@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}
}
@article{ElKeredySchleyerKoenigetal.2012,
  author    = {El-Keredy, Amira and Schleyer, Michael and K{\"o}nig, Christian and Ekim, Aslihan and Gerber, Bertram},
  title     = {Behavioural Analyses of Quinine Processing in Choice, Feeding and Learning of Larval Drosophila},
  series = {PLoS One},
  volume    = {7},
  journal   = {PLoS One},
  number    = {7},
  doi       = {10.1371/journal.pone.0040525},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-130811},
  pages     = {e40525},
  year      = {2012},
  abstract  = {Gustatory stimuli can support both immediate reflexive behaviour, such as choice and feeding, and can drive internal reinforcement in associative learning. For larval Drosophila, we here provide a first systematic behavioural analysis of these functions with respect to quinine as a study case of a substance which humans report as "tasting bitter". We describe the dose-effect functions for these different kinds of behaviour and find that a half-maximal effect of quinine to suppress feeding needs substantially higher quinine concentrations (2.0 mM) than is the case for internal reinforcement (0.6 mM). Interestingly, in previous studies (Niewalda et al. 2008, Schipanski et al 2008) we had found the reverse for sodium chloride and fructose/sucrose, such that dose-effect functions for those tastants were shifted towards lower concentrations for feeding as compared to reinforcement, arguing that the differences in dose-effect function between these behaviours do not reflect artefacts of the types of assay used. The current results regarding quinine thus provide a starting point to investigate how the gustatory system is organized on the cellular and/or molecular level to result in different behavioural tuning curves towards a bitter tastant.},
  language  = {en}
}
@article{TomeiAdamsUccellinietal.2012,
  author    = {Tomei, Sara and Adams, Sharon and Uccellini, Lorenzo and Bedognetti, Davide and De Giorgi, Valeria and Erdenebileg, Narnygerel and Libera Ascierto, Maria and Reinboth, Jennifer and Liu, Qiuzhen and Bevilacqua, Generoso and Wang, Ena and Mazzanti, Chiara and Marincola, Francesco M.},
  title     = {Association between HRAS rs12628 and rs112587690 polymorphisms with the risk of melanoma in the North American population},
  series = {Medical Oncology},
  volume    = {29},
  journal   = {Medical Oncology},
  number    = {5},
  doi       = {dx.doi.org/10.1007/s12032-012-0255-3},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-126834},
  pages     = {3456-3461},
  year      = {2012},
  abstract  = {HRAS belongs to the RAS genes superfamily. RAS genes are important players in several human tumors and the single-nucleotide polymorphism rs12628 has been shown to contribute to the risk of bladder, colon, gastrointestinal, oral, and thyroid carcinoma. We hypothesized that this SNP may affect the risk of cutaneous melanoma as well. HRAS gene contains a polymorphic region (rs112587690), a repeated hexanucleotide -GGGCCT- located in intron 1. Three alleles of this region, P1, P2, and P3, have been identified that contain two, three, and four repeats of the hexanucleotide, respectively. We investigated the clinical impact of these polymorphisms in a case-control study. A total of 141 melanoma patients and 118 healthy donors from the North America Caucasian population were screened for rs12628 and rs112587690 polymorphisms. Genotypes were assessed by capillary sequencing or fragment analysis, respectively, and rs12628 CC and rs112587690 P1P1 genotypes significantly associated with increased melanoma risk (OR = 3.83, p = 0.003; OR = 11.3, p = 0.033, respectively), while rs112587690 P1P3 frequency resulted significantly higher in the control group (OR = 0.5, p = 0.017). These results suggest that rs12628 C homozygosis may be considered a potential risk factor for melanoma development in the North American population possibly through the linkage to rs112587690.},
  language  = {en}
}
@phdthesis{Heidbreder2012,
  author    = {Heidbreder, Meike},
  title     = {Association and Activation of TNF-Receptor I Investigated with Single-Molecule Tracking and Super-Resolution Microscopy in Live Cells},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-73191},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2012},
  abstract  = {Cellular responses to outer stimuli are the basis for all biological processes. Signal integration is achieved by protein cascades, recognizing and processing molecules from the environment. Factors released by pathogens or inflammation usually induce an inflammatory response, a signal often transduced by Tumour Necrosis Factor alpha (TNF). TNFα receptors TNF-R1 and TNF-R2 can in turn lead to apoptosis or proliferation via NF-B. These processes are closely regulated by membrane compartimentalization, protein interactions and trafficking. Fluorescence microscopy offers a reliable and non-invasive method to probe these cellular events. However, some processes on a native membrane are not resolvable, as they are well below the diffraction limit of microscopy. The recent development of super-resolution fluorescence microscopy methods enables the observation of these cellular players well below this limit: by localizing, tracking and counting molecules with high spatial and temporal resolution, these new fluorescence microscopy methods offer a previously unknown insight into protein interactions at the near-molecular level. Direct stochastic optical reconstruction microscopy (dSTORM) utilizes the reversible, stochastic blinking events of small commercially available fluorescent dyes, while photoactivated localization microscopy (PALM) utilizes phototransformation of genetically encoded fluorescent proteins. By photoactivating only a small fraction of the present fluorophores in each observation interval, single emitters can be localized with high precision and a super-resolved image can be reconstructed. Quantum Dot Triexciton imaging (QDTI) utilizes the three-photon absorption (triexcitonic) properties of quantum dots (QD) and to achieve a twofold resolution increase using conventional confocal microscopes. In this thesis, experimental approaches were implemented to achieve super-resolution microscopy in fixed and live-cells to study the spatial and temporal dynamics of TNF and other cellular signaling events. We introduce QDTI to study the three-dimensional cellular distribution of biological targets, offering an easy method to achieve resolution enhancement in combination with optical sectioning, allowing the preliminary quantification of labeled proteins. As QDs are electron dense, QDTI can be used for correlative fluorescence and transmission electron microscopy, proving the versatility of QD probes. Utilizing the phototransformation properties of fluorescent proteins, single-receptor tracking on live cells was achieved, applying the concept of single particle tracking PALM (sptPALM) to track the dynamics of a TNF-R1-tdEos chimera on the membrane. Lateral receptor dynamics can be tracked with high precision and the influences of ligand addition or lipid disruption on TNF-R1 mobility was observed. The results reveal complex receptor dynamics, implying internalization processes in response to TNFα stimulation and a role for membrane domains with reduced fluidity, so-called lipid raft domains, in TNF-R1 compartimentalization prior or post ligand induction. Comparisons with previously published FCS data show a good accordance, but stressing the increased data depth available in sptPALM experiments. Additionally, the active transport of NF-κB-tdEos fusions was observed in live neurons under chemical stimulation and/or inhibition. Contrary to phototransformable proteins that need no special buffers to exhibit photoconversion or photoactivation, dSTORM has previously been unsuitable for in vivo applications, as organic dyes relied on introducing the probes via immunostaining in concert with a reductive, oxygen-free medium for proper photoswitching behaviour. ATTO655 had been previously shown to be suitable for live-cell applications, as its switching behavior can be catalyzed by the reductive environment of the cytoplasm. By introducing the cell-permeant organic dye via a chemical tag system, a high specificity and low background was achieved. Here, the labeled histone H2B complex and thus single nucleosome movements in a live cell can be observed over long time periods and with ~20 nm resolution. Implementing these new approaches for imaging biological processes with high temporal and spatial resolution provides new insights into the dynamics and spatial heterogeneities of proteins, further elucidating their function in the organism and revealing properties that are usually only detectable in vitro.  },
  subject      = {Fluoreszenzmikrosopie},
  language  = {en}
}
@phdthesis{Bruder2012,
  author    = {Bruder, Jessica},
  title     = {Antigenerkennung bei autoaggressiven Lymphozyten},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-73342},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2012},
  abstract  = {Millionen Menschen weltweit leiden an den verschiedensten Autoimmunerkrankungen. Diese Krankheiten entstehen, wenn das Immunsystem gesundes k{\"o}rpereigenes Gewebe angreift und zerst{\"o}rt. An der Pathogenese sind sowohl Komponenten des angeborenen Immunsystems als auch Bestandteile des adaptiven Immunsystems, wie Lymphozyten und Antik{\"o}rper, beteiligt. Da die Ursachen und molekularen Mechanismen der Pathogenese dieser Erkrankungen bis heute weitgehend unbekannt sind, wurden in dieser Arbeit autoaggressive Lymphozyten bei den humanen Autoimmunerkrankungen Polymyositis und Multiple Sklerose n{\"a}her untersucht. Die Polymyositis ist eine chronisch entz{\"u}ndliche Erkrankung der Skelettmuskulatur. Die Muskelfasern werden dabei von zytotoxischen CD8+ gd-T-Lymphozyten infiltriert, attackiert und schließlich zerst{\"o}rt. In einem seltenen Fall der Polymyositis wurden die Muskelzellen hingegen in {\"a}hnlicher Weise von CD8- gd-T-Lymphozyten angegriffen. Die gd-T-Lymphozyten waren monoklonal expandiert und ihr Rezeptor, im Folgenden als M88 bezeichnet, wurde als Vg1.3+Vd2+ identifiziert. Fr{\"u}here Untersuchungen der Antigenspezifit{\"a}t dieser Zellen zeigten, dass M88 mehrere funktionell und strukturell verschiedene Proteine aus unterschiedlichen Spezies erkennt. Die Bindung erfolgt spezifisch durch die Antigenerkennungsregionen beider Rezeptorketten von M88. In dieser Arbeit wurden verschiedene bakterielle und humane Proteine des Translationsapparates als Antigene von M88 identifiziert. Weitere ausf{\"u}hrliche Untersuchungen eines paradigmatischen bakteriellen Antigens, dem Translationsinitiationsfaktor EcIF1, zeigten, dass M88 an Oberfl{\"a}chen-exponierte Konformationsepitope von Proteinen bindet. Interessanterweise erkennt M88 mehrere humane Aminoacyl-tRNA-Synthetasen, Antigene, die in anderen Formen der Myositis von Autoantik{\"o}rpern angegriffen werden. Diese Beobachtung ergibt eine bemerkenswerte Verbindung zwischen T-Zell- und Antik{\"o}rper-vermittelten B-Zell-Antworten bei der autoimmunen Myositis. Bei der Multiplen Sklerose ist das zentrale Nervensystem betroffen. Autoaggressive Lymphozyten greifen die Myelinschicht der Nervenzellen im Gehirn und R{\"u}ckenmark an und zerst{\"o}ren sie. Im Liquor cerebrospinalis von Patienten lassen sich klonal expandierte und affinit{\"a}tsgereifte B-Zellen sowie „oligoklonale Banden" (OKB) Antik{\"o}rper nachweisen. Obwohl diese Merkmale auf eine Antigen-induzierte Immunantwort hindeuten, sind die zugrundeliegenden Antigene und die Rolle der OKB bei der Pathogenese bis heute unbekannt. In dieser Arbeit wurde die Antigenspezifit{\"a}t von f{\"u}nf IgG OKB-Antik{\"o}rpern aus drei Patienten untersucht. Durch verschiedene proteinbiochemische Methoden konnten intrazellul{\"a}re Kandidatenantigene identifiziert werden. Interessanterweise sind darunter mehrere nukle{\"a}re Proteine, die an der Transkriptionsregulation oder der RNA-Prozessierung beteiligt sind. Reaktivit{\"a}ten gegen intrazellul{\"a}re Antigene treten auch bei anderen Autoimmunerkrankungen, wie beispielsweise dem systemischen Lupus erythematodes, auf. Diese Ergebnisse k{\"o}nnten auf einen allgemeinen Mechanismus der Entstehung und Funktion von Autoantik{\"o}rpern bei diesen humanen Autoimmunerkrankungen hindeuten.},
  subject      = {Multiple Sklerose},
  language  = {de}
}
@article{ZirkelCecilSchaeferetal.2012,
  author    = {Zirkel, J. and Cecil, A. and Sch{\"a}fer, F. and Rahlfs, S. and Ouedraogo, A. and Xiao, K. and Sawadogo, S. and Coulibaly, B. and Becker, K. and Dandekar, T.},
  title     = {Analyzing Thiol-Dependent Redox Networks in the Presence of Methylene Blue and Other Antimalarial Agents with RT-PCR-Supported in silico Modeling},
  series = {Bioinformatics and Biology Insights},
  volume    = {6},
  journal   = {Bioinformatics and Biology Insights},
  doi       = {10.4137/BBI.S10193},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-123751},
  pages     = {287-302},
  year      = {2012},
  abstract  = {BACKGROUND: In the face of growing resistance in malaria parasites to drugs, pharmacological combination therapies are important. There is accumulating evidence that methylene blue (MB) is an effective drug against malaria. Here we explore the biological effects of both MB alone and in combination therapy using modeling and experimental data. RESULTS: We built a model of the central metabolic pathways in P. falciparum. Metabolic flux modes and their changes under MB were calculated by integrating experimental data (RT-PCR data on mRNAs for redox enzymes) as constraints and results from the YANA software package for metabolic pathway calculations. Several different lines of MB attack on Plasmodium redox defense were identified by analysis of the network effects. Next, chloroquine resistance based on pfmdr/and pfcrt transporters, as well as pyrimethamine/sulfadoxine resistance (by mutations in DHF/DHPS), were modeled in silico. Further modeling shows that MB has a favorable synergism on antimalarial network effects with these commonly used antimalarial drugs. CONCLUSIONS: Theoretical and experimental results support that methylene blue should, because of its resistance-breaking potential, be further tested as a key component in drug combination therapy efforts in holoendemic areas.},
  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}
}
@article{JahnSchrammSchnoelzeretal.2012,
  author    = {Jahn, Daniel and Schramm, Sabine and Schn{\"o}lzer, Martina and Heilmann, Clemens J. and de Koster, Chris G. and Sch{\"u}tz, Wolfgang and Benavente, Ricardo and Alsheimer, Manfred},
  title     = {A truncated lamin A in the Lmna\(^{-/-}\) mouse line: Implications for the understanding of laminopathies},
  series = {Nucleus},
  volume    = {3},
  journal   = {Nucleus},
  number    = {5},
  doi       = {10.4161/nucl.21676},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-127281},
  pages     = {463-474},
  year      = {2012},
  abstract  = {During recent years a number of severe clinical syndromes, collectively termed laminopathies, turned out to be caused by various, distinct mutations in the human LMNA gene. Arising from this, remarkable progress has been made to unravel the molecular pathophysiology underlying these disorders. A great benefit in this context was the generation of an A-type lamin deficient mouse line (Lmna\(^{-/-}\)) by Sullivan and others,1 which has become one of the most frequently used models in the field and provided profound insights to many different aspects of A-type lamin function. Here, we report the unexpected finding that these mice express a truncated Lmna gene product on both transcriptional and protein level. Combining different approaches including mass spectrometry, we precisely define this product as a C-terminally truncated lamin A mutant that lacks domains important for protein interactions and post-translational processing. Based on our findings we discuss implications for the interpretation of previous studies using Lmna\(^{-/-}\) mice and the concept of human laminopathies.},
  language  = {en}
}
@article{WeisseHeddergottHeydtetal.2012,
  author    = {Weiße, Sebastian and Heddergott, Niko and Heydt, Matthias and Pfl{\"a}sterer, Daniel and Maier, Timo and Haraszti, Tamas and Grunze, Michael and Engstler, Markus and Rosenhahn, Axel},
  title     = {A Quantitative 3D Motility Analysis of Trypanosoma brucei by Use of Digital In-line Holographic Microscopy},
  series = {PLoS One},
  volume    = {7},
  journal   = {PLoS One},
  number    = {5},
  doi       = {10.1371/journal.pone.0037296},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-130666},
  pages     = {e37296},
  year      = {2012},
  abstract  = {We present a quantitative 3D analysis of the motility of the blood parasite Trypanosoma brucei. Digital in-line holographic microscopy has been used to track single cells with high temporal and spatial accuracy to obtain quantitative data on their behavior. Comparing bloodstream form and insect form trypanosomes as well as mutant and wildtype cells under varying external conditions we were able to derive a general two-state-run-and-tumble-model for trypanosome motility. Differences in the motility of distinct strains indicate that adaption of the trypanosomes to their natural environments involves a change in their mode of swimming.},
  language  = {en}
}
@article{StaigerCadotKooteretal.2012,
  author    = {Staiger, Christine and Cadot, Sidney and Kooter, Raul and Dittrich, Marcus and M{\"u}ller, Tobias and Klau, Gunnar W. and Wessels, Lodewyk F. A.},
  title     = {A Critical Evaluation of Network and Pathway-Based Classifiers for Outcome Prediction in Breast Cancer},
  series = {PLoS One},
  volume    = {7},
  journal   = {PLoS One},
  number    = {4},
  doi       = {10.1371/journal.pone.0034796},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-131323},
  pages     = {e34796},
  year      = {2012},
  abstract  = {Recently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically constructed by aggregating the expression levels of several genes. The secondary data sources are employed to guide this aggregation. Although many studies claim that these approaches improve classification performance over single genes classifiers, the gain in performance is difficult to assess. This stems mainly from the fact that different breast cancer data sets and validation procedures are employed to assess the performance. Here we address these issues by employing a large cohort of six breast cancer data sets as benchmark set and by performing an unbiased evaluation of the classification accuracies of the different approaches. Contrary to previous claims, we find that composite feature classifiers do not outperform simple single genes classifiers. We investigate the effect of (1) the number of selected features; (2) the specific gene set from which features are selected; (3) the size of the training set and (4) the heterogeneity of the data set on the performance of composite feature and single genes classifiers. Strikingly, we find that randomization of secondary data sources, which destroys all biological information in these sources, does not result in a deterioration in performance of composite feature classifiers. Finally, we show that when a proper correction for gene set size is performed, the stability of single genes sets is similar to the stability of composite feature sets. Based on these results there is currently no reason to prefer prognostic classifiers based on composite features over single genes classifiers for predicting outcome in breast cancer.},
  language  = {en}
}