@phdthesis{Wangorsch2013,
  author    = {Wangorsch, Gaby},
  title     = {Mathematical modeling of cellular signal transduction},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-87746},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2013},
  abstract  = {A subtly regulated and controlled course of cellular processes is essential for the healthy functioning not only of single cells, but also of organs being constituted thereof. In return, this entails the proper functioning of the whole organism. This implies a complex intra- and inter-cellular communication and signal processing that require equally multi-faceted methods to describe and investigate the underlying processes. Within the scope of this thesis, mathematical modeling of cellular signaling finds its application in the analysis of cellular processes and signaling cascades in different organisms. ...},
  subject      = {Mathematische Modellierung},
  language  = {en}
}
@phdthesis{Robubi2007,
  author    = {Robubi, Armin},
  title     = {RAF Kinases: Pathway, Modulation and Modeling},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-26953},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2007},
  abstract  = {The Ras/RAF/MEK/ERK cascade is a central cellular signal transduction pathway involved in cell proliferation, differentiation, and survival where RAF kinases are pivotal kinases implicated in cancer. The development of specific irreversible kinase inhibitors is a rewarding but difficult aim. CI-1033 was developed to irreversibly inhibit erbB receptor tyrosine kinases by reacting to the Cys113 residue (p38alpha MAP kinase numbering) of the kinase domain. In this study we tried a similar approach to target the RAF oncoproteins which posses a similar cysteine at position 108 in the hinge region between the small n-lobe and the large c-lobe of the kinase domain. A novel synthetic approach including a lyophilization step allowed us the synthesis of a diphenyl urea compound with an epoxide moiety (compound 1). Compound 1 possessed inhibitory activity in vitro. However our time kinetics experiments and mass spectroscopic studies clearly indicate that compound 1 does not react covalently with the cysteine residue in the hinge region. Moreover, in cell culture experiments, a strong activation of the RAF signaling pathway was observed, an effect which is known from several other RAF kinase inhibitors and is here reported for the first time for a diphenyl urea compound, to which the clinically used unspecific kinase inhibitor BAY 43-9006 (Sorafinib, Nexavar) belongs. Although activation was apparently independent on B- and C-RAF hetero-oligomerization in vitro, in vivo experiments support such a mechanism as the activation did not occur in starved knockout cells lacking either B-RAF or C-RAF. Furthermore, we developed a mathematical model of the Ras/RAF/MEK/ERK cascade demonstrating how stimuli induce different signal patterns and thereby different cellular responses, depending on cell type and the ratio between B-RAF and C-RAF. Based on biochemical data for activation and dephosphorylation, we set up differential equations for a dynamical model of the Ras/RAF/MEK/ERK cascade. We find a different signaling pattern and response result for B-RAF (strong activation, sustained signal) and C-RAF (steep activation, transient signal). We further support the significance of such differential modulatory signaling by showing different RAF isoform expression in various cell lines and experimental testing of the predicted kinase activities in B-RAF, C-RAF as well as mutated versions. Additionally the effect of the tumor suppressor DiRas3 (also known as Noey2 or ARHI) on RAF signaling was studied. I could show that DiRas3 down-regulates the mitogenic pathway by inhibition of MEK, a basis for a refined model of the Ras/RAF/MEK/ERK cascade.},
  subject      = {Systembiologie},
  language  = {en}
}
@phdthesis{Nilla2012,
  author    = {Nilla, Jaya Santosh Chakravarthy},
  title     = {An Integrated Knowledgebase and Network Analysis Applied on Platelets and Other Cell Types},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-85730},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2012},
  abstract  = {Systems biology looks for emergent system effects from large scale assemblies of molecules and data, for instance in the human platelets. However, the computational efforts in all steps before such insights are possible can hardly be under estimated. In practice this involves numerous programming tasks, the establishment of new database systems but as well their maintenance, curation and data validation. Furthermore, network insights are only possible if strong algorithms decipher the interactions, decoding the hidden system effects. This thesis and my work are all about these challenges. To answer this requirement, an integrated platelet network, PlateletWeb, was assembled from different sources and further analyzed for signaling in a systems biological manner including multilevel data integration and visualization. PlateletWeb is an integrated network database and was established by combining the data from recent platelet proteome and transcriptome (SAGE) studies. The information on protein-protein interactions and kinase-substrate relationships extracted from bioinformatical databases as well as published literature were added to this resource. Moreover, the mass spectrometry-based platelet phosphoproteome was combined with site-specific phosphorylation/ dephosphorylation information and then enhanced with data from Phosphosite and complemented by bioinformatical sequence analysis for site-specific kinase predictions. The number of catalogued platelet proteins was increased by over 80\% as compared to the previous version. The integration of annotations on kinases, protein domains, transmembrane regions, Gene Ontology, disease associations and drug targets provides ample functional tools for platelet signaling analysis. The PlateletWeb resource provides a novel systems biological workbench for the analysis of platelet signaling in the functional context of protein networks. By comprehensive exploration, over 15000 phosphorylation sites were found, out of which 2500 have the corresponding kinase associations. The network motifs were also investigated in this anucleate cell and characterize signaling modules based on integrated information on phosphorylation and protein-protein interactions. Furthermore, many algorithmic approaches have been introduced, including an exact approach (heinz) based on integer linear programming. At the same time, the concept of semantic similarities between two genes using Gene Ontology (GO) annotations has become an important basis for many analytical approaches in bioinformatics. Assuming that a higher number of semantically similar gene functional annotations reflect biologically more relevant interactions, an edge score was devised for functional network analysis. Bringing these two approaches together, the edge score, based on the GO similarity, and the node score, based on the expression of the proteins in the analyzed cell type (e.g. data from proteomic studies), the functional module as a maximum-scoring sub network in large protein-protein interaction networks was identified. This method was applied to various proteome datasets (different types of blood cells, embryonic stem cells) to identify protein modules that functionally characterize the respective cell type. This scalable method allows a smooth integration of data from various sources and retrieves biologically relevant signaling modules.},
  subject      = {Systembiologie},
  language  = {en}
}
@phdthesis{Liang2009,
  author    = {Liang, Chunguang},
  title     = {Tools for functional genomics applied to Staphylococci, Listeriae, Vaccinia virus and other organisms},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-48051},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2009},
  abstract  = {Genome sequence analysis A combination of genome analysis application has been established here during this project. This offers an efficient platform to interactively compare similar genome regions and reveal loci differences. The genes and operons can be rapidly analyzed and local collinear blocks (LCBs) categorized according to their function. The features of interests are parsed, recognized, and clustered into reports. Phylogenetic relationships can be readily examined such as the evolution of critical factors or a certain highly-conserved region. The resulting platform-independent software packages (GENOVA and inGeno), have been proven to be efficient and easy to handle in a number of projects. The capabilities of the software allowed the investigation of virulence factors, e.g., rsbU, strains' biological design, and in particular pathogenicity feature storage and management. We have successfully investigated the genomes of Staphylococcus aureus strains (COL, N315, 8325, RN1HG, Newman), Listeria spp. (welshimeri, innocua and monocytogenes), E.coli strains (O157:H7 and MG1655) and Vaccinia strains (WR, Copenhagen, Lister, LIVP, GLV-1h68 and parental strains). Metabolic network analysis Our YANAsquare package offers a workbench to rapidly establish the metabolic network of such as Staphylococcous aureus bacteria in genome-scale size as well as metabolic networks of interest such as the murine phagosome lipid signalling network. YANAsquare recruits reactions from online databases using an integrated KEGG browser. This reduces the efforts in building large metabolic networks. The involved calculation routines (METATOOL-derived wrapper or native Java implementation) readily obtain all possible flux modes (EM/EP) for metabolite fluxes within the network. Advanced layout algorithms visualize the topological structure of the network. In addition, the generated structure can be dynamically modified in the graphic interface. The generated network as well as the manipulated layout can be validated and stored (XML file: scheme of SBML level-2). This format can be further parsed and analyzed by other systems biology software, such as CellDesigner. Moreover, the integrated robustness-evaluation routine is able to examine the synthesis rates affected by each single mutation throughout the whole network. We have successfully applied the method to simulate single and multiple gene knockouts, and the affected fluxes are comprehensively revealed. Recently we applied the method to proteomic data and extra-cellular metabolite data of Staphylococci, the physiological changes regarding the flux distribution are studied. Calculations at different time points, including different conditions such as hypoxia or stress, show a good fit to experimental data. Moreover, using the proteomic data (enzyme amounts) calculated from 2D-Gel-EP experiments our study provides a way to compare the fluxome and the enzyme expression. Oncolytic vaccinia virus (VACV) We investigated the genetic differences between the de novo sequence of the recombinant oncolytic GLV-1h68 and other related VACVs, including function predictions for all found genome differences. Our phylogenetic analysis indicates that GLV-1h68 is closest to Lister strains but has lost several ORFs present in its parental LIVP strain, including genes encoding CrmE and a viral Golgi anti-apoptotic protein, v-GAAP. Functions of viral genes were either strain-specific, tissue-specific or host-specific comparing viral genes in the Lister, WR and COP strains. This helps to rationally design more optimized oncolytic virus strains to benefit cancer therapy in human patients. Identified differences from the comparison in open reading frames (ORFs) include genes for host-range selection, virulence and immune modulation proteins, e.g. ankyrin-like proteins, serine proteinase inhibitor SPI-2/CrmA, tumor necrosis factor (TNF) receptor homolog CrmC, semaphorin-like and interleukin-1 receptor homolog proteins. The contribution of foreign gene expression cassettes in the therapeutic and oncolytic virus GLV-1h68 was studied, including the F14.5L, J2R and A56R loci. The contribution of F14.5L inactivation to the reduced virulence is demonstrated by comparing the virulence data of GLV-1h68 with its F14.5L-null and revertant viruses. The comparison suggests that insertion of a foreign gene expression cassette in a nonessential locus in the viral genome is a practical way to attenuate VACVs, especially if the nonessential locus itself contains a virulence gene. This reduces the virulence of the virus without compromising too much the replication competency of the virus, the key to its oncolytic activity. The reduced pathogenicity of GLV-1h68 was confirmed by our experimental collaboration partners in male mice bearing C6 rat glioma and in immunocompetent mice bearing B16-F10 murine melanoma. In conclusion, bioinformatics and experimental data show that GLV-1h68 is a promising engineered VACV variant for anticancer therapy with tumor-specific replication, reduced pathogenicity and benign tissue tropism.},
  subject      = {Genanalyse},
  language  = {en}
}
@phdthesis{Classen2021,
  author    = {Claßen, Alexandra},
  title     = {The ERK-cascade in the pathophysiology of cardiac hypertrophy},
  doi       = {10.25972/OPUS-22966},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-229664},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2021},
  abstract  = {ERK1/2 are known key players in the pathophysiology of heart failure, but the members of the ERK cascade, in particular Raf1, can also protect the heart from cell death and ischemic injury. An additional autophosphorylation (ERK1 at Thr208, ERK2 at Thr188) empowers ERK1/2 translocation to the nucleus and phosphorylation of nuclear targets which take part in the development of cardiac hypertrophy. Thereby, targeting this additional phosphorylation is a promising pharmacological approach. In this thesis, an in silico model of ERK cascade in the cardiomyocyte is introduced. The model is a semi-quantitive model and its behavior was tested with different softwares (SQUAD and CellNetAnalyzer). Different phosphorylation states of ERK1/2 as well as different stimuli can be reproduced. The different types of stimuli include hypertrophic as well as non-hypertrophic stimuli. With the introduced in-silico model time courses and synergistic as well as antagonistic receptor stimuli combinations can be predicted. The simulated time courses were experimentally validated. SQUAD was mainly used to make predictions about time courses and thresholds, whereas CNA was used to analyze steady states and feedback loops. Furthermore, new targets of ERK1/2 which partially contribute, also in the formation of cardiac hypertrophy, were identified and the most promising of them were illuminated. Important further targets are Caspase 8, GAB2, Mxi-2, SMAD2, FHL2 and SPIN90. Cardiomyocyte gene expression data sets were analyzed to verify involved components and to find further significantly altered genes after induced hypertrophy with TAC (transverse aortic constriction). Changes in the ultrastructure of the cardiomyocyte are the final result of induced hypertrophy.},
  subject      = {Herzhypertrophie},
  language  = {en}
}
@phdthesis{Boyanova2012,
  author    = {Boyanova, Desislava Veselinova},
  title     = {Systems biological analysis of the platelet proteome and applications of functional module search in proteome networks},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-72165},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2012},
  abstract  = {Recent development of proteomic approaches and generation of large-scale proteomic datasets calls for new methods for biological interpretation of the obtained results. Systems biological approaches such as integrated network analysis and functional module search have become an essential part of proteomic investigation. Proteomics is especially applied in anucleate cells such as platelets. The underlying molecular mechanisms of platelet activation and their pharmacological modulation are of immense importance for clinical research. Advances in platelet proteomics have provided a large amount of proteomic data, which has not yet been comprehensively investigated in a systems biological perspective. To this end, I assembled platelet specific data from proteomic and transcriptomic studies by detailed manual curation and worked on the generation of a comprehensive human platelet repository for systems biological analysis of platelets in the functional context of integrated networks (PlateletWeb) (http:/PlateletWeb.bioapps.biozentrum.uni-wuerzburg.de). I also added platelet-specific experimentally validated phosphorylation data and generated kinase predictions for 80\% of the newly identified platelet phosphosites. The combination of drug, disease and pathway information with phosphorylation and interaction data makes this database the first integrative platelet platform available for platelet research. PlateletWeb contains more than 5000 platelet proteins, which can also be analyzed and visualized in a network context, allowing identification of all major signaling modules involved in platelet activation and inhibition. Using the wealth of integrated data I performed a series of platelet-specific analyses regarding the platelet proteome, pathways, drug targets and novel platelet phosphorylation events involved in crucial signaling events. I analyzed the statistical enrichment of known pathways for platelet proteins and identified endocytosis as a highly represented pathway in platelets. Further results revealed that highly connected platelet proteins are more often targeted by drugs. Using integrated network analysis offered by PlateletWeb, I analyzed the crucial activation signaling pathway of adenosine diphosphate (ADP), visualizing how the signal flow from receptors to effectors is maintained. My work on integrin inside-out signaling was also based on the integrated network approach and examined new platelet-specific phosphorylation sites and their regulation using kinase predictions. I generated hypothesis on integrin signaling, by investigating the regulation of Ser269 phosphorylation site on the docking protein 1 (DOK1). This phosphorylation site may influence the inhibiting effect of DOK1 on integrin a2bb3. Extending the integrated network approach to further cell lines, I used the assembled human interactome information for the analysis of functional modules in cellular networks. The investigation was performed with a previously developed module detection algorithm, which finds maximum-scoring subgraphs in transcriptomic datasets by using assigned values to the network nodes. We extended the algorithm to qualitative proteomic datasets and enhanced the module search by adding functional information to the network edges to concentrate the solution onto modules with high functional similarity. I performed a series of analyses to validate its performance in small-sized (virus-infected gastric cells) and medium-sized networks (human lymphocytes). In both cases the algorithm extracted characteristic modules of sample proteins with high functional similarity. The functional module search is especially useful in site-specific phosphoproteomic datasets, where kinase regulation of the detected sites is often sparse or lacking. Therefore, I used the module detection algorithm in quantitative phosphoproteomic datasets. In a platelet phosphorylation dataset, I presented a pipeline for network analysis of detected phosphorylation sites. In a second approach, the functional module detecting algorithm was used on a phosphoproteome network of human embryonic stem cells, in which nodes represented the maximally changing phosphorylation sites in the experiment. Additional kinases from the human phosphoproteome in PlateletWeb were included to the network to investigate the regulation of the signal flow. Results indicated important phosphorylation sites and their upstream kinases and explained changes observed in embryonic stem cells during differentiation. This work presents novel approaches for integrated network analysis in cells and introduces for the first time a systematic biological investigation of the human platelet proteome based on the platelet-specific knowledge base PlateletWeb. The extended methods for optimized functional module detection offer an invaluable tool for exploring proteomic datasets and covering gaps in complex large-scale data analysis. By combining exact module detection approaches with functional information data between interacting proteins, characteristic functional modules with high functional resemblance can be extracted from complex datasets, thereby focusing on important changes in the observed networks.},
  subject      = {Netzwerkanalyse},
  language  = {en}
}