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P136 - GCB 2008 - German Conference on Bioinformatics 2008

https://dl.gi.de/handle/20.500.12116/21204
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Auflistung P136 - GCB 2008 - German Conference on Bioinformatics 2008 nach Erscheinungsdatum

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  • Konferenzbeitrag
    Protein Structure Alignment through a Contact Topology Profile using SABERTOOTH
    (German Conference on Bioinformatics, 2008) Teichert, F.; Bastolla, U.; Porto, M.
    The contact vector (CV) of a protein structure is one of the simplest and most condensed descriptions of protein structure available. It lists the number of con- tacts each amino acid has with the surrounding structure and has frequently been used e.g. to derive approximative folding energies in protein folding analysis. The CV, however, is a lossy structure representation, as it does not contain sufficient information to allow for the reconstruction of the full protein structure it was derived from. The loss of information leads to a degeneracy in the sense that a single contact vector is compatible with many different contact matrices, but it has been shown that this degeneracy is nearly fully compensated by the physical constraints protein structure is subject to. We recently developed the alignment framework ‘SABERTOOTH’ that is able to generically align connectivity related vectorial structure profiles to compute protein alignments. Here we show that also the CV allows for state-of-the-art alignment quality, just like the elaborated ‘Effective Connectivity’ profile (EC) that SABERTOOTH currently uses. This simplification leeds to a very simple and elegant approach to structure alignment, which accelerates and generalizes the algorithm we previously proposed. Furthermore, we conclude from our work that the CV in itself is a useful structure description if its collective properties are called for.
  • Konferenzbeitrag
    KIRMES: Kernel-based Identification of Regulatory Modules in Euchromatic Sequences
    (German Conference on Bioinformatics, 2008) Schultheiss, Sebastian; Busch, Wolfgang; Lohmann, Jan U.; Kohlbacher, Oliver; Rätsch, Gunnar
    Motivation: 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
  • Konferenzbeitrag
    Lightweight Comparison of RNAs Based on Exact Sequence-Structure Matches
    (German Conference on Bioinformatics, 2008) Heyne, Steffen; Will, Sebastian; Beckstette, Michael; Backofen, Rolf
    Specific functions of RNA molecules are often associated with different motifs in the RNA structure. The key feature that forms such an RNA motif is the combination of sequence and structure properties. In this paper we introduce a new RNA sequence-structure comparison method which maintains exact matching substructures. Existing common substructures are treated as whole unit while variability is allowed between such structural mo- tifs. Based on a fast detectable set of overlapping and crossing substructure matches for two nested RNA secondary structures, our method computes the longest colinear sequence of substructures common to two RNAs in O(n2m2) time and O(nm) space. Applied to different RNAs, our method correctly identifies sequence-structure similarities between two RNAs. The results of our experiments are in good agreement with existing alignment-based meth- ods, but can be obtained in a fraction of running time, in particular for larger RNAs. The proposed algorithm is implemented in the program expaRNA, which is available from our website (www.bioinf.uni-freiburg.de/Software).
  • Konferenzbeitrag
    Intuitive Modeling of Dynamic Systems with Petri Nets and Fuzzy Logic
    (German Conference on Bioinformatics, 2008) Windhager, Lukas; Zimmer, Ralf
    Current 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.
  • Konferenzbeitrag
    Utilizing promoter pair orientations for HMM-based analysis of ChIP-chip data
    (German Conference on Bioinformatics, 2008) Seifert, Michael; Keilwagen, Jens; Strickert, Marc; Grosse, Ivo
    Array-based analysis of chromatin immunoprecipitation data (ChIP-chip) is a powerful technique for identifying DNA target regions of individual transcription factors. Here, we present three approaches, a standard log-fold-change analysis (LFC), a basic method based on a Hidden Markov Model (HMM), and an ex- tension of the HMM approach to an HMM with scaled transition matrices (SHMM) to incorporate different promoter pair orientations. We compare the prediction of ABI3 target genes for the three methods and evaluate these genes using Geneves- tigator expression profiles and transient assays. We find that the application of the SHMM leads to a superior identification of ABI3 target genes. The software and the ChIP-chip data set used in our case study can be downloaded from http://dig.ipk- gatersleben.de/SHMMs/ChIPchip/ChIPchip.html.
  • 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
    Temporal Analysis of Oncogenesis Using MicroRNA Expression Data
    (German Conference on Bioinformatics, 2008) Zichner, Thomas; Lubovac, Zelmina; Olsson, Björn
    MicroRNAs (miRNAs) have rapidly become the focus of many cancer research studies. These small non-coding RNAs have been shown to play important roles in the regulation of oncogenes and tumor suppressors. It has also been demonstrated that miRNA expression profiles differ significantly between normal and cancerous cells, which indicates the possibility of using miRNAs as markers for cancer diagnosis and prognosis. However, not much is known about the regulation of miRNA expression. One of the issues worth investigating is whether deregulations of miRNA expression in cancer cells occur according to some pattern or in a random order. We therefore selected two approaches, previously used to derive graph models of oncogenesis using chromosomal imbalance data, and adapted them to miRNA expression data. Applying the adapted algorithms to a breast cancer data set, we obtained results indicating the temporal order of miRNA deregulations during tumor development. When analyzing the specific deregulations appearing at different time points in the derived model, we found that several of the deregulations identified as early events could be supported through literature studies.
  • Editiertes Buch
    German Conference on Bioinformatics
    (German Conference on Bioinformatics, 2008)
  • Konferenzbeitrag
    Structure Local Multiple Alignment of RNA
    (German Conference on Bioinformatics, 2008) Otto, Wolfgang; Will, Sebastian; Backofen, Rolf
    Today, RNA is well known to perform important regulatory and catalytic function due to its distinguished structure. Consequently, state-of-the-art RNA multiple alignment algorithms consider structure as well as sequence information. However, existing tools neglect the important aspect of locality. Notably, locality in RNA occurs as similarity of subsequences as well as similarity of only substructures. We present a novel approach for multiple alignment of RNAs that deals with both kinds of locality. The approach extends LocARNA by structural locality for computing all- against-all pairwise, structural local alignments. The final construction of the multiple alignments from the pairwise ones is delegated to T-Coffee. The paper systematically investigates structural locality in known RNA families. Benchmarking multiple align- ment tools on structural local families shows the need for algorithmic support of this locality. The improvement in accuracy in special cases is achieved while staying competitive with state-of-the-art alignment tools across the whole Bralibase. LocARNA and its T-Coffee extended variant LocARNATE are freely available at http://www.bioinf.uni-freiburg.de/Software/LocARNA/.
  • Konferenzbeitrag
    ResqMi - a versatile algorithm and software for Resequencing Microarrays
    (German Conference on Bioinformatics, 2008) Symons, Stephan; Weber, Kirstin; Bonin, Michael; Nieselt, Kay
    Resequencing microarrays are a common tool for fast monitoring of individual genetic variations. Applications include diagnosis of genetic and infectious diseases and SNP prediction. Base calling is the crucial step in the analysis of resequencing data. All current base calling algorithms produce ambiguous calls on parts of the sequence. Therefore, proper data handling, editing and visualization as well as revised calling algorithms are generally necessary for successful data interpretation. We present a base calling algorithm that uses a model-based approach using intensity comparisons and region-wise conformance assessment, as well as an algorithm to revise uncalled positions. The calling algorithm is shown to have call rates comparable to ABACUS, the currently most commonly used method. Both algorithms combined however can considerably increase the calling rate. We also present a new open source software called ResqMi, short for Resequencing using Microarrays, which focuses on the efficient and user-friendly analysis, visual inspection and easy manual editing of resequencing microarray data. Both algorithms are implemented as plugins for ResqMi. ResqMi is available at http://www-ps.informatik.uni-tuebingen.de/resqmi