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  • GBV  (30)
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  • 11
    UID:
    (DE-627)1756648026
    Format: VII, 122, xviii Blätter , Illustrationen, Diagramme
    Content: In dieser Arbeit wurde durch intensive Literatur- und Datenbankrecherche ein Protein-Protein/Gen-Interaktionsnetzwerk um den Transkriptionsfaktor E2F1 herum erstellt. Er ist Schlüsselfaktor für die epithelial-mesenchymale Transition (EMT), Voraussetzung für die Metastasierung. Eine anschließende bioinformatische Analyse identifizierte tumorspezifische Signaturen der E2F1-vermittelten EMT, welche experimentell und anhand von Patientendaten validiert wurden. Gemeinsame Zielgene des näher untersuchten E2F1-TGFβ-Interaktoms bieten mögliche Therapieziele für Krebspatienten.〈ger〉
    Content: By intensive literature and database research we constructed a comprehensive map of interactions around the transcription factor E2F1, a key driver of the epithelial-mesenchymal transition (EMT) as a prerequisite for metastasis. The subsequent bioinformatics analysis of this map lead to the identification of tumour-specific molecular signatures of E2F1-driven EMT. These signatures were validated experimentally as well as on patient data. Common transcriptional targets of the investigated E2F1-TGFβ co-regulome might be suitable therapeutic targets for cancer patients.〈eng〉
    Note: Für nähere Informationen zur bioinformatischen Analyse des E2F1-Netzwerkes, siehe die parallele Doktorarbeit von Faiz M. Khan: "An integrated workflow to study large-scale biochemical networks" der Fakultät für Informatik und Elektrotechnik der Universität Rostock. Teile beider Doktorarbeiten wurden publiziert unter: "Unraveling a tumor type-specific regulatory core underlying E2F1-mediated epithelial-mesenchymal transition to predict receptor protein signatures" Khan FM, Marquardt S, Gupta SK, Knoll S, Schmitz U, Spitschak A, Engelmann D, Vera J, Wolkenhauer O, Pützer BM. Nat Commun. 2017 Aug 4;8(1):198. doi: 10.1038/s41467-017-00268-2 , GutachterInnen: Prof. Dr. med. Dr. rer. nat. Brigitte M. Pützer (Universitätsmedizin Rostock, Institut für Experimentelle Gentherapie und Tumorforschung), Prof. Dr. rer. nat. Lars Kaderali (Universität Greifswald, Institut für Bioinformatik) , Dissertation Universität Rostock 2020
    Additional Edition: Erscheint auch als Online-Ausgabe Marquardt, Stephan, 1981 - Etablierung des E2F1-Interaktoms metastasierungsrelevanter Faktoren durch Integration bioinformatischer und experimenteller Methoden Rostock : Universität, 2019
    Language: German
    Subjects: Biology
    RVK:
    Keywords: Genregulation ; Transkriptionsfaktor ; Protein-Protein-Wechselwirkung ; Bioinformatik ; Hochschulschrift
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  • 12
    UID:
    (DE-627)1869955676
    Format: 80 Blätter , Illustrationen (farbig), Diagramme (farbig)
    Note: Literaturverzeichnis: Blatt 26-36. - Literaturangaben , Dissertation Universitätsmedizin der Universität Greifswald 2023
    Additional Edition: Erscheint auch als Online-Ausgabe Holzscheck, Nicholas Jonas, 1991 - Analyse intrinsischer und extrinsischer Aspekte von Hautalterung in hochdimensionalen biologischen Daten mittels bioinformatischer und maschineller Lernmethoden Greifswald, 2023
    Language: English
    Keywords: Bioinformatik ; Maschinelles Lernen ; Haut ; Alterung ; Hochschulschrift
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  • 13
    UID:
    (DE-627)186812052X
    Format: 1 Online-Ressource (PDF-Datei: 173 Seiten, 28972 Kilobyte) , Illustrationen (farbig), Diagramme (farbig)
    Content: Coxsackievirus B3, Dengue virus, Enterovirus, Hepatitis C virus, Mathematical modeling, Modeling of immune response, Modeling of infectious diseases, Viral dynamics, Virus-host interaction
    Content: Plus‐strand RNA [(+)RNA] viruses are the largest group of viruses, medically highly relevant human pathogens, and are a socio‐economic burden. The current global pandemic of the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) shows how a virus has been rapidly spreading around the globe and that– without an antiviral treatment– virus trans mission is solely dependent on human behavior. However, other (+)RNA viruses such as rhino‐, noro‐, dengue‐ (DENV), Zika, and hepatitis C virus (HCV) are constantly spreading and expanding geographically. As in the case of hepatitis C, since its first identification in the 1970s, it took more than 30 years to understand the HCV structure, genome organiza t ion, life cycle, and virus‐host interplay leading to the cure of a chronic and life‐threatening disease. However, no vaccination or antiviral treatment exists for most (+)RNA viruses. Con sequently, a precise and comprehensive analysis of the viruses, their life cycles, and parasitic interactions with their hosts remains an important field of research. In the presented thesis, we use mathematical modeling to study the life cycles of (+)RNA viruses. We analyze replication strategies of closely related (+)RNA viruses, namely HCV, DENV, and coxsackievirus B3 (CVB3), to compare their life cycles in the presence and ab sence of the host’s immune response and antiviral drug treatment and consider different viral spreading mechanisms. Host dependency factors shape the viral life cycle, contribut ing to permissiveness and replication efficiency. Our mathematical models predicted that host dependency factors, such as ribosomes, and thus the virus’ ability to hijack the host cell’s translation machinery play an essential role in the viral genome replication efficiency. Furthermore, our mathematical model suggested that the availability of ribosomes in the vi ral life cycle is a crucial factor in disease outcome: the development of an acute or chronic disease. Even though the host developed strategies to attack the virus, e.g., by degrading the viral genome, blocking the viral protein production, and preventing viral spread, viruses found strategies to countermeasure those so‐called host restriction factors derived from the immune system. Our mathematical models predicted that DENV might be highly effective in blocking the cell’s attempts to recognize the invader. Moreover, we found ongoing HCV RNAreplication even with highly effective antiviral drugs that block processes in the viral life cycle. Furthermore, we found alternative pathways of infection spread, e.g., by HCV RNA carrying exosomes, which may be a possible explanation for reported plasma HCV RNA at the end of treatment, found in a subset of patients. Hence, the mathematical models presented in this thesis provide valuable tools to study the viral replication mechanism in detail. Even though being a simplification of reality, our model predictions confirm and explain known and suggest novel biological mechanisms. In the pre sented thesis, I will summarize and discuss key findings and contextualize model predictions in the broader scientific literature to improve our understanding of the viral dynamics and the virus‐host interplay.
    Note: Literaturverzeichnis: Seite 145-155. - Literaturangaben , Dissertation Universitätsmedizin der Universität Greifswald 2023
    Additional Edition: Erscheint auch als Druck-Ausgabe Zitzmann, Carolin, 1987 - Mathematical modeling of Plus-strand RNA virus replication Greifswald, 2023
    Language: English
    Keywords: Hepatitis-C-Virus ; Denguefieber ; Enteroviren ; Infektionskrankheit ; Immunreaktion ; Mathematische Modellierung ; Viren ; Hochschulschrift
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  • 14
    UID:
    (DE-627)1868116603
    Format: xv, 155 Seiten , Illustrationen (farbig), Diagramme (farbig)
    Note: Literaturverzeichnis: Seite 145-155. - Literaturangaben , Dissertation Universitätsmedizin der Universität Greifswald 2023
    Additional Edition: Erscheint auch als Online-Ausgabe Zitzmann, Carolin, 1987 - Mathematical modeling of Plus-strand RNA virus replication Greifswald, 2023
    Language: English
    Keywords: Hepatitis-C-Virus ; Denguefieber ; Enteroviren ; Infektionskrankheit ; Immunreaktion ; Mathematische Modellierung ; Viren ; Hochschulschrift
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  • 15
    UID:
    (DE-627)1795348127
    Format: v, 143 Seiten , Illustrationen (teilweise farbig), Diagramme (teilweise farbig)
    Note: Literaturverzeichnis: Seite 115-123. - Literaturangaben , Dissertation Mathematisch-Naturwissenschaftliche Fakultät der Universität Greifswald 2022
    Additional Edition: Erscheint auch als Online-Ausgabe Becker, Ann-Kristin, 1993 - Discovering latent structure in high-dimensional healtcare data Greifswald, 2021
    Language: English
    Keywords: Datenstruktur ; Maschinelles Lernen ; Gesundheitswesen ; Hochschulschrift
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  • 16
    UID:
    (DE-627)1795981156
    Format: 1 Online-Ressource (PDF-Datei: 153 Seiten, 10722 Kilobyte) , Illustrationen (teilweise farbig), Diagramme (teilweise farbig)
    Content: Data Science, Bayes-Netz, Dimensionsreduktion, Fettleber, Cluster, Hierarchie, Interpretability, Interpretable Machine Learning, Latent Structure
    Content: This cumulative thesis describes contributions to the field of interpretable machine learning in the healthcare domain. Three research articles are presented that lie at the intersection of biomedical and machine learning research. They illustrate how incorporating latent structure can provide a valuable compression of the information hidden in complex healthcare data. Methodologically, this thesis gives an overview of interpretable machine learning and the discovery of latent structure, including clusters, latent factors, graph structure, and hierarchical structure. Different workflows are developed and applied to two main types of complex healthcare data (cohort study data and time-resolved molecular data). The core result builds on Bayesian networks, a type of probabilistic graphical model. On the application side, we provide accurate predictive or discriminative models focusing on relevant medical conditions, related biomarkers, and their interactions.
    Note: Literaturverzeichnis: Seite 115-123. - Literaturangaben , Dissertation Mathematisch-Naturwissenschaftliche Fakultät der Universität Greifswald 2022
    Additional Edition: Erscheint auch als Druck-Ausgabe Becker, Ann-Kristin, 1993 - Discovering latent structure in high-dimensional healtcare data Greifswald, 2021
    Language: English
    Keywords: Datenstruktur ; Maschinelles Lernen ; Gesundheitswesen ; Hochschulschrift
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  • 17
    UID:
    (DE-627)1852619406
    Format: XII, 167 Seiten , Diagramme (farbig) , 1 DVD
    Note: Literaturverzeichnis: Seite 123-146 , Dissertation Mathematisch-Naturwissenschaftliche Fakultät der Universität Greifswald 2023
    Additional Edition: Erscheint auch als Online-Ausgabe Kleimeier, Dana Mathematical modeling of the Tryptophan Metabolism During 1-Methyltryptophan administration in pigs in the face of infection Greifswald, 2023
    Language: English
    Keywords: Tryptophan ; Metabolismus ; Mathematische Modellierung ; Modellierung ; Schwein ; Infektion ; Hochschulschrift
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  • 18
    UID:
    (DE-627)186027448X
    Format: 1 Online-Ressource (PDF-Datei: 181 Seiten, 22002 Kilobyte) , Diagramme (farbig)
    Content: Modeling Infection, Modeling Tryptophan-Metabolism, In-Host Modeling, Modeling in Pigs, Modeling of Infectious Diseases,Tryptophan-Metabolism
    Content: Gram-negative bacteria secrete lipopolysaccharides (LPS), leading to a host immune response of proinflammatory cytokine secretion. Those proinflammatory cytokines are TNF-α and IFN-γ, which induce the production of indoleamine 2,3-dioxygenase (IDO). IDO production is increased during severe sepsis, and septic shock. High IDO evels are associated with increased mortality.This enzyme catalyzes the degradation of tryptophan (TRP) to kynurenine (KYN) along the kynurenine pathway (KP). KYN is further degraded to kynurenic acid (KYNA). Increased IDO levels accompany with increased levels of KYNA, which is associated with immunoparalysis. Due to its central role, the KP is a potential target of therapeutic intervention. The degradation of TRP to KYN by IDO was intervened by 1-Methyltryptophan (1-MT), which is assumed to inhibit IDO. By administering 1-MT, the survival of 1-MT-treated mice suffering from sepsis increased compared to mice not treated with 1-MT. The levels of downstream metabolites such as KYN and KYNA were expected to be decreased. Surprisingly, in healthy mice and pigs, an increase in KYNA after 1-MT administration was reported. Those unexpected metabolite alterations after 1-MT administration, and the mode of action, were not the focus of recent research. Hence, there is no explanation for KYNA increase, while KYN did not change. This thesis aims to postulate a possible degradation pathway of 1-MT along the KP with the help of ordinary differential equation (ODE) systems. Moreover, the developed ODE models were used to determine the ability of 1-MT to inhibit IDO in vivo. Therefore, a multiplicity of ODE models were developed, including a model of the KP, an extension by lipopolysaccharide (LPS) administration, and 1-MT administration. Moreover, seven ODE models were developed, all considering possible degradation pathways of 1-MT. The most likely degradation pathway was combined with the ODE model of LPS administration, including the inhibitory effects of 1-MT. Those models consist of several dependent equations describing the dynamics of the KP. For each component of the KP, one equation describes the alterations over time. Equations for TRP, KYN, KYNA, and quinolinic acid (QUIN) were developed. Moreover, the alterations of serotonin (SER) were also included. All together belong to the TRP metabolism. They include the degradation of TRP to SER and to KYN, which is further degraded to KYNA and QUIN. Every degradation is catalyzed by an enzyme. Therefore, Michaelis-Menten (MM) equations were used employing the substrate constant Km and the maximal degradation velocity Vmax. To reduce the complexity of parameter calculation, Km values of the different enzymes were fixed to literature values. The remaining parameters of the equations were determined so that the trajectories of the calculated metabolite levels correspond to data. The parameters of different models were determined. To propose a degradation pathway of 1-MT leading to increased KYNA levels, seven models were developed and compared. The most likely model was extended to test whether the inhibitory effects of 1-MT on IDO can be determined. Three different approaches determined the ODE model parameters of the different hypothesis of 1-MT degradation. In the first approach, ODE model parameters were fixed to values fitted to an independent data set. In the second approach, parameters were fitted to a subset of the data set, which was used for simulations of the different hypotheses. The third approach calculated ODE model parameters 100 times without ixed parameters. The parameter set ending up in trajectories of the TRP metabolites, which have the smallest distance to the data, was assumed to be the most likely. The ODE model parameters were fitted to data measured in pigs. Two different experimental models delivered data used in this thesis. The first experimental model activates IDO by LPS administration in pigs. The second one combines the IDO activation by LPS with the administration of 1-MT in pigs. The most likely hypothesis, according to approach 1 was the degradation of 1-MT to KYNA and TRP. For the second data set the most likely one was the direct degradation of 1-MT to KYNA. With approach 2 the most likely degradation pathways were the combination of all degradation pathways and the degradation of 1-MT to TRP and TRP to KYNA. With approach 3 the most likely way of KYNA increase was given by the direct degradation of 1-MT to KYNA. In summary, the three approaches revealed hypothesis 2, the direct degradation of 1-MT to KYNA most frequently. A cell-free assay validated this result. This experiment combined 1-MT or TRP with or without the enzyme kynurenine aminotransferase (KAT). KAT was already shown to degrade TRP directly to KYNA. The levels of TRP, KYN and KYNA were measured. The highest KYNA levels were yielded with an assay adding KAT to 1-MT, corresponding to hypothesis 2. The models describing the inhibitory effects of 1-MT revealed that the model without inhibitory effects of 1-MT on IDO was more likely for all three approaches. The correctness of hypothesis 2 has to be confirmed by further in vitro experiments. It also has to be investigated which reactions promote the degradation of 1-MT to KYNA. The missing inhibitory properties of 1-MT on IDO, determined by the in silico ODE models, align with previous research. It was shown that the saturation of 1-MT was too low, e.g. in pigs, to inhibit IDO efficiently. In this study, the first possible degradation pathway of 1-MT along the KP is proposed. The reliability of the results depends on the quality of the experimental data, and the season, when data were measured. Moreover, the results vary between the different approaches of parameter fitting. Different approaches of parameter fitting have to be included in the analysis to get more evidence for the correctness of the results.
    Note: Literaturverzeichnis: Seite 123-146 , Dissertation Mathematisch-Naturwissenschaftliche Fakultät der Universität Greifswald 2023
    Additional Edition: Erscheint auch als Druck-Ausgabe Kleimeier, Dana Mathematical modeling of the Tryptophan Metabolism During 1-Methyltryptophan administration in pigs in the face of infection Greifswald, 2023
    Language: English
    Keywords: Tryptophan ; Metabolismus ; Mathematische Modellierung ; Modellierung ; Schwein ; Infektion ; Hochschulschrift
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  • 19
    UID:
    (DE-627)1019263849
    Format: iv,164 Seiten , Illustrationen (farbig), Diagramme (farbig)
    Note: Literaturverzeichnis: Seite 147-159 , Dissertation Universitätsmedizin der Ernst-Moritz-Arndt-Universität Greifswald 2017
    Additional Edition: Erscheint auch als Online-Ausgabe Barry, Joanne, 1984 - Mathematical modelling of the HIV life cycle Greifswald, 2017
    Language: English
    Keywords: HIV ; Lebensdauer ; Mathematisches Modell ; Hochschulschrift
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  • 20
    UID:
    (DE-627)1016382251
    Format: 1 Online-Ressource (PDF-Datei: 168 Seiten, 4216 Kilobyte) , Illustrationen (farbig), Diagramme (farbig)
    Content: HAART, HIV, ODEs, life cycle, parameter estimation
    Content: The intracellular life cycle of the human immunodeficiency virus (HIV) is modelled using ordinary differential equations (ODEs). Model parameters are obtained from the literature or fitted to experimental data using parameter estimation procedures. Key steps in the life cycle are inhibited singly and in combination to show the effects on viral replication. The results validate the success of highly active antiretroviral therapy (HAART), and in addition DNA nuclear import is identified as a novel influential therapeutic target.
    Note: Literaturverzeichnis: Seite 147-159 , Dissertation Universitätsmedizin der Ernst-Moritz-Arndt-Universität Greifswald 2017
    Additional Edition: Erscheint auch als Druck-Ausgabe Barry, Joanne, 1984 - Mathematical modelling of the HIV life cycle Greifswald, 2017
    Language: English
    Keywords: HIV ; Lebensdauer ; Mathematisches Modell ; Hochschulschrift
    URL: Volltext  (kostenfrei)
    URL: Volltext  (kostenfrei)
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