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Auflistung nach Autor:in "Schomburg, Dietmar"

1 - 10 von 16
  • Textdokument
    Bioinformatik & Bioinformation – Braunschweig spielt eine führende Rolle
    (40 Jahre Informatik an der Technischen Universität Braunschweig 1972 - 2012, 2012) Schomburg, Dietmar; Wingender, Edgar
    Die Bioinformatik ist eine vor ca. 20 Jahren entstandene wissenschaftlicher Disziplin, die Informatik-Werkzeuge für die Bearbeitung biologischer Fragestellungen einsetzt. Insbesondere die Entwicklung neuer Algorithmen und Datenbanken und die Integration außergewöhnlich umfangreicher Datenmengen spielen hier eine entscheidende Rolle. Die schnelle Entwicklung der Bioinformatik hat die heutige biowissenschaftliche Forschung erst ermöglicht. Bei der Etablierung des Gebietes in Deutschland und im Hinblick auf die internationale Sichtbarkeit hat Braunschweig eine führende Rolle gespielt.
  • Konferenzbeitrag
    CASOP GS: computing intervention strategies targeted at production improvement in genome-scale metabolic networks
    (German Conference on Bioinformatics 2010, 2010) Bohl, Katrin; Figueiredo, Luís F. de; Hädicke, Oliver; Klamt, Steffen; Kost, Christian; Schuster, Stefan; Kaleta, Christoph
    Metabolic engineering aims to improve the production of desired biochemicals and proteins in organisms and therefore, plays a central role in Biotechnology. However, the design of overproducing strains is not straightforward due to the complexity of metabolic and regulatory networks. Thus, theoretical tools supporting the design of such strains have been developed. One particular method, CASOP, uses the set of elementary flux modes (EFMs) of a reaction network to propose strategies for the overproduction of a target compound. The advantage of CASOP over other approaches is that it does not consider a single specific flux distribution within the network but the whole set of possible flux distributions represented by the EFMs of the network. Moreover, its application results not only in the identification of candidate loci that can be knocked out, but additionally proposes overexpression candidates. However, the utilization of CASOP was restricted to small and medium scale metabolic networks so far, since the entire set of EFMs cannot be enumerated in such networks. This work presents an approach that allows to use CASOP even in genome-scale networks. This approach is based on an estimation of the score utilized in CASOP through a sample of EFMs within a genome-scale network. Using EFMs from the genome-scale metabolic network gives a more reliable picture of the metabolic capabilities of an organism required for the design of overproducing strains. We applied our new method to identify strategies for the overproduction of succinate and histidine in Escherichia coli. The succinate case study, in particular, proposes engineering targets which resemble known strategies already applied in E. coli. Availability: Source code and an executable are available upon request.
  • Konferenzbeitrag
    Efficient sequence clustering for RNA-seq data without a reference genome
    (German Conference on Bioinformatics 2010, 2010) Battke, Florian; Körner, Stephan; Hüttner, Steffen; Nieselt, Kay
    New deep-sequencing technologies are applied to transcript sequencing (RNA-seq) for transcriptomic studies. However, current approaches are based on the availability of a reference genome sequence for read mapping. We present Passage, a method for efficient read clustering in the absence of a reference genome that allows sequencing-based comparative transcriptomic studies for currently unsequenced organisms. If the reference genome is available, our method can be used to reduce the computational effort involved in read mapping. Comparisons to microarray data show a correlation of 0.69, proving the validity of our approach.
  • Konferenzbeitrag
    Efficient similarity retrieval of protein binding sites based on histogram comparison
    (German Conference on Bioinformatics 2010, 2010) Fober, Thomas; Mernberger, Marco; Klebe, Gerhard; Hüllermeier, Eyke
    We propose a method for comparing protein structures or, more specifically, protein binding sites using a histogram-based representation that captures important geometrical and physico-chemical properties. In comparison to hitherto existing approaches in structural bioinformatics, especially methods from graph theory and computational geometry, our approach is computationally much more efficient. Moreover, despite its simplicity, it appears to capture and recover functional similarities surprisingly well.
  • Konferenzbeitrag
    Finding optimal sets of enriched regions in chip-seq data
    (German Conference on Bioinformatics 2010, 2010) Gogol-Döring, Andreas; Chen, Wei
    The main challenge when analyzing ChIP-Seq data is the identification of DNA-protein binding sites by finding genomic regions that are enriched with sequencing reads. We present a new tool called qips especially suited for processing ChIP-Seq data containing broader enriched regions. Our tool certainly finds all enriched regions that are not exceeded by higher significant alternatives.
  • Konferenzbeitrag
    Flexible database-assisted graphical representation of metabolic networks for model comparison and the display of experimental data
    (German conference on bioinformatics 2014, 2014) Tillack, Jana; Bende, Melanie; Rother, Michael; Scheer, Maurice; Ulas, Susanne; Schomburg, Dietmar
    Intracellular processes in living organisms are described by metabolic models. A visualization of metabolic models assists interpretation of data or analyzing results. We introduce the visualization tool DaViMM creating personalized graphical representations of metabolic networks for model comparison or the display of measurements or analyzing results. The tool is coupled to a relational database containing graphical network properties like coordinates, which ensure an intuitive network layout. A combination of DaViMM, the graphical database, and available biochemical databases enables an automated creation of metabolic network maps. The flexibility of this combination is demonstrated with some application examples.
  • Editiertes Buch
  • Konferenzbeitrag
    Integrating public databases into an existing protein visualization and modeling program – BRAGI
    (German Conference on Bioinformatics 2004, GCB 2004, 2004) Dieterich, Guido; Kvesic, Marsel; Schomburg, Dietmar; Heinz, Dirk W.; Reichelt, Joachim
    BRAGI offers an efficient visual access to sequence alignment information, 3D alignments and annotated protein structure-function correlations. As a new feature we have mapped information from SWISS-PROT and InterPro to individual entries of the PDB. 3D structural alignments from DALI database were converted to XML files for easy access in BRAGI. BRAGI provides interactive access to NCBI-Blast and the DALI server. Linking and visualizing different types of information hopefully allow the structure function of proteins to be appreciated more intuitively.
  • Konferenzbeitrag
    Learning pathway-based decision rules to classify microarray cancer samples
    (German Conference on Bioinformatics 2010, 2010) Glaab, Enrico; Garibaldi, Jonathan M.; Krasnogor, Natalio
    Despite recent advances in DNA chip technology current microarray gene expression studies are still affected by high noise levels, small sample sizes and large numbers of uninformative genes. Combining microarray data with cellular pathway data by using new integrative analysis methods could help to alleviate some of these problems and provide new biological insights. We present a method for learning simple decision rules for class prediction from pairwise comparisons of cellular pathways in terms of gene set expression levels representing the upand downregulation of pathway members. The procedure generates compact and comprehensible sets of rules, describing changes in the relative ranks of gene expression levels in pairs of pathways across different biological conditions. Re- sults for two large-scale microarray studies, containing samples from prostate cancer and B-cell lymphoma patients, show that the method provides robust and accurate rule sets and new insights on differentially regulated pathway pairs. However, the main benefit of these predictive models in comparison to other classification methods like support vector machines lies not in the attained accuracy levels but in the ease of interpretation and the insights they provide on the relative regulation of cellular pathways in the biological conditions under consideration.
  • Konferenzbeitrag
    METAtarget – extracting key enzymes of metabolic regulation from high-throughput metabolomics data using KEGG REACTION information
    (German Conference on Bioinformatics 2010, 2010) Budczies, Jan; Denkert, Carsten; Müller, Berit M.; Brockmöller, Scarlet F.; Dietel, Manfred; Griffin, Jules L.; Oresic, Matej; Fiehn, Oliver
    METAtarget is a new method for reverse engineering of metabolic networks and the detection of targets enzymes from high-throughput metabolomics data. Using KEGG REACTION, reactant partners are identified and the ratio of product to substrate metabolite concentrations is employed as surrogate for the reaction activity. A test statistics is introduced to assess changes in the activity of reactions between different disease states. In an application of METAtarget to breast cancer, we investigate the dependence of tumor metabolism on hormone receptor status. To this end, we analyze metabolomics data that were generated within the METAcancer project and compare the identified reactions with data on enzyme expression that are obtained from publicly available breast cancer gene expression series. As result, deregulation of key enzymes and reactions of glycolysis, glutaminolysis and other metabolic pathways are detected.