@phdthesis{Siewert2011,
  author    = {Siewert, Katharina},
  title     = {Autoaggressive human t cell receptorrs and their antigen specificities},
  address   = {Potsdam},
  pages     = {145 S.},
  year      = {2011},
  language  = {en}
}
@phdthesis{Lehmann2011,
  author    = {Lehmann, Martin},
  title     = {Back to the roots : regulation of arabidopsis root metabolism during oxidative stress},
  address   = {Potsdam},
  pages     = {154 S.},
  year      = {2011},
  language  = {en}
}
@phdthesis{Nahavandi2011,
  author    = {Nahavandi, Nahid},
  title     = {Genetic and morphological analysis on the evolution of the Ponto-Caspian amphipod Pontogammarus maeoticus},
  address   = {Potsdam},
  pages     = {54 S.},
  year      = {2011},
  language  = {en}
}
@phdthesis{Schroeder2011,
  author    = {Schr{\"o}der, Florian},
  title     = {Funktionelle Charakterisierung der EXO/EXL-Proteinfamilie und NFXL2-Isoformen in Arabidopsis thaliana},
  address   = {Potsdam},
  pages     = {86 S.},
  year      = {2011},
  language  = {de}
}
@phdthesis{Rott2011,
  author    = {Rott, Markus},
  title     = {Die Rolle der plastid{\"a}ren APT Synthase in der Regulation des photosynthetischen Elektronenflusses},
  address   = {Potsdam},
  pages     = {131 S.},
  year      = {2011},
  language  = {de}
}
@phdthesis{Borwankar2011,
  author    = {Borwankar, Tejas},
  title     = {Natural osmolytes remodel the aggregation pathway of mutant huntingtin exon 1},
  address   = {Potsdam},
  pages     = {120 S.},
  year      = {2011},
  language  = {en}
}
@phdthesis{Klie2011,
  author    = {Klie, Sebastian},
  title     = {Integrative analysis of hight-throughput "omics"-data and structured biological knowledge},
  address   = {Potsdam},
  pages     = {102 S.},
  year      = {2011},
  language  = {en}
}
@phdthesis{CamaraMattosMartins2011,
  author    = {Camara Mattos Martins, Marina},
  title     = {What are the downstream targets of trehalose-6-phosphate signalling in plants?},
  address   = {Potsdam},
  pages     = {164 S.},
  year      = {2011},
  language  = {en}
}
@phdthesis{Mittag2011,
  author    = {Mittag, Sonnhild},
  title     = {Vom Rosetta-Stone-Protein NitFhit zur Tumorsuppressorwirkung der humanen Nitrilase1},
  address   = {Potsdam},
  pages     = {113 S.},
  year      = {2011},
  language  = {de}
}
@phdthesis{Sperfeld2011,
  author    = {Sperfeld, Erik},
  title     = {Effects of temperature and co-limiting nutritional components on life history traits of Daphnia magna and its biochemical composition},
  address   = {Potsdam},
  pages     = {157 S.},
  year      = {2011},
  language  = {en}
}
@phdthesis{Tiller2011,
  author    = {Tiller, Nadine},
  title     = {Plastid translation : functions of plastid-specific ribosomal proteins and identification of a factor mediating plastid-to-nucleus retrograde sifnalling},
  address   = {Potsdam},
  pages     = {122 S.},
  year      = {2011},
  language  = {en}
}
@phdthesis{Li2011,
  author    = {Li, Xiaoqing},
  title     = {Structural and dynamic analysis of circadian oscillators and modelling seasonal response in Soay sheep},
  address   = {Potsdam},
  pages     = {163 S.},
  year      = {2011},
  language  = {en}
}
@phdthesis{Rocha2011,
  author    = {Rocha, Marcia Rosa},
  title     = {Time series analysis reveals links between functional traits, population dynamics and ecosystem functions in a diverse phytoplankton community},
  address   = {Potsdam},
  pages     = {126 S.},
  year      = {2011},
  language  = {en}
}
@phdthesis{Athikomrattanakul2011,
  author    = {Athikomrattanakul, Umporn},
  title     = {Development and characterization of molecularly imprinted polymers as binding elements against nitrofurantoin},
  address   = {Potsdam},
  pages     = {97 S.},
  year      = {2011},
  language  = {en}
}
@phdthesis{CuadrosInostroza2011,
  author    = {Cuadros-Inostroza, Alvaro},
  title     = {Integrated analysis of transcriptome and metabolome to understand grapevine development},
  address   = {Potsdam},
  pages     = {136 S.},
  year      = {2011},
  language  = {en}
}
@phdthesis{Ivakov2011,
  author    = {Ivakov, Alexander},
  title     = {Metabolic interactions in leaf development in Arabidopsis thaliana},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-59730},
  school      = {Universit{\"a}t Potsdam},
  year      = {2011},
  abstract  = {Das Wachstum und {\"U}berleben von Pflanzen basiert auf der Photosynthese in den Bl{\"a}ttern. Diese beinhaltet die Aufnahme von Kohlenstoffdioxid aus der Atmosph{\"a}re und das simultane Einfangen von Lichtenergie zur Bildung organischer Molek{\"u}le. Diese werden nach dem Eintritt in den Metabolismus in viele andere Komponenten umgewandelt, welche die Grundlage f{\"u}r die Zunahme der Biomasse bilden. Bl{\"a}tter sind Organe, die auf die Fixierung von Kohlenstoffdioxid spezialisiert sind. Die Funktionen der Bl{\"a}tter beinhalten vor allem die Optimierung und Feinregulierung vieler Prozesse, um eine effektive Nutzung von Ressourcen und eine maximale Photosynthese zu gew{\"a}hrleisten. Es ist bekannt, dass sich die Morphologie der Bl{\"a}tter den Wachstumsbedingungen der Pflanze anpasst und eine wichtige Rolle bei der Optimierung der Photosynthese spielt. Trotzdem ist die Regulation dieser Art der Anpassung bisher nicht verstanden. Die allgemeine Zielsetzung dieser vorliegenden Arbeit ist das Verst{\"a}ndnis wie das Wachstum und die Morphologie der Bl{\"a}tter im Modellorganismus Arabidopsis thaliana reguliert werden. Besondere Aufmerksamkeit wurde hierbei der M{\"o}glichkeit geschenkt, dass es interne metabolische Signale in der Pflanze geben k{\"o}nnte, die das Wachstum und die Entwicklung von Bl{\"a}ttern beeinflussen. Um diese Fragestellung zu untersuchen, muss das Wachstum und die Entwicklung von Bl{\"a}ttern oberhalb des Levels des einzelnen Organs und im Kontext der gesamten Pflanze betrachtet werden, weil Bl{\"a}tter nicht eigenst{\"a}ndig wachsen, sondern von Ressourcen und regulatorischen Einfl{\"u}ssen der ganzen Pflanze abh{\"a}ngig sind. Aufgrund der Komplexit{\"a}t dieser Fragestellung wurden drei komplement{\"a}re Ans{\"a}tze durchgef{\"u}hrt. Im ersten und spezifischsten Ansatz wurde untersucht ob eine flussabw{\"a}rts liegende Komponente des Zucker-Signalwegs, Trehalose-6-Phosphat (Tre-6-P), das Blattwachstum und die Blattentwicklung beinflussen kann. Um diese Frage zu beantworten wurden transgene Arabidopsis-Linien mit einem gest{\"o}rten Gehalt von Tre-6-P durch die Expression von bakteriellen Proteinen die in dem metabolismus von trehalose beteiligt sind. Die Pflanzen-Linien wurden unter Standard-Bendingungen in Erde angebaut und ihr Metabolismus und ihre Blattmorphologie untersucht. Diese Experimente f{\"u}hrten auch zu einem unerwarteten Projekt hinsichtlich einer m{\"o}glichen Rolle von Tre-6-P in der Regulation der Stomata. In einem zweiten, allgemeineren Ansatz wurde untersucht, ob {\"A}nderungen im Zucker-Gehalt der Pflanzen die Morphogenese der Bl{\"a}tter als Antwort auf Licht beeinflussen. Dazu wurden eine Reihe von Mutanten, die im Zentralmetabolismus beeintr{\"a}chtigt sind, in derselben Lichtbedingung angezogen und bez{\"u}glich ihrer Blattmorphologie analysiert. In einem dritten noch allgemeineren Ansatz wurde die nat{\"u}rliche Variation von morphologischen Auspr{\"a}gungen der Bl{\"a}tter und Rosette anhand von wilden Arabidopsis {\"O}kotypen untersucht, um zu verstehen wie sich die Blattmorphologie auf die Blattfunktion und das gesamte Pflanzenwachstum auswirkt und wie unterschiedliche Eigenschaften miteinander verkn{\"u}pft sind. Das Verh{\"a}ltnis der Blattanzahl zum Gesamtwachstum der Pflanze und Blattgr{\"o}ße wurde gesondert weiter untersucht durch eine Normalisierung der Blattanzahl auf das Frischgewicht der Rosette, um den Parameter „leafing Intensity" abzusch{\"a}tzen. Leafing Intensity integrierte Blattanzahl, Blattgr{\"o}ße und gesamtes Rosettenwachstum in einer Reihe von Kompromiss-Interaktionen, die in einem Wachstumsvorteil resultieren, wenn Pflanzen weniger, aber gr{\"o}ßere Bl{\"a}tter pro Einheit Biomasse ausbilden. Dies f{\"u}hrte zu einem theoretischen Ansatz in dem ein einfaches allometrisch mathematisches Modell konstruiert wurde, um Blattanzahl, Blattgr{\"o}ße und Pflanzenwachstum im Kontext der gesamten Pflanze Arabidopsis zu verkn{\"u}pfen.},
  language  = {en}
}
@phdthesis{Massie2011,
  author    = {Massie, Thomas Michael},
  title     = {Dynamic behavior of phytoplankton populations far from steady state : chemostat experiments and mathematical modeling},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-58102},
  school      = {Universit{\"a}t Potsdam},
  year      = {2011},
  abstract  = {Nature changes continuously and is only seemingly at equilibrium. Environmental parameters like temperature, humidity or insolation may strongly fluctuate on scales ranging from seconds to millions of years. Being part of an ecosystem, species have to cope with these environmental changes. For ecologists, it is of special interest how individual responses to environmental changes affect the dynamics of an entire population - and, if this behavior is predictable. In this context, the demographic structure of a population plays a decisive role since it originates from processes of growth and mortality. These processes are fundamentally influenced by the environment. But, how exactly does the environment influence the behavior of populations? And what does the transient behavior look like? As a result from environmental influences on demography, so called cohorts form. They are age or size classes that are disproportionally represented in the demographic distribution of a population. For instance, if most old and young individuals die due to a cold spell, the population finally consists of mainly middle-aged individuals. Hence, the population got synchronized. Such a population tends to show regular fluctuations in numbers (denoted as oscillations) since the alternating phases of individual growth and population growth (due to reproduction) are now performed synchronously by the majority of the population.That is, one time the population growths, and the other time it declines due to mortality. Synchronous behavior is one of the most pervasive phenomena in nature. Gravitational synchrony in the solar system; fireflies flashing in unison; coordinate firing of pacemaker cells in the heart; electrons in a superconductor marching in lockstep. Whatever scale one looks at, in animate as well as inanimate systems, one is likely to encounter synchrony. In experiments with phytoplankton populations, I could show that this principle of synchrony (as used by physicists) could well-explain the oscillations observed in the experiments, too. The size of the fluctuations depended on the strength by which environmental parameters changed as well as on the demographic state of a population prior to this change. That is, two population living in different habitats can be equally influenced by an environmental change, however, the resulting population dynamics may be significantly different when both populations differed in their demographic state before. Moreover, specific mechanisms relevant for the dynamic behavior of populations, appear only when the environmental conditions change. In my experiments, the population density declined by 50\% after ressource supply was doubled. This counter-intuitive behavior can be explained by increasing ressource consumption. The phytoplankton cells grew larger and enhanced their individual constitution. But at the same time, reproduction was delayed and the population density declined due to the losses by mortality. Environmental influences can also synchronize two or more populations over large distances, which is denoted as Moran effect. Assume two populations living on two distant islands. Although there is no exchange of individuals between them, both populations show a high similarity when comparing their time series. This is because the globally acting climate synchronizes the regionally acting weather on both island. Since the weather fluctuations influence the population dynamics, the Moran effect states that the synchrony between the environment equals the one between the populations. My experiments support this theory and also explain deviations arising when accounting for differences in the populations and the habitats they are living in. Moreover, model simulations and experiments astonishingly show that the synchrony between the populations can be higher than between the environment, when accounting for differences in the environmental fluctuations ("noise color").},
  language  = {de}
}
@phdthesis{Schuette2011,
  author    = {Sch{\"u}tte, Moritz},
  title     = {Evolutionary fingerprints in genome-scale networks},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-57483},
  school      = {Universit{\"a}t Potsdam},
  year      = {2011},
  abstract  = {Mathematical modeling of biological phenomena has experienced increasing interest since new high-throughput technologies give access to growing amounts of molecular data. These modeling approaches are especially able to test hypotheses which are not yet experimentally accessible or guide an experimental setup. One particular attempt investigates the evolutionary dynamics responsible for today's composition of organisms. Computer simulations either propose an evolutionary mechanism and thus reproduce a recent finding or rebuild an evolutionary process in order to learn about its mechanism. The quest for evolutionary fingerprints in metabolic and gene-coexpression networks is the central topic of this cumulative thesis based on four published articles. An understanding of the actual origin of life will probably remain an insoluble problem. However, one can argue that after a first simple metabolism has evolved, the further evolution of metabolism occurred in parallel with the evolution of the sequences of the catalyzing enzymes. Indications of such a coevolution can be found when correlating the change in sequence between two enzymes with their distance on the metabolic network which is obtained from the KEGG database. We observe that there exists a small but significant correlation primarily on nearest neighbors. This indicates that enzymes catalyzing subsequent reactions tend to be descended from the same precursor. Since this correlation is relatively small one can at least assume that, if new enzymes are no "genetic children" of the previous enzymes, they certainly be descended from any of the already existing ones. Following this hypothesis, we introduce a model of enzyme-pathway coevolution. By iteratively adding enzymes, this model explores the metabolic network in a manner similar to diffusion. With implementation of an Gillespie-like algorithm we are able to introduce a tunable parameter that controls the weight of sequence similarity when choosing a new enzyme. Furthermore, this method also defines a time difference between successive evolutionary innovations in terms of a new enzyme. Overall, these simulations generate putative time-courses of the evolutionary walk on the metabolic network. By a time-series analysis, we find that the acquisition of new enzymes appears in bursts which are pronounced when the influence of the sequence similarity is higher. This behavior strongly resembles punctuated equilibrium which denotes the observation that new species tend to appear in bursts as well rather than in a gradual manner. Thus, our model helps to establish a better understanding of punctuated equilibrium giving a potential description at molecular level. From the time-courses we also extract a tentative order of new enzymes, metabolites, and even organisms. The consistence of this order with previous findings provides evidence for the validity of our approach. While the sequence of a gene is actually subject to mutations, its expression profile might also indirectly change through the evolutionary events in the cellular interplay. Gene coexpression data is simply accessible by microarray experiments and commonly illustrated using coexpression networks where genes are nodes and get linked once they show a significant coexpression. Since the large number of genes makes an illustration of the entire coexpression network difficult, clustering helps to show the network on a metalevel. Various clustering techniques already exist. However, we introduce a novel one which maintains control of the cluster sizes and thus assures proper visual inspection. An application of the method on Arabidopsis thaliana reveals that genes causing a severe phenotype often show a functional uniqueness in their network vicinity. This leads to 20 genes of so far unknown phenotype which are however suggested to be essential for plant growth. Of these, six indeed provoke such a severe phenotype, shown by mutant analysis. By an inspection of the degree distribution of the A.thaliana coexpression network, we identified two characteristics. The distribution deviates from the frequently observed power-law by a sharp truncation which follows after an over-representation of highly connected nodes. For a better understanding, we developed an evolutionary model which mimics the growth of a coexpression network by gene duplication which underlies a strong selection criterion, and slight mutational changes in the expression profile. Despite the simplicity of our assumption, we can reproduce the observed properties in A.thaliana as well as in E.coli and S.cerevisiae. The over-representation of high-degree nodes could be identified with mutually well connected genes of similar functional families: zinc fingers (PF00096), flagella, and ribosomes respectively. In conclusion, these four manuscripts demonstrate the usefulness of mathematical models and statistical tools as a source of new biological insight. While the clustering approach of gene coexpression data leads to the phenotypic characterization of so far unknown genes and thus supports genome annotation, our model approaches offer explanations for observed properties of the coexpression network and furthermore substantiate punctuated equilibrium as an evolutionary process by a deeper understanding of an underlying molecular mechanism.},
  language  = {en}
}
@phdthesis{Schoenheit2011,
  author    = {Sch{\"o}nheit, J{\"o}rg},
  title     = {A phagocyte-specific Irf8 gene enhancer establishes early conventional dendritic cell commitment},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-55482},
  school      = {Universit{\"a}t Potsdam},
  year      = {2011},
  abstract  = {Haematopoietic development is a complex process that is strictly hierarchically organized. Here, the phagocyte lineages are a very heterogeneous cell compartment with specialized functions in innate immunity and induction of adaptive immune responses. Their generation from a common precursor must be tightly controlled. Interference within lineage formation programs for example by mutation or change in expression levels of transcription factors (TF) is causative to leukaemia. However, the molecular mechanisms driving specification into distinct phagocytes remain poorly understood. In the present study I identify the transcription factor Interferon Regulatory Factor 8 (IRF8) as the specification factor of dendritic cell (DC) commitment in early phagocyte precursors. Employing an IRF8 reporter mouse, I showed the distinct Irf8 expression in haematopoietic lineage diversification and isolated a novel bone marrow resident progenitor which selectively differentiates into CD8α+ conventional dendritic cells (cDCs) in vivo. This progenitor strictly depends on Irf8 expression to properly establish its transcriptional DC program while suppressing a lineage-inappropriate neutrophile program. Moreover, I demonstrated that Irf8 expression during this cDC commitment-step depends on a newly discovered myeloid-specific cis-enhancer which is controlled by the haematopoietic transcription factors PU.1 and RUNX1. Interference with their binding leads to abrogation of Irf8 expression, subsequently to disturbed cell fate decisions, demonstrating the importance of these factors for proper phagocyte cell development. Collectively, these data delineate a transcriptional program establishing cDC fate choice with IRF8 in its center.},
  language  = {en}
}
@phdthesis{Giorgi2011,
  author    = {Giorgi, Federico Manuel},
  title     = {Expression-based reverse engineering of plant transcriptional networks},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-56760},
  school      = {Universit{\"a}t Potsdam},
  year      = {2011},
  abstract  = {Regulation of gene transcription plays a major role in mediating cellular responses and physiological behavior in all known organisms. The finding that similar genes are often regulated in a similar manner (co-regulated or "co-expressed") has directed several "guilt-by-association" approaches in order to reverse-engineer the cellular transcriptional networks using gene expression data as a compass. This kind of studies has been considerably assisted in the recent years by the development of high-throughput transcript measurement platforms, specifically gene microarrays and next-generation sequencing. In this thesis, I describe several approaches for improving the extraction and interpretation of the information contained in microarray based gene expression data, through four steps: (1) microarray platform design, (2) microarray data normalization, (3) gene network reverse engineering based on expression data and (4) experimental validation of expression-based guilt-by-association inferences. In the first part test case is shown aimed at the generation of a microarray for Thellungiella salsuginea, a salt and drought resistant close relative to the model plant Arabidopsis thaliana; the transcripts of this organism are generated on the combination of publicly available ESTs and newly generated ad-hoc next-generation sequencing data. Since the design of a microarray platform requires the availability of highly reliable and non-redundant transcript models, these issues are addressed consecutively, proposing several different technical solutions. In the second part I describe how inter-array correlation artifacts are generated by the common microarray normalization methods RMA and GCRMA, together with the technical and mathematical characteristics underlying the problem. A solution is proposed in the form of a novel normalization method, called tRMA. The third part of the thesis deals with the field of expression-based gene network reverse engineering. It is shown how different centrality measures in reverse engineered gene networks can be used to distinguish specific classes of genes, in particular essential genes in Arabidopsis thaliana, and how the use of conditional correlation can add a layer of understanding over the information flow processes underlying transcript regulation. Furthermore, several network reverse engineering approaches are compared, with a particular focus on the LASSO, a linear regression derivative rarely applied before in global gene network reconstruction, despite its theoretical advantages in robustness and interpretability over more standard methods. The performance of LASSO is assessed through several in silico analyses dealing with the reliability of the inferred gene networks. In the final part, LASSO and other reverse engineering methods are used to experimentally identify novel genes involved in two independent scenarios: the seed coat mucilage pathway in Arabidopsis thaliana and the hypoxic tuber development in Solanum tuberosum. In both cases an interesting method complementarity is shown, which strongly suggests a general use of hybrid approaches for transcript expression-based inferences. In conclusion, this work has helped to improve our understanding of gene transcription regulation through a better interpretation of high-throughput expression data. Part of the network reverse engineering methods described in this thesis have been included in a tool (CorTo) for gene network reverse engineering and annotated visualization from custom transcription datasets.},
  language  = {en}
}