@phdthesis{Zeeshan2012,
  author    = {Zeeshan, Ahmed},
  title     = {Bioinformatics Software for Metabolic and Health Care Data Management},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-73926},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2012},
  abstract  = {Computer Science approaches (software, database, management systems) are powerful tools to boost research. Here they are applied to metabolic modelling in infections as well as health care management. Starting from a comparative analysis this thesis shows own steps and examples towards improvement in metabolic modelling software and health data management. In section 2, new experimental data on metabolites and enzymes induce high interest in metabolic modelling including metabolic flux calculations. Data analysis of metabolites, calculation of metabolic fluxes, pathways and their condition-specific strengths is now possible by an advantageous combination of specific software. How can available software for metabolic modelling be improved from a computational point of view? A number of available and well established software solutions are first discussed individually. This includes information on software origin, capabilities, development and used methodology. Performance information is obtained for the compared software using provided example data sets. A feature based comparison shows limitations and advantages of the compared software for specific tasks in metabolic modeling. Often found limitations include third party software dependence, no comprehensive database management and no standard format for data input and output. Graphical visualization can be improved for complex data visualization and at the web based graphical interface. Other areas for development are platform independency, product line architecture, data standardization, open source movement and new methodologies. The comparison shows clearly space for further software application development including steps towards an optimal user friendly graphical user interface, platform independence, database management system and third party independence especially in the case of desktop applications. The found limitations are not limited to the software compared and are of course also actively tackled in some of the most recent developments. Other improvements should aim at generality and standard data input formats, improved visualization of not only the input data set but also analyzed results. We hope, with the implementation of these suggestions, metabolic software applications will become more professional, cheap, reliable and attractive for the user. Nevertheless, keeping these inherent limitations in mind, we are confident that the tools compared can be recommended for metabolic modeling for instance to model metabolic fluxes in bacteria or metabolic data analysis and studies in infection biology. ...},
  subject      = {Stoffwechsel},
  language  = {en}
}
@phdthesis{Paxian2012,
  author    = {Paxian, Andreas},
  title     = {Future changes in climate means and extremes in the Mediterranean region deduced from a regional climate model},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-72155},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2012},
  abstract  = {The Mediterranean area reveals a strong vulnerability to future climate change due to a high exposure to projected impacts and a low capacity for adaptation highlighting the need for robust regional or local climate change projections, especially for extreme events strongly affecting the Mediterranean environment. The prevailing study investigates two major topics of the Mediterranean climate variability: the analysis of dynamical downscaling of present-day and future temperature and precipitation means and extremes from global to regional scale and the comprehensive investigation of temperature and rainfall extremes including the estimation of uncertainties and the comparison of different statistical methods for precipitation extremes. For these investigations, several observational datasets of CRU, E-OBS and original stations are used as well as ensemble simulations of the regional climate model REMO driven by the coupled global general circulation model ECHAM5/MPI-OM and applying future greenhouse gas (GHG) emission and land degradation scenarios.},
  subject      = {Mittelmeerraum},
  language  = {en}
}