TY - GEN A1 - Memczak, Henry A1 - Lauster, Daniel A1 - Kar, Parimal A1 - Di Lella, Santiago A1 - Volkmer, Rudolf A1 - Knecht, Volker A1 - Herrmann, Andreas A1 - Ehrentreich-Förster, Eva A1 - Bier, Frank Fabian A1 - Stöcklein, Walter F. M. T1 - Anti-hemagglutinin antibody derived lead peptides for inhibitors of influenza virus binding T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Antibodies against spike proteins of influenza are used as a tool for characterization of viruses and therapeutic approaches. However, development, production and quality control of antibodies is expensive and time consuming. To circumvent these difficulties, three peptides were derived from complementarity determining regions of an antibody heavy chain against influenza A spike glycoprotein. Their binding properties were studied experimentally, and by molecular dynamics simulations. Two peptide candidates showed binding to influenza A/Aichi/2/68 H3N2. One of them, termed PeB, with the highest affinity prevented binding to and infection of target cells in the micromolar region without any cytotoxic effect. PeB matches best the conserved receptor binding site of hemagglutinin. PeB bound also to other medical relevant influenza strains, such as human-pathogenic A/California/7/2009 H1N1, and avian-pathogenic A/MuteSwan/Rostock/R901/2006 H7N1. Strategies to improve the affinity and to adapt specificity are discussed and exemplified by a double amino acid substituted peptide, obtained by substitutional analysis. The peptides and their derivatives are of great potential for drug development as well as biosensing. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 536 KW - receptor-binding KW - A viruses KW - neutralizing antibody KW - avian influenza KW - origin KW - neuraminidase KW - invection KW - entry KW - sites KW - identification Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-410872 SN - 1866-8372 IS - 536 ER - TY - GEN A1 - Meyer, Sören A1 - Schulz, Jacqueline A1 - Jeibmann, Astrid A1 - Taleshi, Mojtaba S. A1 - Ebert, Franziska A1 - Francesconi, Kevin A1 - Schwerdtle, Tanja T1 - Arsenic-containing hydrocarbons are toxic in the in vivo model Drosophila melanogaster N2 - Arsenic-containing hydrocarbons (AsHC) constitute one group of arsenolipids that have been identified in seafood. In this first in vivo toxicity study for AsHCs, we show that AsHCs exert toxic effects in Drosophila melanogaster in a concentration range similar to that of arsenite. In contrast to arsenite, however, AsHCs cause developmental toxicity in the late developmental stages of Drosophila melanogaster. This work illustrates the need for a full characterisation of the toxicity of AsHCs in experimental animals to finally assess the risk to human health related to the presence of arsenolipids in seafood. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 183 KW - cod-liver KW - arsenolipids present KW - fatty-acids KW - rp-hplc KW - identification KW - fish KW - oil Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-76819 VL - 11 IS - 6 SP - 2010 EP - 2014 ER - TY - GEN A1 - Meyer, Sören A1 - Matissek, M. A1 - Müller, Sandra Marie A1 - Taleshi, M. S. A1 - Ebert, Franziska A1 - Francesconi, Kevin A. A1 - Schwerdtle, Tanja T1 - In vitro toxicological characterisation of three arsenic-containing hydrocarbons N2 - Arsenic-containing hydrocarbons are one group of fat-soluble organic arsenic compounds (arsenolipids) found in marine fish and other seafood. A risk assessment of arsenolipids is urgently needed, but has not been possible because of the total lack of toxicological data. In this study the cellular toxicity of three arsenic-containing hydrocarbons was investigated in cultured human bladder (UROtsa) and liver (HepG2) cells. Cytotoxicity of the arsenic-containing hydrocarbons was comparable to that of arsenite, which was applied as the toxic reference arsenical. A large cellular accumulation of arsenic, as measured by ICP-MS/MS, was observed after incubation of both cell lines with the arsenolipids. Moreover, the toxic mode of action shown by the three arsenic-containing hydrocarbons seemed to differ from that observed for arsenite. Evidence suggests that the high cytotoxic potential of the lipophilic arsenicals results from a decrease in the cellular energy level. This first in vitro based risk assessment cannot exclude a risk to human health related to the presence of arsenolipids in seafood, and indicates the urgent need for further toxicity studies in experimental animals to fully assess this possible risk. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - paper 170 KW - cod-liver KW - human-cells KW - arsenolipids present KW - excision-repair KW - fatty-acids KW - marine oils KW - RP-HPLC KW - metabolites KW - identification KW - trivalent Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-74201 SP - 1023 EP - 1033 ER - TY - THES A1 - Quade, Markus T1 - Symbolic regression for identification, prediction, and control of dynamical systems T1 - Symbolische Regression zur Identifikation, Vorhersage und Regelung dynamischer Systeme N2 - In the present work, we use symbolic regression for automated modeling of dynamical systems. Symbolic regression is a powerful and general method suitable for data-driven identification of mathematical expressions. In particular, the structure and parameters of those expressions are identified simultaneously. We consider two main variants of symbolic regression: sparse regression-based and genetic programming-based symbolic regression. Both are applied to identification, prediction and control of dynamical systems. We introduce a new methodology for the data-driven identification of nonlinear dynamics for systems undergoing abrupt changes. Building on a sparse regression algorithm derived earlier, the model after the change is defined as a minimum update with respect to a reference model of the system identified prior to the change. The technique is successfully exemplified on the chaotic Lorenz system and the van der Pol oscillator. Issues such as computational complexity, robustness against noise and requirements with respect to data volume are investigated. We show how symbolic regression can be used for time series prediction. Again, issues such as robustness against noise and convergence rate are investigated us- ing the harmonic oscillator as a toy problem. In combination with embedding, we demonstrate the prediction of a propagating front in coupled FitzHugh-Nagumo oscillators. Additionally, we show how we can enhance numerical weather predictions to commercially forecast power production of green energy power plants. We employ symbolic regression for synchronization control in coupled van der Pol oscillators. Different coupling topologies are investigated. We address issues such as plausibility and stability of the control laws found. The toolkit has been made open source and is used in turbulence control applications. Genetic programming based symbolic regression is very versatile and can be adapted to many optimization problems. The heuristic-based algorithm allows for cost efficient optimization of complex tasks. We emphasize the ability of symbolic regression to yield white-box models. In contrast to black-box models, such models are accessible and interpretable which allows the usage of established tool chains. N2 - In der vorliegenden Arbeit nutzen wird symbolische Regression zur automatisierten Modellierung dynamischer Systeme. Symbolische Regression ist eine mächtige und vielseitige Methode, welche zur Daten-getriebenen Identifikation von mathematischen Ausdrücken geeignet ist. Insbesondere werden dabei Struktur und Parameter des gesuchten Ausdrucks parallel ermittelt. Zwei Varianten der symbolischen Regression werden im Rahmen dieser Arbeit in Betracht gezogen: sparse regression und symbolischer Regression basierend auf genetischem Programmieren. Beide Verfahren werden für die Identifikation, Vor- hersage und Regelung dynamischer Systeme angewandt. Wir führen eine neue Methodik zur Identifikation von dynamischen Systemen, welche eine spontane Änderung erfahren, ein. Die Änderung eines Modells, wel- ches mit Hilfe von sparse regression gefunden wurde, ist definiert als sparsamste Aktualisierung im Hinblick auf das Modell vor der Änderung. Diese Technik ist beispielhaft am chaotischem Lorenz System und dem van der Pol Oszillator demonstriert. Aspekte wie numerische Komplexität, Robustheit gegenüber Rauschen sowie Anforderungen an Anzahl von Datenpunkten werden untersucht. Wir zeigen wie symbolische Regression zur Zeitreihenvorhersage genutzt wer- den kann. Wir nutzen dem harmonischen Oszillator als Beispielmodell, um Aspekte wie Robustheit gegenüber Rauschen sowie die Konvergenzrate der Optimierung zu untersuchen. Mit Hilfe von Einbettungsverfahren demonstrieren wir die Vorhersage propagierenden Fronten in gekoppelten FitzHugh-Nagumo Oszillatoren. Außerdem betrachten wir die kommerzielle Stromproduktionsvorhersage von erneuerbaren Energien. Wir zeigen wie man diesbezügliche die numerische Wettervorhersage mittels symbolischer Regression verfeinern und zur Stromproduktionsvorhersage anwenden kann. Wir setzen symbolische Regression zur Regelung von Synchronisation in gekoppelten van der Pol Oszillatoren ein. Dabei untersuchen wir verschiedene Topologien und Kopplungen. Wir betrachten Aspekte wie Plausibilität und Stabilität der gefundenen Regelungsgesetze. Die Software wurde veröffentlicht und wird u. a. zur Turbulenzregelung eingesetzt. Symbolische Regression basierend auf genetischem Programmieren ist sehr vielseitig und kann auf viele Optimierungsprobleme übertragen werden. Der auf Heuristik basierenden Algorithmus erlaubt die effiziente Optimierung von komplexen Fragestellungen. Wir betonen die Fähigkeit von symbolischer Regression, sogenannte white-box Modelle zu produzieren. Diese Modelle sind – im Gegensatz zu black-box Modellen – zugänglich und interpretierbar. Dies ermöglicht das weitere Nutzen von etablierten Methodiken. KW - dynamical systems KW - symbolic regression KW - genetic programming KW - identification KW - prediction KW - control KW - Dynamische Systeme KW - Symbolische Regression KW - Genetisches Programmieren KW - Identifikation KW - Vorhersage KW - Regelung Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-419790 ER - TY - GEN A1 - Nowak, Michael D. A1 - Russo, Giancarlo A1 - Schlapbach, Ralph A1 - Huu, Cuong Nguyen A1 - Lenhard, Michael A1 - Conti, Elena T1 - The draft genome of Primula veris yields insights into the molecular basis of heterostyly T2 - Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe N2 - Background The flowering plant Primula veris is a common spring blooming perennial that is widely cultivated throughout Europe. This species is an established model system in the study of the genetics, evolution, and ecology of heterostylous floral polymorphisms. Despite the long history of research focused on this and related species, the continued development of this system has been restricted due the absence of genomic and transcriptomic resources. Results We present here a de novo draft genome assembly of P. veris covering 301.8 Mb, or approximately 63% of the estimated 479.22 Mb genome, with an N50 contig size of 9.5 Kb, an N50 scaffold size of 164 Kb, and containing an estimated 19,507 genes. The results of a RADseq bulk segregant analysis allow for the confident identification of four genome scaffolds that are linked to the P. veris S-locus. RNAseq data from both P. veris and the closely related species P. vulgaris allow for the characterization of 113 candidate heterostyly genes that show significant floral morph-specific differential expression. One candidate gene of particular interest is a duplicated GLOBOSA homolog that may be unique to Primula (PveGLO2), and is completely silenced in L-morph flowers. Conclusions The P. veris genome represents the first genome assembled from a heterostylous species, and thus provides an immensely important resource for future studies focused on the evolution and genetic dissection of heterostyly. As the first genome assembled from the Primulaceae, the P. veris genome will also facilitate the expanded application of phylogenomic methods in this diverse family and the eudicots as a whole. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 879 KW - pollen flow KW - reproductive success KW - natural-populations KW - genetic-variation KW - breeding system KW - floral morph KW - evolution KW - vulgaris KW - identification KW - transcriptome KW - Genome Assembly KW - Veris KW - Transcriptome Assembly KW - Corolla Tube KW - Genome Scaffold Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-435088 SN - 1866-8372 IS - 879 ER -