@misc{PolitiPikovskijUllner2017,
  author    = {Politi, Antonio and Pikovskij, Arkadij and Ullner, Ekkehard},
  title     = {Chaotic macroscopic phases in one-dimensional oscillators},
  series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  number    = {721},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-42979},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-429790},
  pages     = {20},
  year      = {2017},
  abstract  = {The connection between the macroscopic description of collective chaos and the underlying microscopic dynamics is thoroughly analysed in mean-field models of one-dimensional oscillators. We investigate to what extent infinitesimal perturbations of the microscopic configurations can provide information also on the stability of the corresponding macroscopic phase. In ensembles of identical one-dimensional dynamical units, it is possible to represent the microscopic configurations so as to make transparent their connection with the macroscopic world. As a result, we find evidence of an intermediate, mesoscopic, range of distances, over which the instability is neither controlled by the microscopic equations nor by the macroscopic ones. We examine a whole series of indicators, ranging from the usual microscopic Lyapunov exponents, to the collective ones, including finite-amplitude exponents. A system of pulse-coupled oscillators is also briefly reviewed as an example of non-identical phase oscillators where collective chaos spontaneously emerges.},
  language  = {en}
}
@phdthesis{Durek2008,
  author    = {Durek, Pawel},
  title     = {Comparative analysis of molecular interaction networks : the interplay between spatial and functional organizing principles},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-31439},
  school      = {Universit{\"a}t Potsdam},
  year      = {2008},
  abstract  = {The study of biological interaction networks is a central theme in systems biology. Here, we investigate common as well as differentiating principles of molecular interaction networks associated with different levels of molecular organization. They include metabolic pathway maps, protein-protein interaction networks as well as kinase interaction networks. First, we present an integrated analysis of metabolic pathway maps and protein-protein interaction networks (PIN). It has long been established that successive enzymatic steps are often catalyzed by physically interacting proteins forming permanent or transient multi-enzyme complexes. Inspecting high-throughput PIN data, it has been shown recently that, indeed, enzymes involved in successive reactions are generally more likely to interact than other protein pairs. In this study, we expanded this line of research to include comparisons of the respective underlying network topologies as well as to investigate whether the spatial organization of enzyme interactions correlates with metabolic efficiency. Analyzing yeast data, we detected long-range correlations between shortest paths between proteins in both network types suggesting a mutual correspondence of both network architectures. We discovered that the organizing principles of physical interactions between metabolic enzymes differ from the general PIN of all proteins. While physical interactions between proteins are generally dissortative, enzyme interactions were observed to be assortative. Thus, enzymes frequently interact with other enzymes of similar rather than different degree. Enzymes carrying high flux loads are more likely to physically interact than enzymes with lower metabolic throughput. In particular, enzymes associated with catabolic pathways as well as enzymes involved in the biosynthesis of complex molecules were found to exhibit high degrees of physical clustering. Single proteins were identified that connect major components of the cellular metabolism and hence might be essential for the structural integrity of several biosynthetic systems. Besides metabolic aspects of PINs, we investigated the characteristic topological properties of protein interactions involved in signaling and regulatory functions mediated by kinase interactions. Characteristic topological differences between PINs associated with metabolism, and those describing phosphorylation networks were revealed and shown to reflect the different modes of biological operation of both network types. The construction of phosphorylation networks is based on the identification of specific kinase-target relations including the determination of the actual phosphorylation sites (P-sites). The computational prediction of P-sites as well as the identification of involved kinases still suffers from insufficient accuracies and specificities of the underlying prediction algorithms, and the experimental identification in a genome-scale manner is not (yet) doable. Computational prediction methods have focused primarily on extracting predictive features from the local, one-dimensional sequence information surrounding P-sites. However the recognition of such motifs by the respective kinases is a spatial event. Therefore, we characterized the spatial distributions of amino acid residue types around P-sites and extracted signature 3D-profiles. We then tested the added value of spatial information on the prediction performance. When compared to sequence-only based predictors, a consistent performance gain was obtained. The availability of reliable training data of experimentally determined P-sites is critical for the development of computational prediction methods. As part of this thesis, we provide an assessment of false-positive rates of phosphoproteomic data.},
  language  = {en}
}
@phdthesis{Muehlenhoff2017,
  author    = {M{\"u}hlenhoff, Judith},
  title     = {Culture-driven innovation},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-104626},
  school      = {Universit{\"a}t Potsdam},
  pages     = {143},
  year      = {2017},
  abstract  = {This cumulative dissertation deals with the potential of underexplored cultural sources for innovation. Nowadays, firms recognize an increasing demand for innovation to keep pace with an ever-growing dynamic worldwide competition. Knowledge is one of the most crucial sources and resource, while until now innovation has been foremost driven by technology. But since the last years, we have been witnessing a change from technology's role as a driver of innovation to an enabler of innovation. Innovative products and services increasingly differentiate through emotional qualities and user experience. These experiences are hard to grasp and require alignment in innovation management theory and practice. This work cares about culture in a broader matter as a source for innovation. It investigates the requirements and fundamentals for "culture-driven innovation" by studying where and how to unlock cultural sources. The research questions are the following: What are cultural sources for knowledge and innovation? Where can one find cultural sources and how to tap into them? The dissertation starts with an overview of its central terms and introduces cultural theories as an overarching frame to study cultural sources for innovation systematically. Here, knowledge is not understood as something an organization owns like a material resource, but it is seen as something created and taking place in practices. Such a practice theoretical lens inheres the rejection of the traditional economic depiction of the rational Homo Oeconomicus. Nevertheless, it also rejects the idea of the Homo Sociologicus about the strong impact of society and its values on individual actions. Practice theory approaches take account of both concepts by underscoring the dualism of individual (agency, micro-level) and structure (society, macro-level). Following this, organizations are no enclosed entities but embedded within their socio-cultural environment, which shapes them and is also shaped by them. Then, the first article of this dissertation acknowledges a methodological stance of this dualism by discussing how mixed methods support an integrated approach to study the micro- and macro-level. The article focuses on networks (thus communities) as a central research unit within studies of entrepreneurship and innovation. The second article contains a network analysis and depicts communities as central loci for cultural sources and knowledge. With data from the platform Meetup.com about events etc., the study explores which overarching communities and themes have been evolved in Berlin's start up and tech scene. While the latter study was about where to find new cultural sources, the last article addresses how to unlock such knowledge sources. It develops the concept of a cultural absorptive capacity, that is the capability of organizations to open up towards cultural sources. Furthermore, the article points to the role of knowledge intermediaries in the early phases of knowledge acquisition. Two case studies on companies working with artists illustrate the roles of such intermediaries and how they support firms to gain knowledge from cultural sources. Overall, this dissertation contributes to a better understanding of culture as a source for innovation from a theoretical, methodological, and practitioners' point of view. It provides basic research to unlock the potential of such new knowledge sources for companies - sources that so far have been neglected in innovation management.},
  language  = {en}
}
@phdthesis{Gengel2021,
  author    = {Gengel, Erik},
  title     = {Direct and inverse problems of network analysis},
  doi       = {10.25932/publishup-51236},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-512367},
  school      = {Universit{\"a}t Potsdam},
  pages     = {VIII, 102},
  year      = {2021},
  abstract  = {Selfsustained oscillations are some of the most commonly observed phenomena in biological systems. They emanate from non-linear systems in a heterogeneous environment and can be described by the theory of dynamical systems. Part of this theory considers reduced models of the oscillator dynamics by means of amplitudes and a phase variable. Such variables are highly attractive for theoretical and experimental studies. Theoretically these variables correspond to an integrable linearization of the generally non-linear system. Experimentally, there exist well established approaches to extract phases from oscillator signals. Notably, one can define phase models also for networks of oscillators. One highly active field examines effects of non-local coupling among oscillators, which is thought to play a key role in networks with strong coupling. The dissertation introduces and expands the knowledge about high-order phase coupling in networks of oscillators. Mathematical calculations consider the Stuart-Landau oscillator. A novel phase estimation scheme for direct observations of an oscillator dynamics is introduced based on numerics. A numerical study of high-order phase coupling applies a Fourier fit for the Stuart-Landau and for the van-der-Pol oscillator. The numerical approach is finally tested on observation-based phase estimates of the Morris-Lecar neuron. A popular approach for the construction of phases from signals is based on phase demodulation by means of the Hilbert transform. Generally, observations of oscillations contain a small and generic variation of their amplitude. The work presents a way to quantify how much the variations of signal amplitude spoil a phase demodulation procedure. For the ideal case of phase modulated signals, amplitude modulations vanish. However, the Hilbert transform produces artificial variations of the reconstructed amplitude even in this case. The work proposes a novel procedure called Iterative Hilbert Transform Embedding to obtain an optimal demodulation of signals. The text presents numerous examples and tests of application for the method, covering multicomponent signals, observables of highly stable limit cycle oscillations and noisy phase dynamics. The numerical results are supported by a spectral theory of convergence for weak phase modulations.},
  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}
}
@misc{SchwarzBuffonEtteetal.2015,
  author    = {Schwarz, Ingo and Buffon, Giuseppe and Ette, Ottmar and Garrido, Elisa and Heyd, Thomas and Lundberg, Karin and Werner, Petra},
  title     = {HiN : Alexander von Humboldt im Netz},
  series = {HIN : Alexander von Humboldt im Netz ; international review for Humboldtian studies},
  volume    = {XVI},
  journal   = {HIN : Alexander von Humboldt im Netz ; international review for Humboldtian studies},
  number    = {30},
  editor    = {Ette, Ottmar and Knobloch, Eberhard},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  issn      = {1617-5239},
  doi       = {10.18443/hinvol16iss302015},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-86895},
  pages     = {101},
  year      = {2015},
  abstract  = {Ingo Schwarz: „Uebrigens verbleibe ich mit besonderer Werthsch{\"a}tzung Euer gn{\"a}diger K{\"o}nig". Zum Briefwechsel Alexander von Humboldts mit Friedrich Wilhelm III. im September 1804 Giuseppe Buffon: The Franciscans in Cathay: memory of men and places. A Contribution for the genealogy of geographical knowledge of Alexander von Humboldt Ottmar Ette: Icono-graf{\´i}a, cali-graf{\´i}a, auto-graf{\´i}a. Sobre el arte de la visualizaci{\´o}n en los diarios del viaje americano de Alexander von Humboldt Elisa Garrido: Arte, ciencia y cultura visual en el atlas pintoresco: Vista de la Plaza Mayor de Mexico Thomas Heyd: Ascensi{\´o}n al Teide de Alexander von Humboldt Karin Lundberg: Networking Knowledge: Considering Alexander von Humboldt's Legacy in a New Shared Space in Education Petra Werner: In der Naturgeschichte „etwas H{\"o}heres suchen". Zu Humboldts Konzept der Pflanzengeographie},
  language  = {mul}
}
@misc{SchroenKoehliScheiffeleetal.2017,
  author    = {Schr{\"o}n, Martin and K{\"o}hli, Markus and Scheiffele, Lena and Iwema, Joost and Bogena, Heye R. and Lv, Ling and Martini, Edoardo and Baroni, Gabriele and Rosolem, Rafael and Weimar, Jannis and Mai, Juliane and Cuntz, Matthias and Rebmann, Corinna and Oswald, Sascha Eric and Dietrich, Peter and Schmidt, Ulrich and Zacharias, Steffen},
  title     = {Improving calibration and validation of cosmic-ray neutron sensors in the light of spatial sensitivity},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe},
  number    = {636},
  doi       = {10.25932/publishup-41913},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-419134},
  pages     = {5009 -- 5030},
  year      = {2017},
  abstract  = {In the last few years the method of cosmic-ray neutron sensing (CRNS) has gained popularity among hydrologists, physicists, and land-surface modelers. The sensor provides continuous soil moisture data, averaged over several hectares and tens of decimeters in depth. However, the signal still may contain unidentified features of hydrological processes, and many calibration datasets are often required in order to find reliable relations between neutron intensity and water dynamics. Recent insights into environmental neutrons accurately described the spatial sensitivity of the sensor and thus allowed one to quantify the contribution of individual sample locations to the CRNS signal. Consequently, data points of calibration and validation datasets are suggested to be averaged using a more physically based weighting approach. In this work, a revised sensitivity function is used to calculate weighted averages of point data. The function is different from the simple exponential convention by the extraordinary sensitivity to the first few meters around the probe, and by dependencies on air pressure, air humidity, soil moisture, and vegetation. The approach is extensively tested at six distinct monitoring sites: two sites with multiple calibration datasets and four sites with continuous time series datasets. In all cases, the revised averaging method improved the performance of the CRNS products. The revised approach further helped to reveal hidden hydrological processes which otherwise remained unexplained in the data or were lost in the process of overcalibration. The presented weighting approach increases the overall accuracy of CRNS products and will have an impact on all their applications in agriculture, hydrology, and modeling.},
  language  = {en}
}
@phdthesis{Wittenbecher2017,
  author    = {Wittenbecher, Clemens},
  title     = {Linking whole-grain bread, coffee, and red meat to the risk of type 2 diabetes},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-404592},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XII, 194, ii},
  year      = {2017},
  abstract  = {Background: Consumption of whole-grain, coffee, and red meat were consistently related to the risk of developing type 2 diabetes in prospective cohort studies, but potentially underlying biological mechanisms are not well understood. Metabolomics profiles were shown to be sensitive to these dietary exposures, and at the same time to be informative with respect to the risk of type 2 diabetes. Moreover, graphical network-models were demonstrated to reflect the biological processes underlying high-dimensional metabolomics profiles. Aim: The aim of this study was to infer hypotheses on the biological mechanisms that link consumption of whole-grain bread, coffee, and red meat, respectively, to the risk of developing type 2 diabetes. More specifically, it was aimed to consider network models of amino acid and lipid profiles as potential mediators of these risk-relations. Study population: Analyses were conducted in the prospective EPIC-Potsdam cohort (n = 27,548), applying a nested case-cohort design (n = 2731, including 692 incident diabetes cases). Habitual diet was assessed with validated semiquantitative food-frequency questionnaires. Concentrations of 126 metabolites (acylcarnitines, phosphatidylcholines, sphingomyelins, amino acids) were determined in baseline-serum samples. Incident type 2 diabetes cases were assed and validated in an active follow-up procedure. The median follow-up time was 6.6 years. Analytical design: The methodological approach was conceptually based on counterfactual causal inference theory. Observations on the network-encoded conditional independence structure restricted the space of possible causal explanations of observed metabolomics-data patterns. Given basic directionality assumptions (diet affects metabolism; metabolism affects future diabetes incidence), adjustment for a subset of direct neighbours was sufficient to consistently estimate network-independent direct effects. Further model-specification, however, was limited due to missing directionality information on the links between metabolites. Therefore, a multi-model approach was applied to infer the bounds of possible direct effects. All metabolite-exposure links and metabolite-outcome links, respectively, were classified into one of three categories: direct effect, ambiguous (some models indicated an effect others not), and no-effect. Cross-sectional and longitudinal relations were evaluated in multivariable-adjusted linear regression and Cox proportional hazard regression models, respectively. Models were comprehensively adjusted for age, sex, body mass index, prevalence of hypertension, dietary and lifestyle factors, and medication. Results: Consumption of whole-grain bread was related to lower levels of several lipid metabolites with saturated and monounsaturated fatty acids. Coffee was related to lower aromatic and branched-chain amino acids, and had potential effects on the fatty acid profile within lipid classes. Red meat was linked to lower glycine levels and was related to higher circulating concentrations of branched-chain amino acids. In addition, potential marked effects of red meat consumption on the fatty acid composition within the investigated lipid classes were identified. Moreover, potential beneficial and adverse direct effects of metabolites on type 2 diabetes risk were detected. Aromatic amino acids and lipid metabolites with even-chain saturated (C14-C18) and with specific polyunsaturated fatty acids had adverse effects on type 2 diabetes risk. Glycine, glutamine, and lipid metabolites with monounsaturated fatty acids and with other species of polyunsaturated fatty acids were classified as having direct beneficial effects on type 2 diabetes risk. Potential mediators of the diet-diabetes links were identified by graphically overlaying this information in network models. Mediation analyses revealed that effects on lipid metabolites could potentially explain about one fourth of the whole-grain bread effect on type 2 diabetes risk; and that effects of coffee and red meat consumption on amino acid and lipid profiles could potentially explain about two thirds of the altered type 2 diabetes risk linked to these dietary exposures. Conclusion: An algorithm was developed that is capable to integrate single external variables (continuous exposures, survival time) and high-dimensional metabolomics-data in a joint graphical model. Application to the EPIC-Potsdam cohort study revealed that the observed conditional independence patterns were consistent with the a priori mediation hypothesis: Early effects on lipid and amino acid metabolism had the potential to explain large parts of the link between three of the most widely discussed diabetes-related dietary exposures and the risk of developing type 2 diabetes.},
  language  = {en}
}
@misc{AgarwalMarwanMaheswaranetal.2017,
  author    = {Agarwal, Ankit and Marwan, Norbert and Maheswaran, Rathinasamy and Merz, Bruno and Kurths, J{\"u}rgen},
  title     = {Multi-scale event synchronization analysis for unravelling climate processes},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {661},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-41827},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-418274},
  pages     = {13},
  year      = {2017},
  abstract  = {The temporal dynamics of climate processes are spread across different timescales and, as such, the study of these processes at only one selected timescale might not reveal the complete mechanisms and interactions within and between the (sub-) processes. To capture the non-linear interactions between climatic events, the method of event synchronization has found increasing attention recently. The main drawback with the present estimation of event synchronization is its restriction to analysing the time series at one reference timescale only. The study of event synchronization at multiple scales would be of great interest to comprehend the dynamics of the investigated climate processes. In this paper, the wavelet-based multi-scale event synchronization (MSES) method is proposed by combining the wavelet transform and event synchronization. Wavelets are used extensively to comprehend multi-scale processes and the dynamics of processes across various timescales. The proposed method allows the study of spatio-temporal patterns across different timescales. The method is tested on synthetic and real-world time series in order to check its replicability and applicability. The results indicate that MSES is able to capture relationships that exist between processes at different timescales.},
  language  = {en}
}
@misc{DiGiacomoDiGiacomoKligeretal.2015,
  author    = {Di Giacomo, Adrian S. and Di Giacomo, Alejandro G. and Kliger, Rafi and Reboreda, Juan C. and Tiedemann, Ralph and Mahler, Bettina},
  title     = {No evidence of genetic variation in microsatellite and mitochondrial DNA markers among remaining populations of the Strange-tailed Tyrant Alectrurus risora, an endangered grassland species},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe},
  number    = {583},
  doi       = {10.25932/publishup-41442},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-414427},
  pages     = {127 -- 138},
  year      = {2015},
  abstract  = {The Strange-tailed Tyrant Alectrurus risora (Aves: Tyrannidae) is an endemic species of southern South American grasslands that suffered a 90\% reduction of its original distribution due to habitat transformation. This has led the species to be classified as globally Vulnerable. By the beginning of the last century, populations were partially migratory and moved south during the breeding season. Currently, the main breeding population inhabits the Ibera wetlands in the province of Corrientes, north-east Argentina, where it is resident all year round. There are two remaining small populations in the province of Formosa, north-east Argentina, and in southern Paraguay, which are separated from the main population by the Parana-Paraguay River and its continuous riverine forest habitat. The populations of Corrientes and Formosa are separated by 300 km and the grasslands between populations are non-continuous due to habitat transformation. We used mtDNA sequences and eight microsatellite loci to test if there were evidences of genetic isolation between Argentinean populations. We found no evidence of genetic structure between populations (Phi(ST) = 0.004, P = 0.32; Fst = 0.01, P = 0.06), which can be explained by either retained ancestral polymorphism or by dispersal between populations. We found no evidence for a recent demographic bottleneck in nuclear loci. Our results indicate that these populations could be managed as a single conservation unit on a regional scale. Conservation actions should be focused on preserving the remaining network of areas with natural grasslands to guarantee reproduction, dispersal and prevent further decline of populations.},
  language  = {en}
}