P136 - GCB 2008 - German Conference on Bioinformatics 2008
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Auflistung P136 - GCB 2008 - German Conference on Bioinformatics 2008 nach Autor:in "Beyer, Andreas"
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- KonferenzbeitragA Comparative Study of Robust Feature Detectors for 2D Electrophoresis Gel Image Registration(German Conference on Bioinformatics, 2008) Möller, Birgit; Greß, Oliver; Posch, StefanIn 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.
- KonferenzbeitragConsecutive 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.
- KonferenzbeitragDesigning Binding Pockets on Protein Surfaces using the A* Algorithm(German Conference on Bioinformatics, 2008) Eyrisch, Susanne; Helms, VolkhardThe 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.
- KonferenzbeitragEvolutionary Construction of Multiple Graph Alignments for the Structural Analysis of Biomolecules(German Conference on Bioinformatics, 2008) Fober, Thomas; Hüllermeier, Eyke; Mernberger, MarcoThe 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.
- KonferenzbeitragExploring the Enzyme Neighbourhood to interpret gene expression data(German Conference on Bioinformatics, 2008) Goffard, Nicolas; Frickey, Tancred; Imin, Nijat; Weiller, GeorgPost-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.
- KonferenzbeitragFRANz: Fast reconstruction of wild pedigrees(German Conference on Bioinformatics, 2008) Riester, Markus; Peter F., Stadler; Klemm, KonstantinWe 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 BuchGerman Conference on Bioinformatics(German Conference on Bioinformatics, 2008)
- KonferenzbeitragIdentifying the topology of protein complexes from affinity purification assays(German Conference on Bioinformatics, 2008) Friedel, Caroline C.; Zimmer, RalfRecent advances in high-throughput technologies have made it possible to investigate not only individual protein interactions but the association of these proteins in complexes. So far the focus has been on the prediction of complexes as sets of proteins from the experimental results while the modular substructure and the physical interactions within protein complexes have been mostly ignored. In this article, we present an approach for identifying the direct physical interactions and the subcomponent structure of protein complexes predicted from affinity purification assays. Our algorithm calculates the union of all maximum spanning trees from scoring networks for each protein complex to extract relevant interactions. In a subsequent step this network is extended to interactions which are not accounted for by alternative indirect paths. We show that the interactions identified with this approach are more accurate in predicting experimentally derived physical interactions than baseline approaches and resolve more satisfactorily the subcomponent structure of the complexes. The usefulness of our approach is illustrated on the RNA polymerases for which the modular substructure can be successfully reconstructed with our method.
- KonferenzbeitragIntuitive Modeling of Dynamic Systems with Petri Nets and Fuzzy Logic(German Conference on Bioinformatics, 2008) Windhager, Lukas; Zimmer, RalfCurrent approaches in modeling dynamic biological systems often lack comprehensibility, especially for users without mathematical background. We pro- pose a new approach to overcome such limitations by combining the graphical representation provided by the use of Petri nets with the modeling of dynamics by powerful yet intuitive fuzzy logic based systems. The mathematical functions and formulations typically used to describe or quantify dynamic changes of systems are replaced by if-then rules, which are both easy to read and formulate. Precise values of kinetic constants or concentrations are substituted by more natural fuzzy representations of entities. We will show that our new approach allows a semi-quantitative modeling of biological systems like signal transduction pathways or metabolic processes while not being limited to those cases.
- KonferenzbeitragKIRMES: Kernel-based Identification of Regulatory Modules in Euchromatic Sequences(German Conference on Bioinformatics, 2008) Schultheiss, Sebastian; Busch, Wolfgang; Lohmann, Jan U.; Kohlbacher, Oliver; Rätsch, GunnarMotivation: Understanding transcriptional regulation is one of the main challenges in computational biology. An important problem is the identification of transcription factor binding sites in promoter regions of potential transcription factor target genes. It is typically approached by position weight matrix-based motif identification algorithms using Gibbs sampling or heuristics for extending seed oligos. Such algorithms succeed in identifying single, relatively well conserved binding sites, but tend to fail when it comes to the identification of combinations of several degenerate binding sites as those often found in cis-regulatory modules. Results: We propose a new algorithm that combines the benefits of existing motif finding with the ones of Support Vector Machines (SVMs) to find degenerate motifs in order to improve the modeling of regulatory modules. In experiments on microarray data from Arabidopsis thaliana we were able to show that the newly developed strat- egy significantly improves the recognition of transcription factor targets. Availability: The PYTHON source code (open source–licensed under GPL), the data for the experiments and a web-service are available at http://www.fml.mpg. de/raetsch/projects/kirmes. Contact: sebi@tuebingen.mpg.de