1,720,958 research outputs found
Towards comprehensive and consistent kinetic models of metabolism under uncertainty
No full textMetabolism is the sum of the chemical interactions occurring inside a cell that process nutrients into cellular constituents and energy. Research in the recent decades has enabled the characterization of metabolic reaction networks for multiple organisms. Genome-scale models (GEMs) have been utilized to mathematically describe and analyze these networks. GEMs are stoichiometric models that can serve as basis for studying metabolism and identifying metabolic states. However, stoichiometric models of metabolism do not account for the dynamics of the system. An understanding of cellular dynamics and regulation is essential for metabolic engineering of cells that produce certain metabolites of interest. Kinetic models can provide invaluable knowledge about system dynamics of cellular metabolism as metabolic control analysis (MCA) can offer information about the systemâ s response to perturbations. Nonetheless, the construction of kinetic models is a challenging endeavor as several hurdles have to be overcome. Kinetic models of metabolism are subject to two general issues: diversity of network topologies and underlying uncertainty. Kinetic models are often built on an ad hoc basis without clear explanation or justification about their network contents, as there is no systematic protocol for their construction. Furthermore, kinetic modeling is subject to uncertainty from various sources. Multiple steady states can characterize an observed physiology. Additionally, the kinetic mechanisms describing a system and the values of their kinetic parameters are often not known.
In this thesis, we tackle several issues that hinder the formulation of kinetic models. Firstly, we apply model reduction algorithms to systematically reduce GEMs to construct study-specific kinetic models of different degrees of complexity. We demonstrate that the MCA outputs for these kinetic models are mostly independent of the complexity level because we preserve model equivalency. Secondly, as published kinetic models to date are constructed around a steady state of metabolism, we analyzed the impact of alternative steady states on metabolic engineering strategies. We proposed a systematic workflow for deriving conclusions that take into account the alternative feasible steady states of a physiology. We concluded that MCA outputs are more sensitive to the metabolite concentrations than to the metabolic fluxes of the system. Hence, it is essential to consider alternative metabolic states for a given physiology. Thirdly, since multiple kinetic models can describe a physiology due to the given uncertainties, it is important to consider them in populations. In order to derive conclusions from populations of kinetic models, it is essential to quantify with what certainty we make such predictions. We tested different statistical methods for assigning confidence levels to our conclusions and make recommendations applicable to any kinetic models. Finally, we implemented a sensitivity analysis approach that can elucidate which input parameters of a kinetic model contribute the most to the uncertainty in MCA outputs. The approach appears to predict correctly the sources of uncertainty and can be applied to any large-scale kinetic models. Overall, the work from this thesis contributes towards establishing a systematic workflow for building more consistent and comprehensible kinetic models for observed physiologies under uncertainty.LCS
Study on how underlying uncertainty in the flux values affects metabolic control analysis of optimally grown E. coli
No full textLarge-scale kinetic models of metabolism are essential for understanding and predicting the behavior of cellular systems when subject to perturbations. Despite the advances in experimental measurement technologies, the numerous parameters that are required to build kinetic models remain scarce and involve uncertainty. Even after incorporating the partially available experimental data, models still have many degrees of freedom. Due to this parametric uncertainty, some reactions are able to operate in forward and reverse directions. An operational configuration consists of reactions that operate in a unique direction. This flexibility results in the existence of alternative operational configurations representing the same physiology, with very distinct regulatory properties. In this study, we focus on one operational configuration and we investigate how the underlying uncertainty in the flux values affects the robustness of the model predictions and regulatory capabilities. To study this question, we used a large-scale kinetic model and integrated fluxomics and metabolomics data describing the physiology for aerobically grown E. coli. Because of the under-determined nature of the system, there are infinite existing flux solutions within the selected operational configuration. To account for the flux variability within the designated operational configuration, we selected a reference vector of concentrations close to their nominal value. We used the ORACLE (optimization and risk analysis of complex living entities) framework to build populations of kinetic models that are consistent with the given physiology, while satisfying the stoichiometric and thermodynamic constraints. We next performed a systematic analysis of the effect that the flux profiles have on the robustness of the regulatory properties of the system. We used the mean PCA (principle component analysis) value of the flux samples as reference when selecting flux profiles. Flux profiles across the main components of the PCA were studied. We used ORACLE to generate populations of kinetic models for these flux profiles. Then, we computed the distributions of their flux control coefficients (FCCs) along the dimensions with the highest variance. Finally, by comparing the changes among the distributions of the FCCs versus those corresponding to the reference flux profile, we were able to quantify the robustness of the regulatory predictions within a specific operational configuration.LCS
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
How uncertainty in kinetic parameters affects metabolic control analysis of optimally grown E.coli
No full textLarge-scale kinetic models of metabolism are essential for understanding and predicting the behavior of cellular systems when subject to perturbations. Despite the advances in experimental measurement technologies, the numerous parameters that are required to build kinetic models remain scarce and involve uncertainty. Even after incorporating the partially available experimental data, models still have many degrees of freedom. Due to this parametric uncertainty, some reactions are able to operate in forward and reverse directions. An operational configuration consists of reactions that operate in a unique direction. This flexibility results in the existence of alternative operational configurations representing the same physiology, with very distinct regulatory properties. In this study, we focus on one operational configuration and we investigate how the underlying uncertainty in the kinetic parameters affects the robustness of the model predictions and regulatory capabilities. To study this question, we used a large-scale non-linear kinetic model built using integrated fluxomics and metabolomics data describing the physiology for aerobically grown E. coli. Because of the under-determined nature of the system, there are multiple kinetic parameters that can render the model feasible within the selected operational configuration. To account for the variability of the kinetic parameters within the designated operational configuration, we selected a reference vector of fluxes and concentrations close to their nominal values. Then, we used the ORACLE (optimization and risk analysis of complex living entities) framework to build populations of kinetic models that are consistent with the given physiology, while satisfying the stoichiometric and thermodynamic constraints. From these, we built non-linear models to test how the system’s response to perturbations changed with respect to the chosen kinetic parameters. This allowed us to quantify the effect of the uncertainty in the kinetic parameters on the robustness of the regulatory properties of the system.LCS
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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