Thèses : « Modul biologi »

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Nygren, Kristiina. « Evolutionary Consequences of Reproductive Strategies : Testing Theory on Sex and Reproductive Gene Evolution in the Fungal Model Neurospora ». Doctoral thesis, Uppsala universitet, Evolutionsbiologi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-152953.

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In this thesis, I used the filamentous ascomycete genus Neurospora as a model to test theoretical predictions on the evolutionary consequences of different reproductive strategies and reproductive gene evolution. The genus Neurospora contains taxa representing a diversity of reproductive strategies, and here I constructed a phylogeny by which I was able to show that several independent transitions in reproductive mode have occurred in the evolutionary history of the genus. This feature makes Neurospora a suitable model for the evolution of reproductive modes. Molecular evolutionary analysis of housekeeping genes revealed an accelerated protein evolution in the highly inbreeding homothallic taxa, in accordance with theory predictions of lower efficiency of selection in asexual and highly inbreeding taxa. Furthermore, self-sterile (heterothallic) taxa capable of asexual propagation was found to be associated with a three-fold higher neutral substitution rate, indicative of a higher mutation accumulation due to elevated number of cell divisions per unit time in these taxa. Further, I have shown a general pattern of rapid evolution of genes involved in reproduction in Neurospora, thus extending the pattern of general high divergence of reproductive genes previously well known in animals, to fungi. Two rapidly evolving reproductive genes: the pheromone receptor genes pre-1 and pre-2 involved in mate recognition were studied in detail. For the gene pre-1 the rapid divergence was found to be driven by positive selection in both heterothallic and homothallic taxa. The rapid divergence of the pheromone receptor gene pre-2 cannot be explained by positive selection and for this gene a subtle differences in evolutionary constraints between heterothallic and homothallic taxa were found. The general similarity in evolutionary constraints of pre-genes in taxa of both mating-systems indicates that these genes serve other functions beside mate recognition.

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Borrvall, Charlotte. « Biodiversity and Species Extinctions in Model Food Webs ». Doctoral thesis, Linköping : Department of Physics, Chemistry and Biology, Linköping University, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-6660.

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Marín, de Mas Igor Bartolomé. « Development and application of novel model-driven and data-driven approaches to study metabolism in the framework of systems medicine ». Doctoral thesis, Universitat de Barcelona, 2015. http://hdl.handle.net/10803/296313.

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The general aim of this thesis is to develop and apply new computational tools to overcome existing limitations in the analysis of metabolism. This thesis is focused on developing new computational strategies to overcome the following identified limitations: i) The existing metabolic flux analysis tools does not account for the existence of metabolic channeling: Here we developed a new computational tool based on non-stationary 13 C-FBA to evaluate different models reflecting different topologies of intracellular metabolism, using the channeling in hepatocytes as case of concep ii) Metabolic drug-target discovery based on GSMM does not consider the different cell subpopulations existing within the tumor: Here we develope a method that integrate trancriptomic data into a comparative genome-scale metabolic network reconstruction analysis in the context of intra-tumoral heterogeneity . We determined subpopulation-specific drug targets . Additionally we determined a metabolic gene signature associated to tumor progression in pc that was correlated with other types of cancer. Iii) Current mechanistic and probabilistic computational approaches are not suitable to study the complexity of the crosstalk between metabolic and gene regulatory networks.: Here we developed a novel computational method combining probabilistic and mechanistic approaches to integrate multi-level omic data into a discrete model-based analysis. This method allowed to analyze the mechanism underlying the crosstalk between metabolism and gene regulation, using as case of concept the study of the abnormal adaptation to training in COPD patients.
La presente tesis doctoral se centra en el desarrollo de herramientas computacionales que permitan el estudio de los mecanismos moleculares que ocurren dentro de la célula. Mas específicamente estudia el metabolismo celular desde diferentes puntos de vista usando y desarrollando métodos computacionales basados en diversas metodologías. Así pues en un primer capitulo se desarrolla un método basado en el analista de los flujos metabólicos en estado no estacional isotópico utilizando modelos cinéticos para estudiar el fenómeno de la canalización metabólica en hepatocitos. Este fenómeno modifica la topología metabólica alterando el fenotipo. Nuestro método nos permitió discriminar varios modelos con distintas topología prediciendo la existencia de canalización metabólica en la glucólisis. En el segundo capitulo se desarrolló un método para analizar el metabolismo tumoral teniendo en cuenta la heterogeneidad de poblaciones. En concreto estudiamos dos subpoblaciones extraídas de una linea celular de cáncer de próstata. Para ello utilizamos un modelo a gran escala de todo el metabolismo celular humano. El análisis reflejó la existencia de diferencias notables a nivel de vías metabólicas concretas, confiriendo a cada subpoblacion sensibilidades distintas a diferentes fármacos. En esta linea se demostró que mientras las células PC-3M eran sensibles al etomoxir e insensibles al calcitriol, las PC-3S presentaban una sensibilidad opuesta. En el tercero y ultimo capitulo de la tesis desarrollamos un nuevo método computacional que integra aproximaciones probabilísticas y mecanicistas para integrar diferentes tipos de datos en un análisis basado en modelos discretos. Para ello utilizamos como caso de concepto el estudio de la adaptación anómala al entrenamiento de pacientes con EPOC. El análisis reveló diferencias importantes a nivel de metabolismo energético en comparación con el grupo control.

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Ferrández, Roldán Alfonso. « Deconstruction of the cardiopharyngeal gene regulatory network in appendicularians, a paradigmatic study of Oikopleura dioica as an evolutionary knockout model ». Doctoral thesis, Universitat de Barcelona, 2021. http://hdl.handle.net/10803/672832.

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The bloom of genomic data has revealed a vast amount of gene losses across all life kingdoms. However, the impact of gene loss on the evolution of the mechanisms of embryo development remains an important challenge. In this work, we have used the successful gene loser Oikopleura dioica, to study the impact of gene loss on the evolution of the cardiopharyngeal gene regulatory network (GRN), and we have extrapolated our results to decipher the ancestral condition of tunicates as free-living or sessile, a hot topic of discussion. To address this question, we have searched for gene losses by combining best reciprocal blast hit (BRBH) with exhaustive phylogenetic reconstructions of the gene family of interest. We have also performed expression analyses of the present orthologs to test for their cardiac function as well as, in the case of lost orthologs, with paralogs trying to detect potential events of function shuffling. Finally, we performed functional analyses by inhibiting the FGF and BMP signaling pathways and started the implementation of a microinjection facility for future functional analyses by gene targeting. Our results show a clear deconstruction of the cardiopharyngeal GRN with the loss of many genes (Mesp, Ets1/2a, Gata4/5/6, Mek1/2, Tbx1/10, and RA- and FGF-signaling related genes) and cardiac subfunctions (FoxF, Islet, Ebf, Mrf, Dach, and Bmp signaling) crucial for cardiopharyngeal development in ascidians and vertebrates. All these losses have led to the dismantling of two genetic modules related to the maintenance of multipotency in the cardiopharyngeal precursors. This has been accompanied by the loss of the second heart field and pharyngeal muscles in appendicularians, which has been phenotypically translated into an open bilaminar heart with an accelerated development compared to the tubular heart present in the rest of chordates. The deconstruction of the cardiopharyngeal GRN in appendicularians can therefore be interpreted as an evolutionary adaptation to the transition from a sessile to a free-living lifestyle based on the innovation of the filter-feeding house. Therefore, our results show O. dioica as a paradigmatic example of the advantages of using species that along their evolution has lost many genes (evolutionary knockout models, eKO) to better understand the evolution of GRNs, mechanisms of embryo development, or any physiological adaptation in the absence of any given gene of interest.

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MACEDO, JOSE ANTONIO FERNANDES DE. « A CONCEPTUAL MODEL FOR MOLECULAR BIOLOGY ». PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2005. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=7939@1.

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Projetos de genômica e biológica molecular estão gerando dados cujos volumes e complexidades jamais foram observados nesta área. Além disso, fontes de dados e de conhecimento são produzidas e utilizadas por grupos de pesquisa os quais utilizam terminologias diferentes (sinônimos, apelido e fórmulas), sintaxes diferentes (estrutura de arquivos e separadores) e semânticas diferentes (intra e interdisciplinares homônimos). O sucesso da pesquisa em biologia dependerá da correta representação e manipulação dos dados biológicos permitindo os cientistas criarem, gerenciarem, manipularem, integrarem e analisarem os dados de forma a gerar informação e conhecimento. Neste trabalho, estudamos os problemas para representação de dados biológicos apresentados nas principais linguagens de modelagem tradicionais. Em seguida, levantamos os requisitos para um novo modelo de dados conceitual para biologia molecular. Finalmente, propomos um novo modelo conceitual contendo construtores específicos para solucionar alguns dos problemas estudados. Além disso, formalizamos o modelo proposto usando lógica de primeira ordem e utilizamos esta descrição lógica para realizar inferências que auxiliem o trabalho do projetista de banco de dados durante a criação de um esquema de banco de dados.
Genomic and molecular biology projects are generating knowledge data whose volume and complexity are unparalleled in this research area. In addition, data and knoweledge sources produced and used by research groups have terminological differences (synonyms, aliases and formulae), syntactic differences (file structure, separators and spelling) and semantic differences (intra- and interdisciplinary homonyms). In this context, data management techniques play a fundamental role for biological applications development because it offers adequate abstractions to desing, implement, access and manage data, in order to generate knowledge. In this work, we study the representation problems presentd in traditional languages. Following, we raise the main requiremants for a new conceptual data model specially conceived for molecular biology. Finally, we propose a new conceptual data model with special types of constructor tryng to solve some of the representation problems discurssed before. In addition, we formalize our proposed model using first-order logic and we use this logical description to infer some properties that may help database designer during the elaboration of database schema.

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Browning, Alexander P. « Model complexity in biology and bioengineering ». Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/227787/1/Alexander_Browning_Thesis.pdf.

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In biology and bioengineering, mathematical and statistical analysis provides an understanding of biological systems that enables their control and manipulation. Tailoring mathematical and experimental complexity to the biological question of interest is crucial to avoid issues relating to parameter identifiability. We develop models and tools to bring new data-based insights to a range of contemporary problems in biology and bioengineering. These include data-focused stochastic models that describe complex cell interactions and decision making, incorporating biological systems into new engineered materials, and new tools to diagnose parameter identifiability and guide model complexity for stochastic differential equation models.

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Johannes, Eleanor M. « Voice, disability and inclusion : a case study of biology learners with cerebral palsy ». Thesis, University of the Western Cape, 2006. http://etd.uwc.ac.za/index.php?module=etd&amp.

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This study attempted to ascertain whether the under-representation of black, disadvantaged learners with cerebral palsy in biology and related careers is linked in any way to the method and content of teaching and learning in special education. In addition this study also attempted to identify and uncover the barriers that prevent learners with cerebral palsy from pursuing careers in science and technology related professions.

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Ziehm, Matthias Fritz. « Computational biology of longevity in model organisms ». Thesis, University of Cambridge, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.648888.

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Nylander, Johan A. A. « Bayesian Phylogenetics and the Evolution of Gall Wasps ». Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-3996.

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Paulsen, Jon Rune. « Optimal Information Retrieval Model for Molecular Biology Information ». Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2007. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-8718.

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Search engines for biological information are not a new technology. Since the 1960s computers have emerged as an important tool for biologists. Online Mendelian Inheritance in Man (OMIM) is a comprehensive catalogue containing approximately 14 000 records with information about human genes and genetic disorders. An approach called Latent Semantic Indexing (LSI) was introduced in 1990 that is based on Singular Value Decomposition (SVD). This approach improved the information retrieval and reduced the storage requirements. This thesis applies LSI on the collection of OMIM records. To further improve the retrieval effectiveness and efficiency, the author propose a clustering method based on the standard k-means algorithm, called Two step k-means. Both the standard k-means and the Two step k-means algorithms are tested and compared with each other.

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Santos, Elmer Buluran. « Biologic response to papillomavirus DNA in COPV model ». Thesis, University of Cambridge, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.621132.

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Li, Yifei. « Nonlinear diffusion in mathematical biology ». Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/234381/1/Yifei_Li_Thesis.pdf.

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Reaction-diffusion models with nonlinear diffusion are widely used for studying population dynamics in biology and ecology. Yet, the relationship between nonlinear diffusion mechanisms in populations and the behaviours of individuals is hard to be intuitively interpreted in classical models. To address this problem, we develop a discrete-continuum modelling framework, where the movement of individuals influenced by crowding effects is connected to the nonlinear diffusivity functions in a well-defined continuum limit. Using this framework, we explore the influence of nonlinear diffusion on population extinction, and analyse the existence and stability of travelling waves in continuous equations which model the invasion process.

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Coskun, Sarp Arda. « PATHCASE-SB MODEL SIMULATION AND MODEL COMPOSITION TOOLS FOR SYSTEMS BIOLOGY MODELS ». Case Western Reserve University School of Graduate Studies / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=case1328556115.

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Foguet, Coll Carles. « Development of model-driven approaches for metabolic flux analysis and anticancer drug discovery ». Doctoral thesis, Universitat de Barcelona, 2019. http://hdl.handle.net/10803/668644.

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Metabolism is a hallmark of life and underlies most biological processes in both health and disease. For instance, dysregulation of liver metabolism underlies multifactorial disorders such as diabetes or obesity. Similarly, cancer progression involves a reprogramming of metabolism to support unchecked proliferation, metastatic spread and other facets of the cancer phenotype. Hence, the study of metabolism is of great biomedical interest. The metabolic phenotype emerges from the complex interactions of metabolites, enzymes, and the signaling cascades regulating their expression and thus must be studied following a holistic approach. With this aim, Systems Biology formulates the interactions between the molecular components of metabolism as a set of mathematical expressions, termed metabolic models, and uses them as a framework to integrate multiple layers of data (e.g., transcriptomics, proteomics and metabolomics) and simulate the emergent metabolic phenotype. The Systems Biology toolbox for the analysis of metabolism consists of several complementary model-based approaches, each with its strengths and limitations. For instance, constraint-based modeling can predict flux distributions at a genome-scale, whereas kinetic modeling and 13C metabolic flux analysis (13C MFA) can more accurately model central carbon metabolism. As part of this Ph.D. thesis, we have expanded this toolbox through the development of new model-based approaches for computing both detailed metabolic maps of central carbon metabolism and genome-scale flux maps. With this aim, we developed HepatoDyn, a highly detailed kinetic model of hepatocyte metabolism capable of dynamic 13C MFA and used it to characterize the negative effects of fructose in hepatic metabolic function. Similarly, we also developed Iso2Flux, a novel steady-state 13C MFA software, and parsimonious 13C MFA, a new 13C MFA algorithm that can integrate transcriptomics to trace flux through large metabolic networks. Even more, we developed r2MTA a constraint-based modeling algorithm to robustly identify the optimal interventions to induce a transition towards a therapeutically desirable metabolic state. Finally, we also developed a workflow for integrating transcriptomics, metabolomics, gene dependencies, and 13C MFA to predict genome-scale flux maps. Furthermore, we apply the systems biology toolbox, using both newly developed and existing tools, to the genome-scale analysis of the molecular drivers underlying cancer stem cells and metastasis in prostate and colorectal cancer, respectively. We identify putative therapeutic interventions against both phenotypes paving the way for a new generation of anticancer drugs.

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Jin, Wang. « Investigating the reproducibility of in vitro cell biology assays using mathematical models ». Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/109790/1/Wang_Jin_Thesis.pdf.

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In vitro cell biology assays are routinely used to study cancer spreading, drug design and tissue repair. However, issues associated with reproducibility are reported in literature. In this thesis we investigate the overlooked source of variability that affects the reproducibility of cell biology assays, using a combined mathematical and experimental approach. By calibrating mathematical models to experimental data, we find that the initial degree of confluence significantly affects cell motility. Following the similar approach, we identify the two-phase growth in scratch assays. We then propose a proliferation mechanism for lattice-based, random walk models, which accounts for biologically more realistic crowding effects. At last, we use a lattice-based, random walk model to mimic the passaging process and find that the passage number could significantly affect the wound closure in scratch assays.

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Demattè, Lorenzo. « Scaling up Systems Biology : Model Construction, Simulation and Visualization ». Doctoral thesis, Università degli studi di Trento, 2010. https://hdl.handle.net/11572/369136.

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Being a multi-disciplinary field of research, Systems Biology struggle to have a common view and a common vocabulary, and inevitably people coming from different backgrounds see and care about different aspects. Scientists have to work hard to comprehend each other and to take advantage of each others work, but on the other hand they can provide unexpected and beautiful new insight to the problems we have to face, enabling cross-fertilization among different disciplines. However, Systems Biology scientists all share one main goal, in the end: comprehend how a system as complex as a living creature can work and exists. Once we really understand how and why a biological system works, we can answer other important questions: can we fix it when it breaks down; can we enhance it and make it more resistant, correct its flaws; can we reproduce its behaviour and take it as inspiration for new works of engineering; can we copy it to make our everyday work easier and our human-created systems more reliable. The contribution of this thesis is to push ahead the current state of art in different areas of information technology and computer science as applied to systems biology, in a way that could lead, one day, to the understanding of a whole, complex biological system. In particular, this thesis builds upon the current state of art of different disciplines, like programming languages theory and implementation, parallel computing, software engineering and visualization. Work done in these areas is applied to Systems Biology, in the effort to scale up the dimension of the problems that is possible to tackle with current tools and techniques.

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Dematté, Lorenzo. « Scaling up Systems Biology : Model Construction, Simulation and Visualization ». Doctoral thesis, University of Trento, 2010. http://eprints-phd.biblio.unitn.it/258/1/PhD-Thesis.pdf.

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Being a multi-disciplinary field of research, Systems Biology struggle to have a common view and a common vocabulary, and inevitably people coming from different backgrounds see and care about different aspects. Scientists have to work hard to comprehend each other and to take advantage of each others work, but on the other hand they can provide unexpected and beautiful new insight to the problems we have to face, enabling cross-fertilization among different disciplines. However, Systems Biology scientists all share one main goal, in the end: comprehend how a system as complex as a living creature can work and exists. Once we really understand how and why a biological system works, we can answer other important questions: can we fix it when it breaks down; can we enhance it and make it more resistant, correct its flaws; can we reproduce its behaviour and take it as inspiration for new works of engineering; can we copy it to make our everyday work easier and our human-created systems more reliable. The contribution of this thesis is to push ahead the current state of art in different areas of information technology and computer science as applied to systems biology, in a way that could lead, one day, to the understanding of a whole, complex biological system. In particular, this thesis builds upon the current state of art of different disciplines, like programming languages theory and implementation, parallel computing, software engineering and visualization. Work done in these areas is applied to Systems Biology, in the effort to scale up the dimension of the problems that is possible to tackle with current tools and techniques.

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Vogel, Ivan. « Aplikace pro zpracování dat z oblasti evoluční biologie ». Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-235533.

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Phylogenetic tree inference is a very common method for visualising evolutionary relationships among species. This work focuses on explanation of mathematical theory behind molecular phylogenetics as well as design of a modified algorithm for phylogenetic tree inference based on intra-group analysis of nucleotide and amino acid sequences. Furthermore, it describes the object design and implementation of the proposed methods in Python language, as well as its integration into powerful bioinformatic portal. The proposed modified algorithmic solutions give better results comparing to standard methods, especially on the field of clustering of predefined groups. Finally, future work as well as an application of proposed methods to other fields of information technology are discussed.

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Veliz-Cuba, Alan A. « The Algebra of Systems Biology ». Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/28240.

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In order to understand biochemical networks we need to know not only how their parts work but also how they interact with each other. The goal of systems biology is to look at biological systems as a whole to understand how interactions of the parts can give rise to complex dynamics. In order to do this efficiently, new techniques have to be developed. This work shows how tools from mathematics are suitable to study problems in systems biology such as modeling, dynamics prediction, reverse engineering and many others. The advantage of using mathematical tools is that there is a large number of theory, algorithms and software available. This work focuses on how algebra can contribute to answer questions arising from systems biology.
Ph. D.

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Naruse, Kiyoshi, Mitsuru Sakaizumi et Akihiro Shima. « Medaka as a model organism for research in experimental biology ». Laboratory of Freshwater Fish Stocks Bioscience Center Nagoya University, 1994. http://hdl.handle.net/2237/13792.

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Karlstädt, Anja [Verfasser]. « A systems biology approach to model cardiomyocyte metabolism / Anja Karlstädt ». Berlin : Medizinische Fakultät Charité - Universitätsmedizin Berlin, 2013. http://d-nb.info/1043197656/34.

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Konieczka, Jay, Kevin Drew, Alex Pine, Kevin Belasco, Sean Davey, Tatiana Yatskievych, Richard Bonneau et Parker Antin. « BioNetBuilder2.0 : bringing systems biology to chicken and other model organisms ». BioMed Central, 2009. http://hdl.handle.net/10150/610006.

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BACKGROUND:Systems Biology research tools, such as Cytoscape, have greatly extended the reach of genomic research. By providing platforms to integrate data with molecular interaction networks, researchers can more rapidly begin interpretation of large data sets collected for a system of interest. BioNetBuilder is an open-source client-server Cytoscape plugin that automatically integrates molecular interactions from all major public interaction databases and serves them directly to the user's Cytoscape environment. Until recently however, chicken and other eukaryotic model systems had little interaction data available.RESULTS:Version 2.0 of BioNetBuilder includes a redesigned synonyms resolution engine that enables transfer and integration of interactions across species
this engine translates between alternate gene names as well as between orthologs in multiple species. Additionally, BioNetBuilder is now implemented to be part of the Gaggle, thereby allowing seamless communication of interaction data to any software implementing the widely used Gaggle software. Using BioNetBuilder, we constructed a chicken interactome possessing 72,000 interactions among 8,140 genes directly in the Cytoscape environment. In this paper, we present a tutorial on how to do so and analysis of a specific use case.CONCLUSION:BioNetBuilder 2.0 provides numerous user-friendly systems biology tools that were otherwise inaccessible to researchers in chicken genomics, as well as other model systems. We provide a detailed tutorial spanning all required steps in the analysis. BioNetBuilder 2.0, the tools for maintaining its data bases, standard operating procedures for creating local copies of its back-end data bases, as well as all of the Gaggle and Cytoscape codes required, are open-source and freely available at http://err.bio.nyu.edu/cytoscape/bionetbuilder/ webcite.

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Hinneburg, Detlef, et Nicole Mölders. « A mesoscale atmospheric model combining meteorology, chemistry, biology, and heterogeneity ». Universitätsbibliothek Leipzig, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-213743.

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A mesoscale non-hydrostatic atmospheric model was extended by including both a chemical transport module (CTM) for the chemical triade NO, N02, and 0 3, and an explicit surface-subgrid module (ESSM) for a subscale resolution of the topographical surface. CTEM: The simulated time-dependent concentration fields result from the following processes involved: anthropogenic emission at different heights, biogenic emission, dry deposition on the receptive surface, chemical reactions, turbulent diffusion, and passive transport according to the model dynamics. The calculations in the lowest model layer, usually treated as a constant-flux layer, are now performed on a vertical subgrid that was inserted to better resolve the often observed high concentration gradients within the surface layer. ESSM: Moreover, an equidistant horizontal-subgrid is introduced for finer resolving the topography. The surface fluxes of momentum, sensible and latent heat, long-wave radiation, soil heat flux and wetness as well as the surf ace-energy balance are calculated in the usual approximations, however, employing the individual surface and soil properties of the subgrid cells. The averaged subgrid quantities serve as boundary values required for the model-grid calculations. Within the CTM the ESSM method leads to an intersection of the horizontal ESSM subgrid and the vertical CTM subgrid. Preliminary results representing an interim realization state of the ESSM demonstrate partially strong changes of the dry deposition rates caused by subgrid-resolved surface properties
Ein mesoskaliges nicht-hydrostatisches Atmosphärenmodell ist um ein Chemie-TransportModul (CTM) zur Berücksichtigung der Triaden-Komponenten NO, N02 und 03 sowie um ein Verfahren zur verfeinerten Auflösung der topographischen Unterlage (explicit surface-subgrid modul ESSM) erweitert worden. CTM: Die simulierten zeitabhängigen Konzentrationsfelder sind das Resultat folgender modellierter Prozesse: Anthropogene Emission in verschiedenen Höhenschichten, biogene Emission, trockene Deposition (Rezeption), die speziellen chemischen Umwandlungen, turbulente Diffusion und passiver Transport. Da der Schwerpunkt der Prozesse und die höchsten Konzentrationsgradienten innerhalb der bodennahen ersten Modellschicht vorliegen, werden die Berechnungen in dieser Schicht auf einem verfeinerten vertikalen Untergitter durchgeführt. ESSM: Unabhängig von den Eigenheiten des CTM wird für alle untergrundbezogenen meteorologischen Größen ein regelmäßiges horizontales Untergitter zwecks Berücksichtigung des subskalig aufgelösten topographischen Untergrundes eingeführt. Auf diesem Untergitter werden in den bisherigen Näherungen alle Oberflächenflüsse für Impuls, fühlbare und latente Wärme, langwellige Strahlung, der Bodenwärmefluß, die Bodenfeuchte sowie die Energiebilanz am Boden berechnet. Die über die Untergitterzellen gemittelten Werte dienen den weiteren Berechnungen im normalen Modellgitter als die erforderlichen Randwerte. Innerhalb des CTM führt die ESSM-Methode zu einer Überlagerung des vertikalen CTM-Untergitters mit dem horizontalen Untergitter des ESSM. Erste Simulationsergebnisse, die dem derzeitigen Stand in der Realisierung des ESSM entsprechen, erbringen teilweise stark veränderte Depositionsraten infolge der Berücksichtigung der horizontal feiner aufgelösten Topographie

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Hinneburg, Detlef, et Nicole Mölders. « A mesoscale atmospheric model combining meteorology, chemistry, biology, and heterogeneity ». Wissenschaftliche Mitteilungen des Leipziger Instituts für Meteorologie ; 12 = Meteorologische Arbeiten aus Leipzig ; 4 (1999), S. 44-58, 1999. https://ul.qucosa.de/id/qucosa%3A15094.

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A mesoscale non-hydrostatic atmospheric model was extended by including both a chemical transport module (CTM) for the chemical triade NO, N02, and 0 3, and an explicit surface-subgrid module (ESSM) for a subscale resolution of the topographical surface. CTEM: The simulated time-dependent concentration fields result from the following processes involved: anthropogenic emission at different heights, biogenic emission, dry deposition on the receptive surface, chemical reactions, turbulent diffusion, and passive transport according to the model dynamics. The calculations in the lowest model layer, usually treated as a constant-flux layer, are now performed on a vertical subgrid that was inserted to better resolve the often observed high concentration gradients within the surface layer. ESSM: Moreover, an equidistant horizontal-subgrid is introduced for finer resolving the topography. The surface fluxes of momentum, sensible and latent heat, long-wave radiation, soil heat flux and wetness as well as the surf ace-energy balance are calculated in the usual approximations, however, employing the individual surface and soil properties of the subgrid cells. The averaged subgrid quantities serve as boundary values required for the model-grid calculations. Within the CTM the ESSM method leads to an intersection of the horizontal ESSM subgrid and the vertical CTM subgrid. Preliminary results representing an interim realization state of the ESSM demonstrate partially strong changes of the dry deposition rates caused by subgrid-resolved surface properties.
Ein mesoskaliges nicht-hydrostatisches Atmosphärenmodell ist um ein Chemie-TransportModul (CTM) zur Berücksichtigung der Triaden-Komponenten NO, N02 und 03 sowie um ein Verfahren zur verfeinerten Auflösung der topographischen Unterlage (explicit surface-subgrid modul ESSM) erweitert worden. CTM: Die simulierten zeitabhängigen Konzentrationsfelder sind das Resultat folgender modellierter Prozesse: Anthropogene Emission in verschiedenen Höhenschichten, biogene Emission, trockene Deposition (Rezeption), die speziellen chemischen Umwandlungen, turbulente Diffusion und passiver Transport. Da der Schwerpunkt der Prozesse und die höchsten Konzentrationsgradienten innerhalb der bodennahen ersten Modellschicht vorliegen, werden die Berechnungen in dieser Schicht auf einem verfeinerten vertikalen Untergitter durchgeführt. ESSM: Unabhängig von den Eigenheiten des CTM wird für alle untergrundbezogenen meteorologischen Größen ein regelmäßiges horizontales Untergitter zwecks Berücksichtigung des subskalig aufgelösten topographischen Untergrundes eingeführt. Auf diesem Untergitter werden in den bisherigen Näherungen alle Oberflächenflüsse für Impuls, fühlbare und latente Wärme, langwellige Strahlung, der Bodenwärmefluß, die Bodenfeuchte sowie die Energiebilanz am Boden berechnet. Die über die Untergitterzellen gemittelten Werte dienen den weiteren Berechnungen im normalen Modellgitter als die erforderlichen Randwerte. Innerhalb des CTM führt die ESSM-Methode zu einer Überlagerung des vertikalen CTM-Untergitters mit dem horizontalen Untergitter des ESSM. Erste Simulationsergebnisse, die dem derzeitigen Stand in der Realisierung des ESSM entsprechen, erbringen teilweise stark veränderte Depositionsraten infolge der Berücksichtigung der horizontal feiner aufgelösten Topographie.

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Patitucci, Cecilia. « PPARy, a new player in hepatic metabolic adaptation from mouse model to human liver cancer ». Thesis, Sorbonne Paris Cité, 2016. http://www.theses.fr/2016USPCB056/document.

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La tumorigenèse est influencée par des facteurs génétiques et environmentaux. La surnutrition est une cause d'obésité et d'accumulation pathologique de lipides dans le foie, la stéatose, qui peut évoluer en stéato-hépatite. Obésité et stéato-hépatite contribuent à l'augmentation de l'incidence du diabète dans le monde entier. Le diabète et l'obésité sont des facteurs de risque pour le cancer du foie (El-Serag et al., Clin Gastroenterol Hepatol, 2006). Cet projet de thèse élucide les mécanismes moléculaires liant l'activation de la voie de signalisation de l'insuline, les maladies du foie gras et le développement du cancer du foie, et il propose de nouvelles stratégies thérapeutiques. La délétion hépato-spécifique du gène codant le suppresseur de tumeurs Phosphatase and tensin homolog (PTEN) est un modèle de cancer du foie associé à la stéatose (Horie et al., J Clin Invest, 2004). Nous avons utilisé ce modèle, où la cascade de signalisation PI3K/mTOR est activée, pour démontrer que l'induction de l'expression du facteur de transcription et récepteur nucléaire Peroxysome Proliferator-Activated Receptor gamma (PPARγ) est responsable de la stéatose et de la glycolyse aérobie (effet Warburg). Son activité est spécifiquement dépendente de l'activité d'un effectuer en aval de la voie PI3K/mTOR, la protéine sérine/thréonine kinase, AKT2 (Panasyuk et al., Nat Comm, 2012). Sur la base de ces observations, nous avons construit l'hypothèse que PPARγ est un important régulateur de la croissance pathologique et du développement des adénocarcinomes hépatiques associés aux stéato-hépatites. Avec mon travail de thèse j'ai pu démontrer que l'expression et l'activité de PPARγ sont essentielles pour le développement du cancer du foie dans le modèle de souris invalidées pour PTEN dans les hépatocytes. Par ailleurs, la délétion de PPARγ dans le foie dépourvu de PTEN joue un rôle protecteur de la tumorigenèse, confirmant que PPARγ est effectivement placé en aval de AKT2. De plus, nous avons découvert que PPARγ est induit dans des échantillons de carcinome hépatocellulaire humains. Ces échantillons sont caractérisés par leur agressivité (haut taux prolifératif et bas niveau de différentiation) et aussi par l'activation de la voie PI3K/AKT. L'analyse des échantillons humains au stade pré-carcinome (adénomes) nous a permis de démontrer que l'ARN de PPARγ est le plus exprimé dans les adénomes caractérisés par un haut degré de stéatose. Ils sont caractérisés par la perte de fonction du facteur de transcription Hepatocyte Nuclear Factor 1α (HNF1α). Nous avons identifié HNF1α comment un nouveau régulateur négatif de la transcription de PPARγ. Nous avons aussi découvert que l'expression et l'activité de HNF1α sont inhibées par AKT2, induisant l'expression de PPARγ et son activité pro-tumorigénique. Finalement, la sensitibilité de PPARγ aux ligands, naturels et exogènes, nous a encouragé à tester des traitements pharmacologiques pour moduler son activation. La stimulation de l'activité de PPARγ avec l'agoniste synthétique Pioglitazone a conduit à une aggravation des symptomes dans le foie. Par contre, son inhibition par un antagoniste sélectif, SR2595, était thérapeutique, resultant en une réduction de signes pré-tumoraux et tumoraux dans le foie des souris invalidé par PTEN. En résumé, nos études chez l'humain et la souris, révèlent une nouvelle signature d'interaction entre les facteurs de transcription HNF1α et PPARγ et la voie de signalisation de l'insuline, suggérant de nouvelles stratégies thérapeutiques possibles pour le traitement d'une sous-classe spécifique de cancer du foie lié aux stéato-hépatites
Tumorigenesis is influenced by genetic and environmental factors. Overnutrition leads to obesity and fatty liver disease, contributing to increase diabetes incidence worldwide. Diabetes and obesity are independent risk factors for liver cancer development (El-Serag et al., Clin Gastroenterol Hepatol, 2006). This PhD project elucidates the molecular mechanisms linking activated insulin signalling pathway, fatty liver disease and liver cancer development and proposes novel therapeutic strategies. The hepatocytes-specific deletion of tumour suppressor Phosphatase and tensin homolog (PTEN) is a model of steatosis-associated liver cancer (Horie et al., J Clin Invest, 2004). Using this model of activated PI3K/mTOR signalling, our laboratory discovered that the nuclear receptor transcription factor Proliferator-Activated Receptor gamma (PPARγ) is induced in PTEN-null liver. My group demonstrated that in the liver PPARγ contributes to steatosis and aerobic glycolysis. Its activity specifically requires a downstream effector in the PI3K/mTOR pathway, the serine/threonine-specific protein kinase AKT2 (Panasyuk et al., Nat Comm, 2012). Based on these observations, we hypothesized that PPARγ might be an important regulator of pathological growth and development of steatohepatitis-associated liver adenocarcinomas. In my PhD work, I demonstrated that PPARγ expression and activity is essential for liver cancer in PTEN mutants. Moreover, PPARγ is induced in human samples of Hepatocellular Carcinoma (HCC) characterized by poor differentiation accompanied by the activation of PI3K/AKT pathway. We could attribute to PPARγ a specific role in tumour formation as it is required for abnormal liver growth and steatosis in mice at pre-tumoral age. In addition, deletion of PPARγ in PTEN mutants protected animals form liver tumorigenesis placing PPARγ downstream of activated AKT2. Analysing human samples of pre-carcinoma lesions characterized by high steatotic rate, we demonstrated that PPARγ transcript levels are increased in a specific subgroup of adenomas characterized by loss-of-function mutations in the Hepatocyte Nuclear Factor 1α (HNF1α). We identified HNF1α as a novel direct negative regulator of PPARγ transcription. We also revealed HNF1α expression and activity inhibited by AKT2 and thereby inducing PPARγ pro-tumorigenic action. Finally, the sensitivity of PPARγ to natural and exogenous ligands encouraged us to perform treatments to pharmacologically modulate PPARγ activity. Further activation of PPARγ with its synthetic ligand pioglitazione dramatically aggravates liver disease. While PPARγ inhibition by selective antagonist SR2595 allowed to reduce the pre-tumoral and tumoral signs of PTEN-null mice. In sum, our studies in men and mice reveal a novel pro-tumorigenic network of transcription factors HNF1α and PPARγ downstream of activated insulin signalling pathway, suggesting possible strategies for treatment of a subgroup of steatohepatitis-associated liver cancer

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Schutte, Brian J. « Biology and ecology of Ambrosia Trifida L. seedling emergence ». The Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=osu1181937971.

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Kallner, Bastviken Sofia. « Nitrogen removal in treatment wetlands : Factors influencing spatial and temporal variations ». Doctoral thesis, Linköpings universitet, Ekologi, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-7564.

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Decreasing the nitrogen transport from land to surrounding seas is a major task throughout the world to limit eutrophication of the coastal areas. Several approaches are currently used, including the establishment of wetlands, to decrease the transport of nitrogen. Wetlands represent ecosystems where the nitrogen removal from water can be efficient given that they are appropriately designed. The aim of this thesis was to investigate and quantify the effect of critical factors that regulate the nitrogen removal in wetlands, and to develop better guidelines for wetland design. Studies were performed at different scales, from microcosms to full scale wetlands, and methods included modelling, mass balance calculations and process studies. A first order rate model was used to simulate the nitrogen transformations in two large wetlands treating wastewater containing both ammonium and nitrate nitrogen. It was found that the dynamics of the main itrogen transformation processes could not be satisfactorily described using this approach. Large wetlands containing vegetation are complex ecosystems, and the process rates vary in both time and space. The great diversity of microenvironments favours different nitrogen processes, and large differences in potential nitrification and denitrification rates were found between different surface structures within a wetland. The results from microcosms measurements showed that the highest potential for nitrification was on surfaces in the water column, while the denitrification capacity was highest in the sediment. For the sediment denitrification capacity, the plant community composition was shown to be of major importance primarily by supplying litter serving as a carbon and energy source, and/or attachment surfaces, for denitrifying bacteria. Denitrification rates may be affected more than three fold by different types of litter and detritus in the sediments. Intact sediment cores from stands of the emergent plants Glyceria maxima and Typha latifolia had higher denitrification potential than sediment cores from stands of the submersed plant Potamogeton pectinatus. However, the quality of the organic material for the denitrifying bacteria was highest in G. maxima and P. pectinatus stands. All sediment cores from the wetland were limited by carbon, and the lower denitrification capacity of the submersed plant, P. pectinatus, was likely due to lower amounts of organic matter. However, in another wetland, intact cores from stands of the submersed plant Elodea canadensis had a higher denitrification capacity than the cores from stands of T. latifolia and Phragmites australis. This was possibly due to a larger biomass, and better quality, of the organic matter from that submersed specie, or to epiphytic biofilms on the living plants. Those microcosms studies showed that both the quality of the organic matter as a substrate for the microbial communities, and the amount of organic material produced were important for the denitrification capacity. In pilot scale wetlands, the composition of the plant community was also a more important factor for high nitrate removal than the differences in hydraulic loads (equivalent of 1 or 3 d retention time), despite the cold climate. The greatest removal was found in wetlands with emergent vegetation dominated by P. australis and G. maxima, rather than in wetlands with submersed vegetation. In brief, the results presented in this thesis emphasize the importance of dense emergent vegetation for high annual nitrate removal in treatment wetlands.

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Österman, Hanna. « Olfactory performance and neuropathology in the Tg6799 strain of Alzheimer’s disease model mice ». Thesis, Linköpings universitet, Institutionen för fysik, kemi och biologi, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-56816.

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The present study evaluated olfactory and cognitive abilities of the Tg6799 (also called 5xFAD) strain of Alzheimer’s disease (AD) model mice of two different age groups (2-3 and 8-10 months of age), and one group of healthy control mice (9-10 months). Employment of an operant conditioning paradigm using an automated olfactometer, an olfactory habituation/dishabituation test and a spatial learning test with non olfactory cues resulted in data showing that the 5xFAD mice develop olfactory impairments already at 2-3 months of age. The impairments consisted in a robust impairment in olfactory sensitivity, decreased responsiveness to novel odors and an inability to discriminate between enantiomeric odor molecules in the 5xFAD mice compared to control mice. Spatial learning deficits were also detected at this age, suggesting that cognitive functions were also affected. No differences in magnitude of the olfactory or spatial learning impairments could be detected between the age groups of model mice tested. Histological examination of development and presence of amyloid β (Aβ) plaques in the brains showed that plaques develop mainly between the ages of 3 and 8 months. This indicates that soluble Aβ rather than the formation of plaques might be responsible for the olfactory impairment and spatial learning impairments found. By 10 months of age plaque load of the 5xFAD mice was massive. The results of the present study clearly show that the 5xFAD strain might be suitable for research on human AD with regard to the early onset of olfactory impairments.

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Yao, Xuefei. « High Forest or Wood Pasture : A model of Large Herbivores' impact on European Lowland Vegetation ». Thesis, Linköping University, Linköping University, Linköping University, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-57429.

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Natural forest dynamics is a foundational topic of forest science. A new Wood Pasture hypothesis considering large herbivore as driving force in forest ecosystem is now challenging the traditional High Forest hypothesis, in which vegetation is regarded as main driving force. In this study, a model-based approach is applied to investigate differences between these two hypotheses and the determine factors in the system. A theoretical landscape of 1 km²formed by 100*100 cells is set up with 100 vegetation patches and free moving herbivores on. Our null hypothesis that herbivores make no difference in vegetation dynamics especially at canopy level is rejected. It is found that synchronization of herbivore behaviors is the most influencing factor of how a landscape might be shaped. It is also found that landscape could be a mosaic of both high forest and wood pasture depends on large herbivore’s herd size.

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Tashakor, Ghazal. « Scalable agent-based model simulation using distributed computing on system biology ». Doctoral thesis, Universitat Autònoma de Barcelona, 2021. http://hdl.handle.net/10803/671332.

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El modelat basat en agents és una eina informàtica molt útil que permet simular un comportament complex utilitzant regles tant a escales micro com macro. La complexitat d’aquest tipus de modelat està en la definició de les regles que tendran els agents per definir elements estructurals o els patrons de comportament estàtics i/o dinàmics. La present tesis aborda la definició de models complexos de xarxes biològiques que representen cèl·lules canceroses per obtenir comportaments sobre diferents escenaris mitjançant simulació i conèixer l’evolució del procés de metàstasi per a usuaris no-experts en sistemes de còmput. A més es desenvolupa una prova de concepte de com incorporar tècniques d’anàlisi de xarxes dinàmiques i d’aprenentatge automàtic en els models basats en agents a partir del desenvolupament d’un sistema de simulació federat per millorar el procés de presa de decisions. Per al desenvolupament d’aquesta tesi s’ha tingut que abordar, des del punt de vista de la simulació, la representació de xarxes biològiques complexes basades en grafs i investigar com integrar la topologia i funcions d’aquest tipus de xarxes interactuant amb un model basat en agents. En aquest objectiu, s’ha utilitzat el model ABM com a base per a la construcció, agrupament i classificació dels elements de la xarxa i que representen l’estructura d’una xarxa biològica complexa i escalable. La simulació d’un model complex de múltiples escales i múltiples agents, proporciona una eina útil per a que un científic, no-expert en computació, pugui executar un model complex i paramètric i utilitzar-ho com a eina d’anàlisi d’escenaris o predicció de variacions segons els diferents perfils de pacients considerats. El desenvolupament s’ha centrat en un model de tumor basat en agents que ha evolucionat des d’un model ABM simple i bé conegut, al qual se li han incorporat les variables i dinàmiques referenciades per l’Hallmarks of Cancer, fins a un models basat en grafs. Aquest model, basat en grafs, permet representar a diferents nivells d’interacció i dinàmiques dins de les cèl·lules en l’evolució d’un tumor que permet diferents graus de representacions (a nivell molecular/cel·lular). Tot això s’ha posat en funcionament en un entorn de simulació i ha creat un flux de treball (workflow) per construir una xarxa escalable complexa basada en un escenari de creixement tumoral i on s’apliquen tècniques dinàmiques per conèixer el creixement de la xarxa tumoral sobre diferents patrons. L’experimentació s’ha realitzat utilitzant l’entorn de simulació desenvolupat considerat l’execució de models per a diferents perfils de pacients, com a mostra de la seva funcionalitat, per a paràmetres d’interès per a l’expert no-informàtic com per exemple l’evolució del volum del tumor. L’entorn ha estat dissenyat per descobrir i classificar subgrafs del model de tumor basat en agents, que permetran distribuir els models en un sistema de còmput d’altes prestacions per poder analitzar escenaris complexos i/o diferents perfils de pacients amb patrons tumorals amb un alt nombre de cèl·lules canceroses en un temps reduït.
El modelado basado en agentes es una herramienta computacional muy útil que permite simular un comportamiento complejo utilizando reglas tanto en escalas micro como macro. La complejidad de este tipo de modelado radica en la definición de las reglas que tendrán los agentes para definir los elementos estructurales o los patrones de comportamiento estáticos y/o dinámicos. La presente tesis aborda la definición de modelos complejos de redes biológicas que representan células cancerosas para obtener comportamientos sobre diferentes escenarios mediante simulación y conocer la evolución del proceso de metástasis para usuarios no expertos en sistemas de cómputo. Además se desarrolla una prueba de concepto de cómo incorporar técnicas de análisis de redes dinámicas y de aprendizaje automático en los modelos basados en agentes a partir del desarrollo de un sistema de simulación federado para mejorar el proceso de toma de decisiones. Para el desarrollo de esta tesis se han tenido que abordar, desde el punto de vista de la simulación, la representación de redes biológicas complejas basadas en grafos e investigar como integrar la topología y funciones de este tipo de redes interactuando un modelo basado en agentes. En este objetivo, se ha utilizado el modelo ABM como base para la construcción, agrupamiento y clasificación de los elementos de la red y que representan la estructura de una red biológica compleja y escalable. La simulación de un modelo complejo de múltiples escalas y múltiples agentes, proporciona una herramienta útil para que un científico, no-experto en computación, pueda ejecutar un modelo complejo paramétrico y utilizarlo como herramienta de análisis de escenarios o predicción de variaciones según los diferentes perfiles de pacientes considerados. El desarrollo se ha centrado en un modelo de tumor basado en agentes que ha evolucionado desde un modelo ABM simple y bien conocido, al cual se le han incorporado las variables y dinámicas referenciadas por el Hallmarks of Cancer, a un modelo complejo basado en grafos. Este modelo, basado en grafos, se utiliza para representar a diferentes niveles de interacción y dinámicas dentro de las células en la evolución de un tumor que permite diferentes grado de representaciones (a nivel molecular/celular). Todo ello se ha puesto en funcionamiento en un entorno de simulación y se ha creado un flujo de trabajo (workflow) para construir una red escalable compleja basada en un escenario de crecimiento tumoral y donde se aplican técnicas dinámicas para conocer el crecimiento de la red tumoral sobre diferentes patrones. La experimentación se ha realizado utilizando el entorno de simulación desarrollado considerado la ejecución de modelos para diferentes perfiles de pacientes, como muestra de su funcionalidad, para calcular parámetros de interés para el experto no-informático como por ejemplo la evolución del volumen del tumor. El entorno ha sido diseñado para descubrir y clasificar subgrafos del modelo de tumor basado en agentes, que permitirá distribuir los modelos en un sistema de cómputo de altas prestaciones y así poder analizar escenarios complejos y/o diferentes perfiles de pacientes con patrones tumorales con un alto número de células cancerosas en un tiempo reducido.
Agent-based modeling is a very useful computational tool to simulate complex behavior using rules at micro and macro scales. This type of modeling’s complexity is in defining the rules that the agents will have to define the structural elements or the static and dynamic behavior patterns. This thesis considers the definition of complex models of biological networks that represent cancer cells obtain behaviors on different scenarios by means of simulation and to know the evolution of the metastatic process for non-expert users of computer systems. Besides, a proof of concept has been developed to incorporate dynamic network analysis techniques and machine learning in agent-based models based on developing a federated simulation system to improve the decision-making process. For this thesis’s development, the representation of complex biological networks based on graphs has been analyzed, from the simulation point of view, to investigate how to integrate the topology and functions of this type of networks interacting with an agent-based model. For this purpose, the ABM model has been used as a basis for the construction, grouping, and classification of the network elements representing the structure of a complex and scalable biological network. The simulation of complex models with multiple scales and multiple agents provides a useful tool for a scientist, non-computer expert to execute a complex parametric model and use it to analyze scenarios or predict variations according to the different patient’s profiles. The development has focused on an agent-based tumor model that has evolved from a simple and well-known ABM model. The variables and dynamics referenced by the Hallmarks of Cancer have been incorporated into a complex model based on graphs. Based on graphs, this model is used to represent different levels of interaction and dynamics within cells in the evolution of a tumor with different degrees of representations (at the molecular/cellular level). A simulation environment and workflow have been created to build a complex, scalable network based on a tumor growth scenario. In this environment, dynamic techniques are applied to know the tumor network’s growth using different patterns. The experimentation has been carried out using the simulation environment developed considering the execution of models for different patient profiles, as a sample of its functionality, to calculate parameters of interest for the non-computer expert, such as the evolution of the tumor volume. The environment has been designed to discover and classify subgraphs of the agent-based tumor model to execute these models in a high-performance computer system. These executions will allow us to analyze complex scenarios and different profiles of patients with tumor patterns with a high number of cancer cells in a short time.

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Tervonen, V. (Virpi). « Salmon cardiac peptide (sCP) : a new model for natriuretic peptide biology ». Doctoral thesis, University of Oulu, 2001. http://urn.fi/urn:isbn:9514264932.

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Abstract Natriuretic peptide hormones secreted from the heart are important in maintaining the volume and electrolyte balance and in regulation of blood pressure. The secretion of natriuretic peptides is stimulated by myocyte stretch and paracrine factors. However, the intracellular actions of these stimuli and the cellular and molecular mechanisms involved in the processing and secretion of natriuretic peptides are still largely unknown. In this study, a new model for studies of the natriuretic peptide system was developed using a novel natriuretic peptide from salmon. Salmon (Salmo salar) maintains its water and salt homeostasis despite the volume gain in fresh water and electrolyte gain in sea water. Thus, salmon is an ideal model to study the mechanisms regulating the extracellular volume and salt balance, like natriuretic peptides. Furthermore, comparative studies revealing the common characteristics in phylogenetically distinct species suggest the importance of these factors in the regulation of the natriuretic peptide system. A novel natriuretic peptide, salmon cardiac peptide (sCP), was cloned from salmon heart. Distribution of sCP was studied in a variety of vertebrates and its physiological effects were examined in in vitro and in vivo experiments in salmon and rats. The storage and release of sCP was studied using a salmon ventricle perfusion system and by analysing the molecular forms of stored and secreted forms. Factors modulating the secretion and circulating concentration of sCP, and cardiac peptide and sCP mRNA level in salmon were examined as well. The biosynthesis of sCP is strictly restricted to the heart. sCP is stored in myocytes in the prohormone form, while the secreted form is a 29-amino acid peptide in salmon. Mechanical load on isolated salmon ventricle and volume overload in intact salmon induced a rapid release of sCP. Exposure to hyperosmotic environment decreased the plasma sCP level. sCP increased diuresis and natriuresis, as well as relaxed preconstricted arteries from salmon and rats. Thus the storage, processing and release of sCP resembles those of mammalian ANP. The circulating level of sCP in salmon was markedly upregulated at increased temperatures. Upregulation resulted from decreased elimination rather than increased secretion of sCP, providing the first direct evidence that elimination is used for the regulation of the natriuretic peptide system. In conclusion, sCP is a promising model for studying the general factors regulating the cardiac natriuretic peptides.

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Deshpande, Abhishek. « Beyond the two-state model of switching in biology and computation ». Thesis, Imperial College London, 2018. http://hdl.handle.net/10044/1/62626.

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The thesis presents various perspectives on physical and biological computation. Our fundamental object of study in both these contexts is the notion of switching/erasing a bit. In a physical context, a bit is represented by a particle in a double well, whose dynamics is governed by the Langevin equation. We define the notions of reliability and erasing time-scales in addition to the work required to erase a bit for a given family of control protocols. We call bits “optimal” if they meet the required reliability and erasing time requirements with minimal work cost. We find that optimal bits always saturate the erasing time requirement, but may not saturate the reliability time requirement. This allows us to eliminate several regions of parameter space as sub-optimal. In a biological context, our bits are represented by substrates that are acted upon by catalytic enzymes. We define retroactivity as the back-signal propagated by the downstream system when connected to the upstream system. We analyse certain upstream systems that can help mitigate retroactivity. However, these systems require a substantial pool of resources and are therefore not optimal. As a consequence, we turn our attention to insulating networks called push-pull motifs. We find that high rates of energy consumption are not essential to alleviate retroactivity in push-pull motifs; all we need is to couple weakly to the upstream system. However, this approach is not resilient to cross-talk caused by leak reactions in the circuit. Next, we consider a single enzyme-substrate reaction and analyse its mechanism. Our system has two intermediate states (enzyme-substrate complexes). Our main question is “How should we choose binding energies of the intermediates to minimize sequestra- tion of substrates (retroactivity), whilst maintaining a minimum flux at steady-state?”. Choosing very low binding energies increases retroactivity since the system spends a considerable proportion of time in the intermediate states. Choosing binding energies that are very high reduces retroactivity, but hinders the progress of the reaction. As a result, we find that the the optimal binding energies are both moderate, and indeed tuned with each other. In particular, their difference is related to the free energy difference between the products and reactants.

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Richardson, Jennifer. « Zebrafish as a model of BRAFV600E melanoma subtypes and Nevus biology ». Thesis, University of Edinburgh, 2012. http://hdl.handle.net/1842/6493.

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The most frequent mutation identified in both benign nevi and malignant melanoma is the constitutively activating V600E substitution of BRAF. However, how additional mutations co-operate with BRAFV600E to promote subtypes of melanoma in animals is only beginning to be understood. In this thesis, I generate and analyze zebrafish BRAFV600E melanoma models and also develop the first animal model for BRAFV600E nevus recurrence. In my first data chapter, I develop a unique animal model of nevus recurrence. In people it is not uncommon for a nevus to recur following removal, even when no pigmented nevus cells remain. The biology of how and why this happens is unknown. By partial amputation of the nevus in the zebrafish tail fin, we described both nevus regrowth, as well as nevi that do not regrow. Utilising melanin as a lineage tracer, I was able to show that recurrent nevi are repopulated from an unpigmented precursor population. This suggested that BRAFV600E nevi are supported by an undifferentiated stem cell population that is recruited to regenerate and pigment the nevus after removal. In my second data chapter, I use genetics to develop BRAFV600E zebrafish models of melanoma. In collaboration with Dr. James Lister and Professor Jeroen den Hertog, I describe three differing models of zebrafish melanoma. All three models show progression to melanoma, and in collaboration with Dr. Marie Mathers I establish that while BRAFV600E is present in all three models, co-operating mutations affect melanoma pathology. In my third data chapter, I develop tools to study the molecular differences in the BRAFV600E melanoma models. I described the optimisation of a broad range of antibodies, raised against human peptides due to the lack of reliable antibodies in the zebrafish field. I use punch core biopsies of both zebrafish and human tumours, and whole sagittal sections of juvenile zebrafish, to show specific staining throughout many organs of the developing fish. I then use some of these antibodies to analyse molecular pathways in the melanoma models.

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Prescott, Thomas Paul. « Large-scale layered systems and synthetic biology : model reduction and decomposition ». Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:205a18fb-b21f-4148-ba7d-3238f4b1f25b.

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This thesis is concerned with large-scale systems of Ordinary Differential Equations that model Biomolecular Reaction Networks (BRNs) in Systems and Synthetic Biology. It addresses the strategies of model reduction and decomposition used to overcome the challenges posed by the high dimension and stiffness typical of these models. A number of developments of these strategies are identified, and their implementation on various BRN models is demonstrated. The goal of model reduction is to construct a simplified ODE system to closely approximate a large-scale system. The error estimation problem seeks to quantify the approximation error; this is an example of the trajectory comparison problem. The first part of this thesis applies semi-definite programming (SDP) and dissipativity theory to this problem, producing a single a priori upper bound on the difference between two models in the presence of parameter uncertainty and for a range of initial conditions, for which exhaustive simulation is impractical. The second part of this thesis is concerned with the BRN decomposition problem of expressing a network as an interconnection of subnetworks. A novel framework, called layered decomposition, is introduced and compared with established modular techniques. Fundamental properties of layered decompositions are investigated, providing basic criteria for choosing an appropriate layered decomposition. Further aspects of the layering framework are considered: we illustrate the relationship between decomposition and scale separation by constructing singularly perturbed BRN models using layered decomposition; and we reveal the inter-layer signal propagation structure by decomposing the steady state response to parametric perturbations. Finally, we consider the large-scale SDP problem, where large scale SDP techniques fail to certify a system’s dissipativity. We describe the framework of Structured Storage Functions (SSF), defined where systems admit a cascaded decomposition, and demonstrate a significant resulting speed-up of large-scale dissipativity problems, with applications to the trajectory comparison technique discussed above.

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Feist, Adam Michael. « Model-driven metabolic engineering of Escherichia coli a systems biology approach / ». Diss., [La Jolla] : University of California, San Diego, 2008. http://wwwlib.umi.com/cr/ucsd/fullcit?p3354731.

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Thesis (Ph. D.)--University of California, San Diego, 2008.
Title from first page of PDF file (viewed June 2, 2009). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references.

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Gay, Steven. « Subgraph Epimorphisms : Theory and Application to Model Reductions in Systems Biology ». Sorbonne Paris Cité, 2015. http://www.theses.fr/2015USPCC265.

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Cette thèse développe une méthode de morphismes de graphes et l'applique à la réduction de modèles en biologie des systèmes. Nous nous intéressons au problème suivant: l'ensemble des modèles en biologie des systèmes est en expansion, mais aucune relation formelle entre les modèles de cet ensemble n'a été entreprise. Ainsi, la tâche d'organisation des modèles existants, qui est essentielle pour le raffinement et le couplage de modèles, doit être effectuée par le modélisateur. En biomathématiques, les techniques de réduction de modèle sont étudiées depuis longtemps, mais ces techniques sont bien trop restrictives pour être appliquées aux échelles requises en biologie des systèmes. Nous proposons un cadre de réduction de modèle, basé uniquement sur des graphes, qui permet d'organiser les modèles en un ordre partiel. Les modèles de biologie des systèmes seront représentés par leur graphe de réaction. Pour capturer le processus de réduction lui-même, nous étudierons un type particulier de morphismes de graphes : les épimorphismes de sous-graphe, qui permettent la fusion et l'effacement de sommets. Nous commencerons en analysant l'ordre partiel qui émerge des opérations de fusion et d'effacement, puis nous développerons des outils théoriques pour résoudre les problèmes calculatoires de notre méthode, et pour finir nous montrerons la faisabilité de l'approche et la précision du cadre "graphes de réactions/épimorphismes de sous-graphe", en utilisant un dépôt de modèles de biologie des systèmes
This thesis develops a framework of graph morphisms and applies it to model reduction in systems biology. We are interested in the following problem: the collection of systems biology models is growing, but there is no formai relation between models in this collection. Thus, the task of organizing the existing models, essential for model refinement and coupling, is left to the modeler. In mathematical biology, model reduction techniques have been studied for a long time, however these techniques are far too restrictive to be applied on the scales required by systems biology. We propose a model reduction framework based solely on graphs, allowing to organize models in a partial order. Systems biology models will be represented by their reaction graphs. To capture the process of reduction itself, we study a particular kind of graph morphisms: subgraph epimorphisms, which allow both vertex merging and deletion. We first analyze the partial order emerging from the merge/delete graph operations, then develop tools to solve computational problems raised by this framework, and finally show both the computational feasibility of the approach and the accuracy of the reaction graphs/subgraph epimorphisms framework on a large repository of systems biology models

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Frenkel, Martin. « Light, stress and herbivory : from photoprotection to trophic interactions using Arabidopsis thaliana as a model organism ». Doctoral thesis, Umeå : Department of Ecology and Environmental Science, Umeå University, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-1651.

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Murphy, Ryan John. « Mechanochemical and experimental models in mathematical biology ». Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/228428/1/Ryan%20John_Murphy_Thesis.pdf.

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Experiments that probe epithelial tissue dynamics, cell competition, and tumour growth are fundamental to understand processes in developmental biology, cancer progression and treatment. However, interpreting complex biological experiments is challenging. To address this challenge, we develop and use a range of mathematical models. First, we focus on epithelial tissue dynamics. Second, we use real-time cell cycle imaging to reveal the structure of growing tumour spheroids. We then revisit the seminal Greenspan tumour growth model and use statistical analysis to quantitatively connect it to experimental data for the first time to reveal experimental design choices that lead to reliable biological insight.

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Boman, Erik. « Olfactory and cognitive abilities in two strains of Alzheimer`s disease model mice ». Thesis, Linköping University, Department of Physics, Chemistry and Biology, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-19200.

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The present study assessed olfactory and cognitive abilities in two strains of Alzheimer’s disease (AD) model mice and in healthy control mice over a four month time period. To this end an operant conditioning paradigm using an automated olfactometer and a spatial learning test with non-olfactory cues were employed and data on olfactory learning and memory, discrimination, and sensitivity as well as spatial learning and memory were collected. The mice were between 6 to 7 month old at the beginning of the study and 9 to 10 months old at the end of the data collection, that is, in the age range when the animals are supposed to display marked neuroanatomical changes typical of AD. The results demonstrate that there were no systematic differences in olfactory performance and spatial learning and memory abilities of AD model mice and the control mice up to the age they were tested. Further, there was no indication of an age-related decline in performance in any of the mouse strains across the testing period. Several reasons might account for the observed lack of difference in olfactory and cognitive performance between the mouse strains tested here: the AD model mice might not develop amyloid plaques and neurofibrillary tangles at all or they might develop them later than stated by the supplier. Alternatively, the AD model mice may have developed AD-typical neuroanatomical changes but these do not, or not yet, affect their olfactory performance and/or spatial learning and memory capabilities. Ongoing data collection will help to evaluate which of these explanations holds true.

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Nangu, Bongiwe B. « Teaching in English and Isixhosa : code-switching in grade 11 Biology classes at a school in Khayelitsha ». Thesis, University of the Western Cape, 2006. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_7339_1242696871.

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This study explored the use of code-switching in Biology classes at high school level, how it is used in the teaching and learning situation and its effect on the learners' performance in the subject. Grade 11 was chosen as it precedes the last year at high school.

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Chen, Daphne Wei-chen. « Integrative modelling of glucocorticoid induced apoptosis with a systems biology approach ». Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/integrative-modelling-of-glucocorticoid-induced-apoptosis-with-a-systems-biology-approach(a05039a1-f3e3-44d2-959e-0fade52a28a1).html.

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Glucocorticoids (GCs) have an important role in anti-inflammation, apoptosis and immunomodulatory activity. GCs exert their effect by binding to their receptor, glucocorticoid receptor (GR), which subsequently triggers receptor dimerisation, nuclear translocation and eventually causes impact on transcriptional activity. Such regulatory mechanism is complex as it is not only controlled at the transcription level, but also at the post translational level with other contributing factors such as protein stability and cofactor recruitment. Glucocorticoids are commonly used as part of the chemotherapeutical protocols for lymphoid malignancies and have been successfully implicated in treating childhood acute lymphoblastic leukaemia (ALL). Nevertheless, resistance and side effects such as muscle atrophy and osteoporosis still occur frequently.With the advance in high-throughput technology, vast amount of data on various scales, including genomics, proteomics, and metabolomics make the molecular study of cancer more complicated. The rise of systems biology helps the scientist to address this problem with the use of computation. Although the concept and the approach may vary depending on the research fields, the ultimate goal remains the same which is to create a comprehensive understanding of biological processes and to forecast outcome.The goal of this body of work is to better understand glucocorticoid induced apoptosis in acute lymphoblastic leukaemia by adopting a systems biology approach. As the Bcl-2 family, particularly Bim is known to be a key determinant of GC-induced apoptosis, we investigated the molecular mechanism of GC induction of Bim. By adopting ordinary differential equation modelling approach, we were able to make prediction and investigate details of Bim regulation by GCs. Further to this, we carried out an integrated microarray analysis in various ALL to study GC resistance and identified crucial candidate gene c-Jun as a regulator of Bim and Erg as a determinant for GC resistance. These results allowed us to refine our models and enabled more answers to be addressed. In conclusion, our findings not only suggest potential regulatory mechanisms for determining GC sensitivity, they also aid us to find potential biomarkers for determining GC resistance. More importantly, this study represents a successful example for utilising systems biology to study the genetic complexity in cancer.

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Pastor, André [Verfasser]. « Membranadsorber-Modul zur Aufarbeitung ungeklärter Bioprozessmedien / André Pastor ». Hannover : Technische Informationsbibliothek (TIB), 2016. http://d-nb.info/1128922665/34.

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ROSAS, ILIANA NICOLE. « MODEL BASED INQUIRY IN AN INTRODUCTORY MOLECULAR AND CELLULAR BIOLOGY LABORATORY SETTING ». Thesis, The University of Arizona, 2016. http://hdl.handle.net/10150/613566.

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The cycles of reasoning of “Model Based Inquiry” (MBI) were used to create a lesson plan for undergraduate Molecular and Cellular Biology Laboratories at the University of Arizona. The implementation of this lesson plan was performed in a pilot lab using the unicellular organism Chlamydomonas, and students were audio and video recorded. Researchers paid specific attention to students’ observations and recognition of data patters, the development of explanatory models to explain these and in accordance with previous knowledge, the use of such models as predictive tools, and the revision or reinvention of models when additional information was given. Some limitation of the implementation of the lesson plan involved low attendance of students, and improper adherence to the lesson plan by the instructor. Even so, there was evidence of Model Based Inquiry performed by students as they investigated Chlamydomonas through microscopes and phototaxis assays.

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Ghosh, Krishnendu. « Formal Analysis of Automated Model Abstractions under Uncertainty : Applications in Systems Biology ». University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1330024977.

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Toni, Tina. « Approximate Bayesian computation for parameter inference and model selection in systems biology ». Thesis, Imperial College London, 2010. http://hdl.handle.net/10044/1/11481.

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In this thesis we present a novel algorithm for parameter estimation and model selection of dynamical systems. The algorithm belongs to the class of approximate Bayesian computation (ABC) methods, which can evaluate posterior distributions without having to calculate likelihoods. It is based on a sequential Monte Carlo framework, which gives our method a computational advantage over other existing ABC methods. The algorithm is applied to a wide variety of biological systems such as prokaryotic and eukaryotic signalling and stress response pathways, gene regulatory networks, and infectious diseases. We illustrate its applicability to deterministic and stochastic models, and draw inferences from different data frameworks. Posterior parameter distributions are analysed in order to gain further insight into parameter sensitivity and sloppiness. The comprehensive analysis provided in this thesis illustrates the flexibility of our new ABC SMC approach. The algorithm has proven useful for efficient parameter inference, systematic model selection and inference-based modelling, and is a novel and useful addition to the systems biology toolbox.

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Wang, Zhi. « Module-Based Analysis for "Omics" Data ». Thesis, North Carolina State University, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3690212.

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This thesis focuses on methodologies and applications of module-based analysis (MBA) in omics studies to investigate the relationships of phenotypes and biomarkers, e.g., SNPs, genes, and metabolites. As an alternative to traditional single–biomarker approaches, MBA may increase the detectability and reproducibility of results because biomarkers tend to have moderate individual effects but significant aggregate effect; it may improve the interpretability of findings and facilitate the construction of follow-up biological hypotheses because MBA assesses biomarker effects in a functional context, e.g., pathways and biological processes. Finally, for exploratory “omics” studies, which usually begin with a full scan of a long list of candidate biomarkers, MBA provides a natural way to reduce the total number of tests, and hence relax the multiple-testing burdens and improve power.

The first MBA project focuses on genetic association analysis that assesses the main and interaction effects for sets of genetic (G) and environmental (E) factors rather than for individual factors. We develop a kernel machine regression approach to evaluate the complete effect profile (i.e., the G, E, and G-by-E interaction effects separately or in combination) and construct a kernel function for the Gene-Environmental (GE) interaction directly from the genetic kernel and the environmental kernel. We use simulation studies and real data applications to show improved performance of the Kernel Machine (KM) regression method over the commonly adapted PC regression methods across a wide range of scenarios. The largest gain in power occurs when the underlying effect structure is involved complex GE interactions, suggesting that the proposed method could be a useful and powerful tool for performing exploratory or confirmatory analyses in GxE-GWAS.

In the second MBA project, we extend the kernel machine framework developed in the first project to model biomarkers with network structure. Network summarizes the functional interplay among biological units; incorporating network information can more precisely model the biological effects, enhance the ability to detect true signals, and facilitate our understanding of the underlying biological mechanisms. In the work, we develop two kernel functions to capture different network structure information. Through simulations and metabolomics study, we show that the proposed network-based methods can have markedly improved power over the approaches ignoring network information.

Metabolites are the end products of cellular processes and reflect the ultimate responses of biology system to genetic variations or environment exposures. Because of the unique properties of metabolites, pharmcometabolomics aims to understand the underlying signatures that contribute to individual variations in drug responses and identify biomarkers that can be helpful to response predictions. To facilitate mining pharmcometabolomic data, we establish an MBA pipeline that has great practical value in detection and interpretation of signatures, which may potentially indicate a functional basis for the drug response. We illustrate the utilities of the pipeline by investigating two scientific questions in aspirin study: (1) which metabolites changes can be attributed to aspirin intake, and (2) what are the metabolic signatures that can be helpful in predicting aspirin resistance. Results show that the MBA pipeline enables us to identify metabolic signatures that are not found in preliminary single-metabolites analysis.

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Cossa, Eugenia Flora Rosa. « A case study of practical work in a cell biology course at the Eduardo Mondlane University in Mozambique ». Thesis, University of the Western Cape, 2007. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_1757_1228307542.

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This study was carried out with the assumption that practical work does contribute to the teaching and learning of cell biology at Eduardo Mondlane University in Mozambique. In this regard, the main purpose of this study was to investigate the impact of practical work in the teaching and learning of cell biology concepts, specifically focussing on cell divisions concepts. It also aimed at determining the students' perceptions of the role of practical work in the learning of cell biology. On the other hand, the study sought also to understand the lecturers' practical work teaching experiences and views regarding the cell biology practical work.

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Lott, Paul Christian. « StochHMM| A Flexible Hidden Markov Model Framework ». Thesis, University of California, Davis, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3602142.

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In the era of genomics, data analysis models and algorithms that provide the means to reduce large complex sets into meaningful information are integral to further our understanding of complex biological systems. Hidden Markov models comprise one such data analysis technique that has become the basis of many bioinformatics tools. Its relative success is primarily due to its conceptually simplicity and robust statistical foundation. Despite being one of the most popular data analysis modeling techniques for classification of linear sequences of data, researchers have few available software options to rapidly implement the necessary modeling framework and algorithms. Most tools are still hand-coded because current implementation solutions do not provide the required ease or flexibility that allows researchers to implement models in non-traditional ways. I have developed a free hidden Markov model C++ library and application, called StochHMM, that provides researchers with the flexibility to apply hidden Markov models to unique sequence analysis problems. It provides researchers the ability to rapidly implement a model using a simple text file and at the same time provide the flexibility to adapt the model in non-traditional ways. In addition, it provides many features that are not available in any current HMM implementation tools, such as stochastic sampling algorithms, ability to link user-defined functions into the HMM framework, and multiple ways to integrate additional data sources together to make better predictions. Using StochHMM, we have been able to rapidly implement models for R-loop prediction and classification of methylation domains. The R-loop predictions uncovered the epigenetic regulatory role of R-loops at CpG promoters and protein coding genes 3' transcription termination. Classification of methylation domains in multiple pluripotent tissues identified epigenetics gene tracks that will help inform our understanding of epigenetic diseases.

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Maqungo, Monique Nonceba. « Physiological and cellular characterization of a plant natriuretic peptide ». Thesis, University of the Western Cape, 2005. http://etd.uwc.ac.za/index.php?module=etd&amp.

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Plants in the field are exposed to multiple stresses and their response to these various stresses determines their capacity to survive. Plants can use multiple signaling pathways and signals to mediate their response
for example, at least four different signal pathways have been identified for water-deficit stress (Shinozaki and Yamaguchi-Shinozaki, 1997
Xiong et al., 2002). Different forms of stress may activate or utilize the same components, including proteins and other signaling molecules. Signaling molecules such as jasmonic acid (JA) are involved in multiple stress response and development in plants (Creelman and Mullet, 1995, 1997
Turner et al., 2002). However it is the specific combination of various components of the signaling network coupled with spatial and temporal factors that allows the plant to mount a directed response to any given stress factors. Systemic defense responses thus provide an attractive model for the study of cell-to-to cell signal transduction pathways that operates over long distances (Lucas and Lee, 2004).

Cellular and physiological evidence suggest the presence of a novel class of systemic mobile plant molecule that is recognized by antibodies against vertebrate atrial natriuretic peptides (ANPs). It has been demonstrated that a recombinant Arabidopsis thaliana natriuretic peptide analogue (AtPNP-A) molecule can induce osmoticumdependent water uptake into protoplast at nanomolar concentrations thus affecting cell volume and hence plant growth. In this study we confirm that active recombinant protein causes swelling in Arabidopsis mesophyll cell protoplasts (MCPs).

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Buckalew, Richard L. « Mathematical Models in Cell Cycle Biology and Pulmonary Immunity ». Ohio University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1395242276.

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