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Auflistung nach Autor:in "Schroeder, Michael"

1 - 10 von 29
  • Konferenzbeitrag
    Classifying permanent and transient protein interactions
    (German Conference on Bioinformatics, 2006) Kottha, Samatha; Schroeder, Michael
    Currently much research is devoted to the characterization and classification of transient and permanent protein-protein interactions. From the literature, we take data sets consisting of 161 permanent (65 homodimers, 96 heterodimers) and 242 transient interactions. We collect over 300 interface attributes relating to size, physiochemical properties, interaction propensities, and secondary structure elements. Our major discovery is a surprisingly simple relationship not yet reported in the literature: interactions with the same molecular weight or very big interfaces are per- manent and otherwise transient. We train a support vector machine and achieve the following results: Molecular weight difference alone achieves 80% success rate. To- gether with the size of the buried surface the success rate improves to 89%. Adding water at the interface and the number of hydrophobic contacts we achieve a success rate of 97%.
  • Konferenzbeitrag
    A Comparative Study of Robust Feature Detectors for 2D Electrophoresis Gel Image Registration
    (German Conference on Bioinformatics, 2008) Möller, Birgit; Greß, Oliver; Posch, Stefan
    In this study we consider the performance of different feature detectors used as the basis for the registration of images from two-dimensional gel electrophoresis. These are three spot detectors also used to identify proteins, and two domain inde- pendent keypoint detectors. We conduct a case study with images from a publically available data set which are synthetically distorted using thin plate splines. The per- formance is assessed by the repeatability score, the probability of an image structure to be detected in original and distorted images with reasonable localization accuracy.
  • Konferenzbeitrag
    Consecutive KEGG pathway models for the interpretation of high-throughput genomics data
    (German Conference on Bioinformatics, 2008) Antonov, Alexey V.; Diemann, Sabine; Mewes, Han W.
    A common strategy to deal with the interpretation of gene lists is to look for overrepresentation of Gene Ontology (GO) terms or pathways. In related computational approaches the cell is formalized as genes that are grouped into functional categories. As output, a list of interesting biological processes is provided, which seems to be mostly covered by the supplied gene list. However, it is more natural to model the cell as a network that reflects relations between genes. For many biological processes such information is available, but it is not used to the full extent in interpretational analyses. In this paper, we propose to interpret gene lists in network terms to provide the most probable scenario of gene interactions based on the available information about the topology of metabolic pathways. The proposed approach is an effort to exploit the biological information available in public resources to a greater extent in comparison to the existing techniques. Applying our approach to experimental data, we demonstrate that the currently widely employed strategy produces an incomplete interpretation, whilst our procedure provides deeper insights into possible molecular mechanisms behind the experimental data.
  • Konferenzbeitrag
    Designing Binding Pockets on Protein Surfaces using the A* Algorithm
    (German Conference on Bioinformatics, 2008) Eyrisch, Susanne; Helms, Volkhard
    The in-silico design of ligands binding to the protein surface instead of deep binding pockets is still a great challenge. Often no appropriate binding pockets are available in the apo experimental structures and standard virtual screening techniques will fail. Here, we present two new algorithms for designing tailored ligand binding pockets on the protein surface that account for protein backbone and side chain flexibility. At first, the protein surface is scanned for potential pocket positions using a program named PocketScanner. This program minimizes the protein energetically in the presence of generic pocket spheres representing the new binding pockets whose positions remain fixed. The side chains of the relaxed protein conformations are then further refined by a second program named PocketBuilder. PocketBuilder identifies all residues within a given radius of the pocket positions and searches for the best combination of side chain rotamers using the A* algorithm. Given multiple protein conformations as input, PocketBuilder identifies those that lead to the best results, namely protein conformations of low energy that possess binding pockets with desired properties. The approach was tested on the proteins BCL-XL, IL-2, and MDM2 which are involved in protein-protein interactions and hence represent challenging drug tar- gets. Although the native ligand binding pocket was not or only partly open in the apo crystal or NMR structures, PocketScanner and PocketBuilder successfully generated conformations with pockets into which a known inhibitor could be docked in a native- like orientation for two out of the three test systems. For BCL-XL, the docking scores were even similar to those obtained in re-docking experiments to the inhibitor bound crystal structure.
  • Konferenzbeitrag
    Evolutionary Construction of Multiple Graph Alignments for the Structural Analysis of Biomolecules
    (German Conference on Bioinformatics, 2008) Fober, Thomas; Hüllermeier, Eyke; Mernberger, Marco
    The concept of multiple graph alignment has recently been introduced as a novel method for the structural analysis of biomolecules. Using inexact, approximate graph-matching techniques, this method enables the robust identification of approximately conserved patterns in biologically related structures. In particular, multiple graph alignments enable the characterization of functional protein families independent of sequence or fold homology. This paper first recalls the concept of multiple graph alignment and then addresses the problem of computing optimal alignments from an algorithmic point of view. In this regard, a method from the field of evolutionary algorithms is proposed and empirically compared to a hitherto existing greedy strategy. Empirically, it is shown that the former yields significantly better results than the latter, albeit at the cost of an increased runtime.
  • Konferenzbeitrag
    Exploring the Enzyme Neighbourhood to interpret gene expression data
    (German Conference on Bioinformatics, 2008) Goffard, Nicolas; Frickey, Tancred; Imin, Nijat; Weiller, Georg
    Post-genomic data analysis represents a new challenge to link and interpret the vast amount of raw data obtained with transcriptomic or proteomic techniques in the context of metabolic pathways. We propose a new strategy with the help of a metabolic network graph to extend PathExpress, a web-based tool to interpret gene expression data, without being restricted to predefined pathways. We defined the Enzyme Neighbourhood as groups of linked enzymes, corresponding to a sub-network, to explore the metabolic network in order to identify the most relevant sub-networks affected in gene expression experiments.
  • Konferenzbeitrag
    FRANz: Fast reconstruction of wild pedigrees
    (German Conference on Bioinformatics, 2008) Riester, Markus; Peter F., Stadler; Klemm, Konstantin
    We present a software package for fast pedigree reconstruction in natural populations using co-dominant genomic markers such as microsatellites and SNPs. If available, the algorithm makes use of prior information such as known relationships (sub-pedigrees) or the age and sex of individuals. Statistical confidence is estimated by a simulation of the sampling process. The accuracy of the algorithm is demonstrated for simulated data as well as an empirical data set with known pedigree. The parentage inference is robust even in the presence of genotyping errors.
  • Editiertes Buch
    German Conference on Bioinformatics
    (German Conference on Bioinformatics, 2008)
  • Konferenzbeitrag
    GoPubMed: ontology-based literature search applied to gene ontology and pubmed
    (German Conference on Bioinformatics 2004, GCB 2004, 2004) Delfs, Ralph; Doms, Andreas; Kozlenkov, Alexander; Schroeder, Michael
    The biomedical literature grows at a tremendous rate, so that finding the relevant literature is becoming more and more difficult. To address this problem we introduce ontology-based literature search, which structures search results thorugh the categories of an ontology. We develop and implement GoP- ubMed, which submits keywords to PubMed, extracts GeneOntology-terms from the retrieved abstracts, and presents the relevant sub-ontology for browsing. For GoPubMed we develop a novel term extraction algorithm and evaluate its performance. GoPubMed is available at www.gopubmed.org
  • Zeitschriftenartikel
    Grid-Computing
    (Informatik-Spektrum: Vol. 27, No. 6, 2004) Bry, François; Nagel, Wolfgang E.; Schroeder, Michael
    „Grid-Computing“, ein Mitte der 90er-Jahre eingeführter Begriff [1,2], bezeichnet eine Architektur für verteilte Systeme, die auf dem World Wide Web aufbaut und die Web-Vision erweitert. Mit dem Grid-Computing werden die Ressourcen einer Gemeinschaft, einer so genannten „virtuellen Organisation“, integriert. Die Hoffnung ist, dass hierdurch rechen- und/oder datenintensiven Aufgaben, die eine einzelne Organisation nicht lösen kann, handhabbar werden. Ein „Grid“ bezeichnet eine nach dem Grid-Computing-Ansatz aufgebaute Rechner-, Netzwerk- und Software-Infrastruktur zur Teilung von Ressourcen mit dem Ziel, die Aufgaben einer virtuellen Organisation zu erledigen.