard. The language allows for portable, system-independent, machine-parsable and human-readable representation of essential features of proteins. The language is of immediate use for several bioinformatics applications: we discuss clustering of proteins into families and the representation of the specific shared features of the respective clusters. Moreover, we use ProML for specification of data used in fold recognition bench-marks exploiting experimentally derived distance constraints.
We present a comprehensive analysis of methods for improving the fold recognition rate of the threading approach to protein structure prediction by the utilization of few additional distance constraints. The distance ...
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We present a comprehensive analysis of methods for improving the fold recognition rate of the threading approach to protein structure prediction by the utilization of few additional distance constraints. The distance constraints between protein residues may be obtained by experiments such as mass spectrometry or NMR spectroscopy. We applied a post-filtering step with new scoring functions incorporating measures of constraint satisfaction to ranking lists of 123D threading alignments. The detailed analysis of the results on a small representative benchmark set show that the fold recognition rate can be improved significantly by up to 30% from about 54%-65% to 77%-84%, approaching the maximal attainable performance of 90% estimated by structural superposition alignments. This gain in performance adds about 10% to the recognition rate already achieved in our previous study with cross-link constraints only. Additional recent results on a larger benchmark set involving a confidence function for threading predictions also indicate notable improvements by our combined approach, which should be particularly valuable for rapid structure determination and validation of protein models.
MOTIVATION:Large scale gene expression data are often analysed by clustering genes based on gene expression data alone, though a priori knowledge in the form of biological networks is available. The use of this additi...
MOTIVATION:Large scale gene expression data are often analysed by clustering genes based on gene expression data alone, though a priori knowledge in the form of biological networks is available. The use of this additional information promises to improve exploratory analysis considerably.
RESULTS:We propose constructing a distance function which combines information from expression data and biological networks. Based on this function, we compute a joint clustering of genes and vertices of the network. This general approach is elaborated for metabolic networks. We define a graph distance function on such networks and combine it with a correlation-based distance function for gene expression measurements. A hierarchical clustering and an associated statistical measure is computed to arrive at a reasonable number of clusters. Our method is validated using expression data of the yeast diauxic shift. The resulting clusters are easily interpretable in terms of the biochemical network and the gene expression data and suggest that our method is able to automatically identify processes that are relevant under the measured conditions.
Alignments of frequency profiles against frequency profiles have a wide scope of applications in currently used bioinformatic analysis tools ranging from multiple alignment methods based on the progressive alignment a...
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