@phdthesis{Kuespert2014,
  author    = {K{\"u}spert, Maritta},
  title     = {Untersuchung zur Rolle des La-verwandten Proteins LARP4B im mRNA-Metabolismus},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-107490},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2014},
  abstract  = {Eukaryotische messenger-RNAs (mRNAs) m{\"u}ssen diverse Prozessierungsreaktionen durchlaufen, bevor sie der Translationsmaschinerie als Template f{\"u}r die Proteinbiosynthese dienen k{\"o}nnen. Diese Reaktionen beginnen bereits kotranskriptionell und schließen das Capping, das Spleißen und die Polyadenylierung ein. Erst nach dem die Prozessierung abschlossen ist, kann die reife mRNA ins Zytoplasma transportiert und translatiert werden. mRNAs interagieren in jeder Phase ihres Metabolismus mit verschiedenen trans-agierenden Faktoren und bilden mRNA-Ribonukleoproteinkomplexe (mRNPs) aus. Dieser „mRNP-Code" bestimmt das Schicksal jeder mRNA und reguliert dadurch die Genexpression auf posttranskriptioneller Ebene. F{\"u}r das La-verwandte Protein LARP4B (La-related protein 4B) wurde k{\"u}rzlich eine direkte Interaktion mit den Translationsfaktoren PABPC1 (poly(A) binding protein, cytoplasmic 1) und RACK1 (receptor for activated C kinase) gefunden. Diese Befunde sowie die Assoziation mit aktiv translatierenden Ribosomen l{\"a}sst vermuten, dass LARP4B zum mRNP-Code beitr{\"a}gt. Die Dom{\"a}nenstruktur des Proteins legt dar{\"u}ber hinaus nahe, dass LARP4B direkt mRNAs bindet. Um einen Einblick in die Funktion von LARP4B und seiner in vivo RNA-Bindungspartner zu erhalten, wurde die mRNA-Assoziation transkriptomweit mit Hilfe von PAR-CLIP (Photoactivatable-Ribonucleoside-Enhanced Crosslinking and Immunoprecipitation)-Experimenten bestimmt. Diese Daten zeigten, dass LARP4B ein spezifisches Set an zellul{\"a}ren mRNAs {\"u}ber Sequenzbereiche in deren 3'-untranslatierten Regionen bindet. Die bioinformatische Auswertung der PAR-CLIP-Daten identifizierte ein LARP4B-Bindemotiv, welches durch in vitro Bindungsstudien validiert werden konnte. Dar{\"u}ber hinaus belegten pSILAC (pulsed stable isotope labeling with amino acids in cell culture)-Experimente und eine transkriptomweite Analyse der mRNA-Level, dass LARP4B die Expression der Ziel-mRNAs beeinflusst, indem es die Stabilit{\"a}t der gebundenen Transkripte erh{\"o}ht. LARP4B konnte somit als positiver Faktor der eukaryotischen Genexpression identifiziert werden.},
  subject      = {Messenger-RNS},
  language  = {de}
}
@phdthesis{Schmalbach2014,
  author    = {Schmalbach, Katja},
  title     = {Identification of factors influencing 17beta-estradiol metabolism in female mammary gland},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-109300},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2014},
  abstract  = {The female sex hormone 17beta-estradiol, produced naturally in the body, seems to play an important role in the development of breast cancer, since (i) it can be activated to reactive metabolites, which are known to damage DNA and (ii) the stimulation of the estrogen receptor alpha by 17beta-estradiol enhances cell proliferation. Both processes together increase mutation frequency and subsequently lead to transformation of epithelial cells. Therefore, the aim of this work was to characterize the influence of polymorphisms and lifestyle factors on 17beta-estradiol metabolism in normal mammary gland tissue. [...] In sum, the tissue specific 17beta-estradiol metabolism was described in mammary gland tissue homogenate, whereas differences in proliferation of epithelial cells were only reflected in isolated epithelial cells. Factors associated with breast cancer risk (age, BMI and age-related changes in mammary gland morphology) were shown to affect 17beta-estradiol tissue levels. The 17beta-estradiol mediated genotoxicity was evaluated using bioinformatically calculated DNA adduct fluxes, which were predominately influenced by individual mRNA patterns rather than individual genotypes and (DNA adduct fluxes) were correlated with known breast cancer risk factors (age, parity, BMI and polymorphism of glutathione-S-transferase theta 1).},
  subject      = {Milchdr{\"u}se},
  language  = {en}
}
@phdthesis{ZeeshangebMajeed2014,
  author    = {Zeeshan [geb. Majeed], Saman},
  title     = {Implementation of Bioinformatics Methods for miRNA and Metabolic Modelling},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-102900},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2014},
  abstract  = {Dynamic interactions and their changes are at the forefront of current research in bioinformatics and systems biology. This thesis focusses on two particular dynamic aspects of cellular adaptation: miRNA and metabolites. miRNAs have an established role in hematopoiesis and megakaryocytopoiesis, and platelet miRNAs have potential as tools for understanding basic mechanisms of platelet function. The thesis highlights the possible role of miRNAs in regulating protein translation in platelet lifespan with relevance to platelet apoptosis and identifying involved pathways and potential key regulatory molecules. Furthermore, corresponding miRNA/target mRNAs in murine platelets are identified. Moreover, key miRNAs involved in aortic aneurysm are predicted by similar techniques. The clinical relevance of miRNAs as biomarkers, targets, resulting later translational therapeutics, and tissue specific restrictors of genes expression in cardiovascular diseases is also discussed. In a second part of thesis we highlight the importance of scientific software solution development in metabolic modelling and how it can be helpful in bioinformatics tool development along with software feature analysis such as performed on metabolic flux analysis applications. We proposed the "Butterfly" approach to implement efficiently scientific software programming. Using this approach, software applications were developed for quantitative Metabolic Flux Analysis and efficient Mass Isotopomer Distribution Analysis (MIDA) in metabolic modelling as well as for data management. "LS-MIDA" allows easy and efficient MIDA analysis and, with a more powerful algorithm and database, the software "Isotopo" allows efficient analysis of metabolic flows, for instance in pathogenic bacteria (Salmonella, Listeria). All three approaches have been published (see Appendices).},
  subject      = {miRNS},
  language  = {en}
}