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Sample records for genome-scale kinetic model

  1. Genome-Scale Models

    DEFF Research Database (Denmark)

    Bergdahl, Basti; Sonnenschein, Nikolaus; Machado, Daniel

    2016-01-01

    An introduction to genome-scale models, how to build and use them, will be given in this chapter. Genome-scale models have become an important part of systems biology and metabolic engineering, and are increasingly used in research, both in academica and in industry, both for modeling chemical pr...

  2. Genome-scale Metabolic Reaction Modeling: a New Approach to Geomicrobial Kinetics

    Science.gov (United States)

    McKernan, S. E.; Shapiro, B.; Jin, Q.

    2014-12-01

    Geomicrobial rates, rates of microbial metabolism in natural environments, are a key parameter of theoretical and practical problems in geobiology and biogeochemistry. Both laboratory- and field-based approaches have been applied to study rates of geomicrobial processes. Laboratory-based approaches analyze geomicrobial kinetics by incubating environmental samples under controlled laboratory conditions. Field methods quantify geomicrobial rates by observing the progress of geomicrobial processes. To take advantage of recent development in biogeochemical modeling and genome-scale metabolic modeling, we suggest that geomicrobial rates can also be predicted by simulating metabolic reaction networks of microbes. To predict geomicrobial rates, we developed a genome-scale metabolic model that describes enzyme reaction networks of microbial metabolism, and simulated the network model by accounting for the kinetics and thermodynamics of enzyme reactions. The model is simulated numerically to solve cellular enzyme abundance and hence metabolic rates under the constraints of cellular physiology. The new modeling approach differs from flux balance analysis of system biology in that it accounts for the thermodynamics and kinetics of enzymatic reactions. It builds on subcellular metabolic reaction networks, and hence also differs from classical biogeochemical reaction modeling. We applied the new approach to Methanosarcina acetivorans, an anaerobic, marine methanogen capable of disproportionating acetate to carbon dioxide and methane. The input of the new model includes (1) enzyme reaction network of acetoclastic methanogenesis, and (2) representative geochemical conditions of freshwater sedimentary environments. The output of the simulation includes the proteomics, metabolomics, and energy and matter fluxes of M. acetivorans. Our simulation results demonstrate the predictive power of the new modeling approach. Specifically, the results illustrate how methanogenesis rates vary

  3. Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism.

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    Vital-Lopez, Francisco G; Reifman, Jaques; Wallqvist, Anders

    2015-10-01

    A hallmark of Pseudomonas aeruginosa is its ability to establish biofilm-based infections that are difficult to eradicate. Biofilms are less susceptible to host inflammatory and immune responses and have higher antibiotic tolerance than free-living planktonic cells. Developing treatments against biofilms requires an understanding of bacterial biofilm-specific physiological traits. Research efforts have started to elucidate the intricate mechanisms underlying biofilm development. However, many aspects of these mechanisms are still poorly understood. Here, we addressed questions regarding biofilm metabolism using a genome-scale kinetic model of the P. aeruginosa metabolic network and gene expression profiles. Specifically, we computed metabolite concentration differences between known mutants with altered biofilm formation and the wild-type strain to predict drug targets against P. aeruginosa biofilms. We also simulated the altered metabolism driven by gene expression changes between biofilm and stationary growth-phase planktonic cultures. Our analysis suggests that the synthesis of important biofilm-related molecules, such as the quorum-sensing molecule Pseudomonas quinolone signal and the exopolysaccharide Psl, is regulated not only through the expression of genes in their own synthesis pathway, but also through the biofilm-specific expression of genes in pathways competing for precursors to these molecules. Finally, we investigated why mutants defective in anthranilate degradation have an impaired ability to form biofilms. Alternative to a previous hypothesis that this biofilm reduction is caused by a decrease in energy production, we proposed that the dysregulation of the synthesis of secondary metabolites derived from anthranilate and chorismate is what impaired the biofilms of these mutants. Notably, these insights generated through our kinetic model-based approach are not accessible from previous constraint-based model analyses of P. aeruginosa biofilm

  4. Systematic construction of kinetic models from genome-scale metabolic networks.

    Directory of Open Access Journals (Sweden)

    Natalie J Stanford

    Full Text Available The quantitative effects of environmental and genetic perturbations on metabolism can be studied in silico using kinetic models. We present a strategy for large-scale model construction based on a logical layering of data such as reaction fluxes, metabolite concentrations, and kinetic constants. The resulting models contain realistic standard rate laws and plausible parameters, adhere to the laws of thermodynamics, and reproduce a predefined steady state. These features have not been simultaneously achieved by previous workflows. We demonstrate the advantages and limitations of the workflow by translating the yeast consensus metabolic network into a kinetic model. Despite crudely selected data, the model shows realistic control behaviour, a stable dynamic, and realistic response to perturbations in extracellular glucose concentrations. The paper concludes by outlining how new data can continuously be fed into the workflow and how iterative model building can assist in directing experiments.

  5. Integrating Kinetic Model of E. coli with Genome Scale Metabolic Fluxes Overcomes Its Open System Problem and Reveals Bistability in Central Metabolism.

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    Ahmad A Mannan

    Full Text Available An understanding of the dynamics of the metabolic profile of a bacterial cell is sought from a dynamical systems analysis of kinetic models. This modelling formalism relies on a deterministic mathematical description of enzyme kinetics and their metabolite regulation. However, it is severely impeded by the lack of available kinetic information, limiting the size of the system that can be modelled. Furthermore, the subsystem of the metabolic network whose dynamics can be modelled is faced with three problems: how to parameterize the model with mostly incomplete steady state data, how to close what is now an inherently open system, and how to account for the impact on growth. In this study we address these challenges of kinetic modelling by capitalizing on multi-'omics' steady state data and a genome-scale metabolic network model. We use these to generate parameters that integrate knowledge embedded in the genome-scale metabolic network model, into the most comprehensive kinetic model of the central carbon metabolism of E. coli realized to date. As an application, we performed a dynamical systems analysis of the resulting enriched model. This revealed bistability of the central carbon metabolism and thus its potential to express two distinct metabolic states. Furthermore, since our model-informing technique ensures both stable states are constrained by the same thermodynamically feasible steady state growth rate, the ensuing bistability represents a temporal coexistence of the two states, and by extension, reveals the emergence of a phenotypically heterogeneous population.

  6. Genome scale metabolic modeling of cancer

    DEFF Research Database (Denmark)

    Nilsson, Avlant; Nielsen, Jens

    2016-01-01

    been used as scaffolds for analysis of high throughput data to allow mechanistic interpretation of changes in expression. Finally, GEMs allow quantitative flux predictions using flux balance analysis (FBA). Here we critically review the requirements for successful FBA simulations of cancer cells......Cancer cells reprogram metabolism to support rapid proliferation and survival. Energy metabolism is particularly important for growth and genes encoding enzymes involved in energy metabolism are frequently altered in cancer cells. A genome scale metabolic model (GEM) is a mathematical formalization...... of metabolism which allows simulation and hypotheses testing of metabolic strategies. It has successfully been applied to many microorganisms and is now used to study cancer metabolism. Generic models of human metabolism have been reconstructed based on the existence of metabolic genes in the human genome...

  7. Modeling cancer metabolism on a genome scale

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    Yizhak, Keren; Chaneton, Barbara; Gottlieb, Eyal; Ruppin, Eytan

    2015-01-01

    Cancer cells have fundamentally altered cellular metabolism that is associated with their tumorigenicity and malignancy. In addition to the widely studied Warburg effect, several new key metabolic alterations in cancer have been established over the last decade, leading to the recognition that altered tumor metabolism is one of the hallmarks of cancer. Deciphering the full scope and functional implications of the dysregulated metabolism in cancer requires both the advancement of a variety of omics measurements and the advancement of computational approaches for the analysis and contextualization of the accumulated data. Encouragingly, while the metabolic network is highly interconnected and complex, it is at the same time probably the best characterized cellular network. Following, this review discusses the challenges that genome-scale modeling of cancer metabolism has been facing. We survey several recent studies demonstrating the first strides that have been done, testifying to the value of this approach in portraying a network-level view of the cancer metabolism and in identifying novel drug targets and biomarkers. Finally, we outline a few new steps that may further advance this field. PMID:26130389

  8. Use of genome-scale microbial models for metabolic engineering

    DEFF Research Database (Denmark)

    Patil, Kiran Raosaheb; Åkesson, M.; Nielsen, Jens

    2004-01-01

    network structures. The major challenge for metabolic engineering in the post-genomic era is to broaden its design methodologies to incorporate genome-scale biological data. Genome-scale stoichiometric models of microorganisms represent a first step in this direction.......Metabolic engineering serves as an integrated approach to design new cell factories by providing rational design procedures and valuable mathematical and experimental tools. Mathematical models have an important role for phenotypic analysis, but can also be used for the design of optimal metabolic...

  9. Genome-scale modeling for metabolic engineering

    Energy Technology Data Exchange (ETDEWEB)

    Simeonidis, E; Price, ND

    2015-01-13

    We focus on the application of constraint-based methodologies and, more specifically, flux balance analysis in the field of metabolic engineering, and enumerate recent developments and successes of the field. We also review computational frameworks that have been developed with the express purpose of automatically selecting optimal gene deletions for achieving improved production of a chemical of interest. The application of flux balance analysis methods in rational metabolic engineering requires a metabolic network reconstruction and a corresponding in silico metabolic model for the microorganism in question. For this reason, we additionally present a brief overview of automated reconstruction techniques. Finally, we emphasize the importance of integrating metabolic networks with regulatory information-an area which we expect will become increasingly important for metabolic engineering-and present recent developments in the field of metabolic and regulatory integration.

  10. Genome-scale modeling for metabolic engineering.

    Science.gov (United States)

    Simeonidis, Evangelos; Price, Nathan D

    2015-03-01

    We focus on the application of constraint-based methodologies and, more specifically, flux balance analysis in the field of metabolic engineering, and enumerate recent developments and successes of the field. We also review computational frameworks that have been developed with the express purpose of automatically selecting optimal gene deletions for achieving improved production of a chemical of interest. The application of flux balance analysis methods in rational metabolic engineering requires a metabolic network reconstruction and a corresponding in silico metabolic model for the microorganism in question. For this reason, we additionally present a brief overview of automated reconstruction techniques. Finally, we emphasize the importance of integrating metabolic networks with regulatory information-an area which we expect will become increasingly important for metabolic engineering-and present recent developments in the field of metabolic and regulatory integration.

  11. Modeling Lactococcus lactis using a genome-scale flux model

    Directory of Open Access Journals (Sweden)

    Nielsen Jens

    2005-06-01

    Full Text Available Abstract Background Genome-scale flux models are useful tools to represent and analyze microbial metabolism. In this work we reconstructed the metabolic network of the lactic acid bacteria Lactococcus lactis and developed a genome-scale flux model able to simulate and analyze network capabilities and whole-cell function under aerobic and anaerobic continuous cultures. Flux balance analysis (FBA and minimization of metabolic adjustment (MOMA were used as modeling frameworks. Results The metabolic network was reconstructed using the annotated genome sequence from L. lactis ssp. lactis IL1403 together with physiological and biochemical information. The established network comprised a total of 621 reactions and 509 metabolites, representing the overall metabolism of L. lactis. Experimental data reported in the literature was used to fit the model to phenotypic observations. Regulatory constraints had to be included to simulate certain metabolic features, such as the shift from homo to heterolactic fermentation. A minimal medium for in silico growth was identified, indicating the requirement of four amino acids in addition to a sugar. Remarkably, de novo biosynthesis of four other amino acids was observed even when all amino acids were supplied, which is in good agreement with experimental observations. Additionally, enhanced metabolic engineering strategies for improved diacetyl producing strains were designed. Conclusion The L. lactis metabolic network can now be used for a better understanding of lactococcal metabolic capabilities and potential, for the design of enhanced metabolic engineering strategies and for integration with other types of 'omic' data, to assist in finding new information on cellular organization and function.

  12. Genome-scale constraint-based modeling of Geobacter metallireducens

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    Famili Iman

    2009-01-01

    Full Text Available Abstract Background Geobacter metallireducens was the first organism that can be grown in pure culture to completely oxidize organic compounds with Fe(III oxide serving as electron acceptor. Geobacter species, including G. sulfurreducens and G. metallireducens, are used for bioremediation and electricity generation from waste organic matter and renewable biomass. The constraint-based modeling approach enables the development of genome-scale in silico models that can predict the behavior of complex biological systems and their responses to the environments. Such a modeling approach was applied to provide physiological and ecological insights on the metabolism of G. metallireducens. Results The genome-scale metabolic model of G. metallireducens was constructed to include 747 genes and 697 reactions. Compared to the G. sulfurreducens model, the G. metallireducens metabolic model contains 118 unique reactions that reflect many of G. metallireducens' specific metabolic capabilities. Detailed examination of the G. metallireducens model suggests that its central metabolism contains several energy-inefficient reactions that are not present in the G. sulfurreducens model. Experimental biomass yield of G. metallireducens growing on pyruvate was lower than the predicted optimal biomass yield. Microarray data of G. metallireducens growing with benzoate and acetate indicated that genes encoding these energy-inefficient reactions were up-regulated by benzoate. These results suggested that the energy-inefficient reactions were likely turned off during G. metallireducens growth with acetate for optimal biomass yield, but were up-regulated during growth with complex electron donors such as benzoate for rapid energy generation. Furthermore, several computational modeling approaches were applied to accelerate G. metallireducens research. For example, growth of G. metallireducens with different electron donors and electron acceptors were studied using the genome-scale

  13. Current state of genome-scale modeling in filamentous fungi.

    Science.gov (United States)

    Brandl, Julian; Andersen, Mikael R

    2015-06-01

    The group of filamentous fungi contains important species used in industrial biotechnology for acid, antibiotics and enzyme production. Their unique lifestyle turns these organisms into a valuable genetic reservoir of new natural products and biomass degrading enzymes that has not been used to full capacity. One of the major bottlenecks in the development of new strains into viable industrial hosts is the alteration of the metabolism towards optimal production. Genome-scale models promise a reduction in the time needed for metabolic engineering by predicting the most potent targets in silico before testing them in vivo. The increasing availability of high quality models and molecular biological tools for manipulating filamentous fungi renders the model-guided engineering of these fungal factories possible with comprehensive metabolic networks. A typical fungal model contains on average 1138 unique metabolic reactions and 1050 ORFs, making them a vast knowledge-base of fungal metabolism. In the present review we focus on the current state as well as potential future applications of genome-scale models in filamentous fungi.

  14. Current state of genome-scale modeling in filamentous fungi

    DEFF Research Database (Denmark)

    Brandl, Julian; Andersen, Mikael Rørdam

    2015-01-01

    The group of filamentous fungi contains important species used in industrial biotechnology for acid, antibiotics and enzyme production. Their unique lifestyle turns these organisms into a valuable genetic reservoir of new natural products and biomass degrading enzymes that has not been used to full...... testing them in vivo. The increasing availability of high quality models and molecular biological tools for manipulating filamentous fungi renders the model-guided engineering of these fungal factories possible with comprehensive metabolic networks. A typical fungal model contains on average 1138 unique...... metabolic reactions and 1050 ORFs, making them a vast knowledge-base of fungal metabolism. In the present review we focus on the current state as well as potential future applications of genome-scale models in filamentous fungi....

  15. Next-generation genome-scale models for metabolic engineering

    DEFF Research Database (Denmark)

    King, Zachary A.; Lloyd, Colton J.; Feist, Adam M.

    2015-01-01

    Constraint-based reconstruction and analysis (COBRA) methods have become widely used tools for metabolic engineering in both academic and industrial laboratories. By employing a genome-scale in silico representation of the metabolic network of a host organism, COBRA methods can be used to predict...... optimal genetic modifications that improve the rate and yield of chemical production. A new generation of COBRA models and methods is now being developed. -. encompassing many biological processes and simulation strategies. -. and next-generation models enable new types of predictions. Here, three key...... examples of applying COBRA methods to strain optimization are presented and discussed. Then, an outlook is provided on the next generation of COBRA models and the new types of predictions they will enable for systems metabolic engineering....

  16. Next-generation genome-scale models for metabolic engineering.

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    King, Zachary A; Lloyd, Colton J; Feist, Adam M; Palsson, Bernhard O

    2015-12-01

    Constraint-based reconstruction and analysis (COBRA) methods have become widely used tools for metabolic engineering in both academic and industrial laboratories. By employing a genome-scale in silico representation of the metabolic network of a host organism, COBRA methods can be used to predict optimal genetic modifications that improve the rate and yield of chemical production. A new generation of COBRA models and methods is now being developed--encompassing many biological processes and simulation strategies-and next-generation models enable new types of predictions. Here, three key examples of applying COBRA methods to strain optimization are presented and discussed. Then, an outlook is provided on the next generation of COBRA models and the new types of predictions they will enable for systems metabolic engineering.

  17. Using Genome-scale Models to Predict Biological Capabilities

    DEFF Research Database (Denmark)

    O’Brien, Edward J.; Monk, Jonathan M.; Palsson, Bernhard O.

    2015-01-01

    Constraint-based reconstruction and analysis (COBRA) methods at the genome scale have been under development since the first whole-genome sequences appeared in the mid-1990s. A few years ago, this approach began to demonstrate the ability to predict a range of cellular functions, including cellular...... growth capabilities on various substrates and the effect of gene knockouts at the genome scale. Thus, much interest has developed in understanding and applying these methods to areas such as metabolic engineering, antibiotic design, and organismal and enzyme evolution. This Primer will get you started....

  18. Improving the phenotype predictions of a yeast genome-scale metabolic model by incorporating enzymatic constraints

    DEFF Research Database (Denmark)

    Sanchez, Benjamin J.; Zhang, Xi-Cheng; Nilsson, Avlant

    2017-01-01

    Genome-scale metabolic models (GEMs) are widely used to calculate metabolic phenotypes. They rely on defining a set of constraints, the most common of which is that the production of metabolites and/or growth are limited by the carbon source uptake rate. However, enzyme abundances and kinetics......, which act as limitations on metabolic fluxes, are not taken into account. Here, we present GECKO, a method that enhances a GEM to account for enzymes as part of reactions, thereby ensuring that each metabolic flux does not exceed its maximum capacity, equal to the product of the enzyme's abundance...... with stress, or overexpressing a specific pathway. GECKO also allows to directly integrate quantitative proteomics data; by doing so, we significantly reduced flux variability of the model, in over 60% of metabolic reactions. Additionally, the model gives insight into the distribution of enzyme usage between...

  19. Incorporating Protein Biosynthesis into the Saccharomyces cerevisiae Genome-scale Metabolic Model

    DEFF Research Database (Denmark)

    Olivares Hernandez, Roberto

    Based on stoichiometric biochemical equations that occur into the cell, the genome-scale metabolic models can quantify the metabolic fluxes, which are regarded as the final representation of the physiological state of the cell. For Saccharomyces Cerevisiae the genome scale model has been......, translation initiation, translation elongation, translation termination, translation elongation, and mRNA decay. Considering these information from the mechanisms of transcription and translation, we will include this stoichiometric reactions into the genome scale model for S. Cerevisiae to obtain the first...

  20. BiGG Models: A platform for integrating, standardizing and sharing genome-scale models

    DEFF Research Database (Denmark)

    2016-01-01

    Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized...

  1. BiGG Models: A platform for integrating, standardizing and sharing genome-scale models.

    Science.gov (United States)

    King, Zachary A; Lu, Justin; Dräger, Andreas; Miller, Philip; Federowicz, Stephen; Lerman, Joshua A; Ebrahim, Ali; Palsson, Bernhard O; Lewis, Nathan E

    2016-01-01

    Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scale metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data.

  2. TIGER: Toolbox for integrating genome-scale metabolic models, expression data, and transcriptional regulatory networks

    Directory of Open Access Journals (Sweden)

    Jensen Paul A

    2011-09-01

    Full Text Available Abstract Background Several methods have been developed for analyzing genome-scale models of metabolism and transcriptional regulation. Many of these methods, such as Flux Balance Analysis, use constrained optimization to predict relationships between metabolic flux and the genes that encode and regulate enzyme activity. Recently, mixed integer programming has been used to encode these gene-protein-reaction (GPR relationships into a single optimization problem, but these techniques are often of limited generality and lack a tool for automating the conversion of rules to a coupled regulatory/metabolic model. Results We present TIGER, a Toolbox for Integrating Genome-scale Metabolism, Expression, and Regulation. TIGER converts a series of generalized, Boolean or multilevel rules into a set of mixed integer inequalities. The package also includes implementations of existing algorithms to integrate high-throughput expression data with genome-scale models of metabolism and transcriptional regulation. We demonstrate how TIGER automates the coupling of a genome-scale metabolic model with GPR logic and models of transcriptional regulation, thereby serving as a platform for algorithm development and large-scale metabolic analysis. Additionally, we demonstrate how TIGER's algorithms can be used to identify inconsistencies and improve existing models of transcriptional regulation with examples from the reconstructed transcriptional regulatory network of Saccharomyces cerevisiae. Conclusion The TIGER package provides a consistent platform for algorithm development and extending existing genome-scale metabolic models with regulatory networks and high-throughput data.

  3. Mapping condition-dependent regulation of metabolism in yeast through genome-scale modeling

    DEFF Research Database (Denmark)

    Österlund, Tobias; Nookaew, Intawat; Bordel, Sergio

    2013-01-01

    ABSTRACT: BACKGROUND: The genome-scale metabolic model of Saccharomyces cerevisiae, first presented in 2003, was the first genome-scale network reconstruction for a eukaryotic organism. Since then continuous efforts have been made in order to improve and expand the yeast metabolic network. RESULTS......: Here we present iTO977, a comprehensive genome-scale metabolic model that contains more reactions, metabolites and genes than previous models. The model was constructed based on two earlier reconstructions, namely iIN800 and the consensus network, and then improved and expanded using gap......-filling methods and by introducing new reactions and pathways based on studies of the literature and databases. The model was shown to perform well both for growth simulations in different media and gene essentiality analysis for single and double knock-outs. Further, the model was used as a scaffold...

  4. Diagnostics for stochastic genome-scale modeling via model slicing and debugging.

    Directory of Open Access Journals (Sweden)

    Kevin J Tsai

    Full Text Available Modeling of biological behavior has evolved from simple gene expression plots represented by mathematical equations to genome-scale systems biology networks. However, due to obstacles in complexity and scalability of creating genome-scale models, several biological modelers have turned to programming or scripting languages and away from modeling fundamentals. In doing so, they have traded the ability to have exchangeable, standardized model representation formats, while those that remain true to standardized model representation are faced with challenges in model complexity and analysis. We have developed a model diagnostic methodology inspired by program slicing and debugging and demonstrate the effectiveness of the methodology on a genome-scale metabolic network model published in the BioModels database. The computer-aided identification revealed specific points of interest such as reversibility of reactions, initialization of species amounts, and parameter estimation that improved a candidate cell's adenosine triphosphate production. We then compared the advantages of our methodology over other modeling techniques such as model checking and model reduction. A software application that implements the methodology is available at http://gel.ym.edu.tw/gcs/.

  5. Diagnostics for stochastic genome-scale modeling via model slicing and debugging.

    Science.gov (United States)

    Tsai, Kevin J; Chang, Chuan-Hsiung

    2014-01-01

    Modeling of biological behavior has evolved from simple gene expression plots represented by mathematical equations to genome-scale systems biology networks. However, due to obstacles in complexity and scalability of creating genome-scale models, several biological modelers have turned to programming or scripting languages and away from modeling fundamentals. In doing so, they have traded the ability to have exchangeable, standardized model representation formats, while those that remain true to standardized model representation are faced with challenges in model complexity and analysis. We have developed a model diagnostic methodology inspired by program slicing and debugging and demonstrate the effectiveness of the methodology on a genome-scale metabolic network model published in the BioModels database. The computer-aided identification revealed specific points of interest such as reversibility of reactions, initialization of species amounts, and parameter estimation that improved a candidate cell's adenosine triphosphate production. We then compared the advantages of our methodology over other modeling techniques such as model checking and model reduction. A software application that implements the methodology is available at http://gel.ym.edu.tw/gcs/.

  6. Accomplishments in genome-scale in silico modeling for industrial and medical biotechnology.

    Science.gov (United States)

    Milne, Caroline B; Kim, Pan-Jun; Eddy, James A; Price, Nathan D

    2009-12-01

    Driven by advancements in high-throughput biological technologies and the growing number of sequenced genomes, the construction of in silico models at the genome scale has provided powerful tools to investigate a vast array of biological systems and applications. Here, we review comprehensively the uses of such models in industrial and medical biotechnology, including biofuel generation, food production, and drug development. While the use of in silico models is still in its early stages for delivering to industry, significant initial successes have been achieved. For the cases presented here, genome-scale models predict engineering strategies to enhance properties of interest in an organism or to inhibit harmful mechanisms of pathogens. Going forward, genome-scale in silico models promise to extend their application and analysis scope to become a trans-formative tool in biotechnology.

  7. Advances in the integration of transcriptional regulatory information into genome-scale metabolic models.

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    Vivek-Ananth, R P; Samal, Areejit

    2016-09-01

    A major goal of systems biology is to build predictive computational models of cellular metabolism. Availability of complete genome sequences and wealth of legacy biochemical information has led to the reconstruction of genome-scale metabolic networks in the last 15 years for several organisms across the three domains of life. Due to paucity of information on kinetic parameters associated with metabolic reactions, the constraint-based modelling approach, flux balance analysis (FBA), has proved to be a vital alternative to investigate the capabilities of reconstructed metabolic networks. In parallel, advent of high-throughput technologies has led to the generation of massive amounts of omics data on transcriptional regulation comprising mRNA transcript levels and genome-wide binding profile of transcriptional regulators. A frontier area in metabolic systems biology has been the development of methods to integrate the available transcriptional regulatory information into constraint-based models of reconstructed metabolic networks in order to increase the predictive capabilities of computational models and understand the regulation of cellular metabolism. Here, we review the existing methods to integrate transcriptional regulatory information into constraint-based models of metabolic networks.

  8. MultiMetEval : Comparative and Multi-Objective Analysis of Genome-Scale Metabolic Models

    NARCIS (Netherlands)

    Zakrzewski, Piotr; Medema, Marnix H.; Gevorgyan, Albert; Kierzek, Andrzej M.; Breitling, Rainer; Takano, Eriko; Fong, Stephen S.

    2012-01-01

    Comparative metabolic modelling is emerging as a novel field, supported by the development of reliable and standardized approaches for constructing genome-scale metabolic models in high throughput. New software solutions are needed to allow efficient comparative analysis of multiple models in the co

  9. Modeling Method for Increased Precision and Scope of Directly Measurable Fluxes at a Genome-Scale

    DEFF Research Database (Denmark)

    McCloskey, Douglas; Young, Jamey D.; Xu, Sibei

    2016-01-01

    Metabolic flux analysis (MFA) is considered to be the gold standard for determining the intracellular flux distribution of biological systems. The majority of work using MFA has been limited to core models of metabolism due to challenges in implementing genome-scale MFA and the undesirable trade...... distributions (MIDs),(1) it was found that a total of 232 net fluxes of central and peripheral metabolism could be resolved in the E. coli network. The increase in scope was shown to cover the full biosynthetic route to an expanded set of bioproduction pathways, which should facilitate applications......-off between increased scope and decreased precision in flux estimations. This work presents a tunable workflow for expanding the scope of MFA to the genome-scale without trade-offs in flux precision. The genome-scale MFA model presented here, iDM2014, accounts for 537 net reactions, which includes the core...

  10. Expanding a dynamic flux balance model of yeast fermentation to genome-scale

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    Agosin Eduardo

    2011-05-01

    Full Text Available Abstract Background Yeast is considered to be a workhorse of the biotechnology industry for the production of many value-added chemicals, alcoholic beverages and biofuels. Optimization of the fermentation is a challenging task that greatly benefits from dynamic models able to accurately describe and predict the fermentation profile and resulting products under different genetic and environmental conditions. In this article, we developed and validated a genome-scale dynamic flux balance model, using experimentally determined kinetic constraints. Results Appropriate equations for maintenance, biomass composition, anaerobic metabolism and nutrient uptake are key to improve model performance, especially for predicting glycerol and ethanol synthesis. Prediction profiles of synthesis and consumption of the main metabolites involved in alcoholic fermentation closely agreed with experimental data obtained from numerous lab and industrial fermentations under different environmental conditions. Finally, fermentation simulations of genetically engineered yeasts closely reproduced previously reported experimental results regarding final concentrations of the main fermentation products such as ethanol and glycerol. Conclusion A useful tool to describe, understand and predict metabolite production in batch yeast cultures was developed. The resulting model, if used wisely, could help to search for new metabolic engineering strategies to manage ethanol content in batch fermentations.

  11. Reliable and efficient solution of genome-scale models of Metabolism and macromolecular Expression

    DEFF Research Database (Denmark)

    Ma, Ding; Yang, Laurence; Fleming, Ronan M. T.

    2017-01-01

    Constraint-Based Reconstruction and Analysis (COBRA) is currently the only methodology that permits integrated modeling of Metabolism and macromolecular Expression (ME) at genome-scale. Linear optimization computes steady-state flux solutions to ME models, but flux values are spread over many...

  12. Interplay between Constraints, Objectives, and Optimality for Genome-Scale Stoichiometric Models

    NARCIS (Netherlands)

    Maarleveld, T.R.; Wortel, M.; Olivier, B.G.; Teusink, B.; Bruggeman, F.J.

    2015-01-01

    High-throughput data generation and genome-scale stoichiometric models have greatly facilitated the comprehensive study of metabolic networks. The computation of all feasible metabolic routes with these models, given stoichiometric, thermodynamic, and steady-state constraints, provides important ins

  13. Challenges in experimental data integration within genome-scale metabolic models

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    Képès François

    2010-04-01

    Full Text Available Abstract A report of the meeting "Challenges in experimental data integration within genome-scale metabolic models", Institut Henri Poincaré, Paris, October 10-11 2009, organized by the CNRS-MPG joint program in Systems Biology.

  14. Comparative genome-scale metabolic modeling of actinomycetes : The topology of essential core metabolism

    NARCIS (Netherlands)

    Alam, Mohammad Tauqeer; Medema, Marnix H.; Takano, Eriko; Breitling, Rainer; Gojobori, Takashi

    2011-01-01

    Actinomycetes are highly important bacteria. On one hand, some of them cause severe human and plant diseases, on the other hand, many species are known for their ability to produce antibiotics. Here we report the results of a comparative analysis of genome-scale metabolic models of 37 species of act

  15. Comparative genome-scale metabolic modeling of actinomycetes: the topology of essential core metabolism.

    NARCIS (Netherlands)

    Alam, M.T.; Medema, M.H.; Takano, E.; Breitling, R.

    2011-01-01

    Actinomycetes are highly important bacteria. On one hand, some of them cause severe human and plant diseases, on the other hand, many species are known for their ability to produce antibiotics. Here we report the results of a comparative analysis of genome-scale metabolic models of 37 species of act

  16. Comparative genome-scale metabolic modeling of actinomycetes: the topology of essential core metabolism.

    NARCIS (Netherlands)

    Alam, M.T.; Medema, M.H.; Takano, E.; Breitling, R.

    2011-01-01

    Actinomycetes are highly important bacteria. On one hand, some of them cause severe human and plant diseases, on the other hand, many species are known for their ability to produce antibiotics. Here we report the results of a comparative analysis of genome-scale metabolic models of 37 species of

  17. Comparative genome-scale metabolic modeling of actinomycetes : The topology of essential core metabolism

    NARCIS (Netherlands)

    Alam, Mohammad Tauqeer; Medema, Marnix H.; Takano, Eriko; Breitling, Rainer; Gojobori, Takashi

    2011-01-01

    Actinomycetes are highly important bacteria. On one hand, some of them cause severe human and plant diseases, on the other hand, many species are known for their ability to produce antibiotics. Here we report the results of a comparative analysis of genome-scale metabolic models of 37 species of

  18. Development and experimental verification of a genome-scale metabolic model for Corynebacterium glutamicum

    Directory of Open Access Journals (Sweden)

    Hirasawa Takashi

    2009-08-01

    Full Text Available Abstract Background In silico genome-scale metabolic models enable the analysis of the characteristics of metabolic systems of organisms. In this study, we reconstructed a genome-scale metabolic model of Corynebacterium glutamicum on the basis of genome sequence annotation and physiological data. The metabolic characteristics were analyzed using flux balance analysis (FBA, and the results of FBA were validated using data from culture experiments performed at different oxygen uptake rates. Results The reconstructed genome-scale metabolic model of C. glutamicum contains 502 reactions and 423 metabolites. We collected the reactions and biomass components from the database and literatures, and made the model available for the flux balance analysis by filling gaps in the reaction networks and removing inadequate loop reactions. Using the framework of FBA and our genome-scale metabolic model, we first simulated the changes in the metabolic flux profiles that occur on changing the oxygen uptake rate. The predicted production yields of carbon dioxide and organic acids agreed well with the experimental data. The metabolic profiles of amino acid production phases were also investigated. A comprehensive gene deletion study was performed in which the effects of gene deletions on metabolic fluxes were simulated; this helped in the identification of several genes whose deletion resulted in an improvement in organic acid production. Conclusion The genome-scale metabolic model provides useful information for the evaluation of the metabolic capabilities and prediction of the metabolic characteristics of C. glutamicum. This can form a basis for the in silico design of C. glutamicum metabolic networks for improved bioproduction of desirable metabolites.

  19. Generation and Evaluation of a Genome-Scale Metabolic Network Model of Synechococcus elongatus PCC7942

    Directory of Open Access Journals (Sweden)

    Julián Triana

    2014-08-01

    Full Text Available The reconstruction of genome-scale metabolic models and their applications represent a great advantage of systems biology. Through their use as metabolic flux simulation models, production of industrially-interesting metabolites can be predicted. Due to the growing number of studies of metabolic models driven by the increasing genomic sequencing projects, it is important to conceptualize steps of reconstruction and analysis. We have focused our work in the cyanobacterium Synechococcus elongatus PCC7942, for which several analyses and insights are unveiled. A comprehensive approach has been used, which can be of interest to lead the process of manual curation and genome-scale metabolic analysis. The final model, iSyf715 includes 851 reactions and 838 metabolites. A biomass equation, which encompasses elementary building blocks to allow cell growth, is also included. The applicability of the model is finally demonstrated by simulating autotrophic growth conditions of Synechococcus elongatus PCC7942.

  20. Generation and Evaluation of a Genome-Scale Metabolic Network Model of Synechococcus elongatus PCC7942

    Science.gov (United States)

    Triana, Julián; Montagud†, Arnau; Siurana, Maria; Fuente, David; Urchueguía, Arantxa; Gamermann, Daniel; Torres, Javier; Tena, Jose; de Córdoba, Pedro Fernández; Urchueguía, Javier F.

    2014-01-01

    The reconstruction of genome-scale metabolic models and their applications represent a great advantage of systems biology. Through their use as metabolic flux simulation models, production of industrially-interesting metabolites can be predicted. Due to the growing number of studies of metabolic models driven by the increasing genomic sequencing projects, it is important to conceptualize steps of reconstruction and analysis. We have focused our work in the cyanobacterium Synechococcus elongatus PCC7942, for which several analyses and insights are unveiled. A comprehensive approach has been used, which can be of interest to lead the process of manual curation and genome-scale metabolic analysis. The final model, iSyf715 includes 851 reactions and 838 metabolites. A biomass equation, which encompasses elementary building blocks to allow cell growth, is also included. The applicability of the model is finally demonstrated by simulating autotrophic growth conditions of Synechococcus elongatus PCC7942. PMID:25141288

  1. Pantograph: A template-based method for genome-scale metabolic model reconstruction.

    Science.gov (United States)

    Loira, Nicolas; Zhukova, Anna; Sherman, David James

    2015-04-01

    Genome-scale metabolic models are a powerful tool to study the inner workings of biological systems and to guide applications. The advent of cheap sequencing has brought the opportunity to create metabolic maps of biotechnologically interesting organisms. While this drives the development of new methods and automatic tools, network reconstruction remains a time-consuming process where extensive manual curation is required. This curation introduces specific knowledge about the modeled organism, either explicitly in the form of molecular processes, or indirectly in the form of annotations of the model elements. Paradoxically, this knowledge is usually lost when reconstruction of a different organism is started. We introduce the Pantograph method for metabolic model reconstruction. This method combines a template reaction knowledge base, orthology mappings between two organisms, and experimental phenotypic evidence, to build a genome-scale metabolic model for a target organism. Our method infers implicit knowledge from annotations in the template, and rewrites these inferences to include them in the resulting model of the target organism. The generated model is well suited for manual curation. Scripts for evaluating the model with respect to experimental data are automatically generated, to aid curators in iterative improvement. We present an implementation of the Pantograph method, as a toolbox for genome-scale model reconstruction, curation and validation. This open source package can be obtained from: http://pathtastic.gforge.inria.fr.

  2. Metingear: a development environment for annotating genome-scale metabolic models.

    Science.gov (United States)

    May, John W; James, A Gordon; Steinbeck, Christoph

    2013-09-01

    Genome-scale metabolic models often lack annotations that would allow them to be used for further analysis. Previous efforts have focused on associating metabolites in the model with a cross reference, but this can be problematic if the reference is not freely available, multiple resources are used or the metabolite is added from a literature review. Associating each metabolite with chemical structure provides unambiguous identification of the components and a more detailed view of the metabolism. We have developed an open-source desktop application that simplifies the process of adding database cross references and chemical structures to genome-scale metabolic models. Annotated models can be exported to the Systems Biology Markup Language open interchange format. Source code, binaries, documentation and tutorials are freely available at http://johnmay.github.com/metingear. The application is implemented in Java with bundles available for MS Windows and Macintosh OS X.

  3. Genome-scale metabolic model of Pichia pastoris with native and humanized glycosylation of recombinant proteins

    DEFF Research Database (Denmark)

    Irani, Zahra Azimzadeh; Kerkhoven, Eduard J.; Shojaosadati, Seyed Abbas;

    2016-01-01

    Pichia pastoris is used for commercial production of human therapeutic proteins, and genome-scale models of P. pastoris metabolism have been generated in the past to study the metabolism and associated protein production by this yeast. A major challenge with clinical usage of recombinant proteins...... produced by P. pastoris is the difference in N-glycosylation of proteins produced by humans and this yeast. However, through metabolic engineering, a P. pastoris strain capable of producing humanized N-glycosylated proteins was constructed. The current genome-scale models of P. pastoris do not address...... native nor humanized N-glycosylation, and we therefore developed ihGlycopastoris, an extension to the iLC915 model with both native and humanized N-glycosylation for recombinant protein production, but also an estimation of N-glycosylation of P. pastoris native proteins. This new model gives a better...

  4. Genome-scale modeling of human metabolism - a systems biology approach.

    Science.gov (United States)

    Mardinoglu, Adil; Gatto, Francesco; Nielsen, Jens

    2013-09-01

    Altered metabolism is linked to the appearance of various human diseases and a better understanding of disease-associated metabolic changes may lead to the identification of novel prognostic biomarkers and the development of new therapies. Genome-scale metabolic models (GEMs) have been employed for studying human metabolism in a systematic manner, as well as for understanding complex human diseases. In the past decade, such metabolic models - one of the fundamental aspects of systems biology - have started contributing to the understanding of the mechanistic relationship between genotype and phenotype. In this review, we focus on the construction of the Human Metabolic Reaction database, the generation of healthy cell type- and cancer-specific GEMs using different procedures, and the potential applications of these developments in the study of human metabolism and in the identification of metabolic changes associated with various disorders. We further examine how in silico genome-scale reconstructions can be employed to simulate metabolic flux distributions and how high-throughput omics data can be analyzed in a context-dependent fashion. Insights yielded from this mechanistic modeling approach can be used for identifying new therapeutic agents and drug targets as well as for the discovery of novel biomarkers. Finally, recent advancements in genome-scale modeling and the future challenge of developing a model of whole-body metabolism are presented. The emergent contribution of GEMs to personalized and translational medicine is also discussed. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Construction of an E. Coli genome-scale atom mapping model for MFA calculations.

    Science.gov (United States)

    Ravikirthi, Prabhasa; Suthers, Patrick F; Maranas, Costas D

    2011-06-01

    Metabolic flux analysis (MFA) has so far been restricted to lumped networks lacking many important pathways, partly due to the difficulty in automatically generating isotope mapping matrices for genome-scale metabolic networks. Here we introduce a procedure that uses a compound matching algorithm based on the graph theoretical concept of pattern recognition along with relevant reaction information to automatically generate genome-scale atom mappings which trace the path of atoms from reactants to products for every reaction. The procedure is applied to the iAF1260 metabolic reconstruction of Escherichia coli yielding the genome-scale isotope mapping model imPR90068. This model maps 90,068 non-hydrogen atoms that span all 2,077 reactions present in iAF1260 (previous largest mapping model included 238 reactions). The expanded scope of the isotope mapping model allows the complete tracking of labeled atoms through pathways such as cofactor and prosthetic group biosynthesis and histidine metabolism. An EMU representation of imPR90068 is also constructed and made available.

  6. Modeling Method for Increased Precision and Scope of Directly Measurable Fluxes at a Genome-Scale.

    Science.gov (United States)

    McCloskey, Douglas; Young, Jamey D; Xu, Sibei; Palsson, Bernhard O; Feist, Adam M

    2016-04-05

    Metabolic flux analysis (MFA) is considered to be the gold standard for determining the intracellular flux distribution of biological systems. The majority of work using MFA has been limited to core models of metabolism due to challenges in implementing genome-scale MFA and the undesirable trade-off between increased scope and decreased precision in flux estimations. This work presents a tunable workflow for expanding the scope of MFA to the genome-scale without trade-offs in flux precision. The genome-scale MFA model presented here, iDM2014, accounts for 537 net reactions, which includes the core pathways of traditional MFA models and also covers the additional pathways of purine, pyrimidine, isoprenoid, methionine, riboflavin, coenzyme A, and folate, as well as other biosynthetic pathways. When evaluating the iDM2014 using a set of measured intracellular intermediate and cofactor mass isotopomer distributions (MIDs),1 it was found that a total of 232 net fluxes of central and peripheral metabolism could be resolved in the E. coli network. The increase in scope was shown to cover the full biosynthetic route to an expanded set of bioproduction pathways, which should facilitate applications such as the design of more complex bioprocessing strains and aid in identifying new antimicrobials. Importantly, it was found that there was no loss in precision of core fluxes when compared to a traditional core model, and additionally there was an overall increase in precision when considering all observable reactions.

  7. Genome-Scale Model Reveals Metabolic Basis of Biomass Partitioning in a Model Diatom.

    Directory of Open Access Journals (Sweden)

    Jennifer Levering

    Full Text Available Diatoms are eukaryotic microalgae that contain genes from various sources, including bacteria and the secondary endosymbiotic host. Due to this unique combination of genes, diatoms are taxonomically and functionally distinct from other algae and vascular plants and confer novel metabolic capabilities. Based on the genome annotation, we performed a genome-scale metabolic network reconstruction for the marine diatom Phaeodactylum tricornutum. Due to their endosymbiotic origin, diatoms possess a complex chloroplast structure which complicates the prediction of subcellular protein localization. Based on previous work we implemented a pipeline that exploits a series of bioinformatics tools to predict protein localization. The manually curated reconstructed metabolic network iLB1027_lipid accounts for 1,027 genes associated with 4,456 reactions and 2,172 metabolites distributed across six compartments. To constrain the genome-scale model, we determined the organism specific biomass composition in terms of lipids, carbohydrates, and proteins using Fourier transform infrared spectrometry. Our simulations indicate the presence of a yet unknown glutamine-ornithine shunt that could be used to transfer reducing equivalents generated by photosynthesis to the mitochondria. The model reflects the known biochemical composition of P. tricornutum in defined culture conditions and enables metabolic engineering strategies to improve the use of P. tricornutum for biotechnological applications.

  8. Genome-Scale Model Reveals Metabolic Basis of Biomass Partitioning in a Model Diatom.

    Science.gov (United States)

    Levering, Jennifer; Broddrick, Jared; Dupont, Christopher L; Peers, Graham; Beeri, Karen; Mayers, Joshua; Gallina, Alessandra A; Allen, Andrew E; Palsson, Bernhard O; Zengler, Karsten

    2016-01-01

    Diatoms are eukaryotic microalgae that contain genes from various sources, including bacteria and the secondary endosymbiotic host. Due to this unique combination of genes, diatoms are taxonomically and functionally distinct from other algae and vascular plants and confer novel metabolic capabilities. Based on the genome annotation, we performed a genome-scale metabolic network reconstruction for the marine diatom Phaeodactylum tricornutum. Due to their endosymbiotic origin, diatoms possess a complex chloroplast structure which complicates the prediction of subcellular protein localization. Based on previous work we implemented a pipeline that exploits a series of bioinformatics tools to predict protein localization. The manually curated reconstructed metabolic network iLB1027_lipid accounts for 1,027 genes associated with 4,456 reactions and 2,172 metabolites distributed across six compartments. To constrain the genome-scale model, we determined the organism specific biomass composition in terms of lipids, carbohydrates, and proteins using Fourier transform infrared spectrometry. Our simulations indicate the presence of a yet unknown glutamine-ornithine shunt that could be used to transfer reducing equivalents generated by photosynthesis to the mitochondria. The model reflects the known biochemical composition of P. tricornutum in defined culture conditions and enables metabolic engineering strategies to improve the use of P. tricornutum for biotechnological applications.

  9. Reconstruction of genome-scale metabolic models for 126 human tissues using mCADRE.

    Science.gov (United States)

    Wang, Yuliang; Eddy, James A; Price, Nathan D

    2012-12-13

    Human tissues perform diverse metabolic functions. Mapping out these tissue-specific functions in genome-scale models will advance our understanding of the metabolic basis of various physiological and pathological processes. The global knowledgebase of metabolic functions categorized for the human genome (Human Recon 1) coupled with abundant high-throughput data now makes possible the reconstruction of tissue-specific metabolic models. However, the number of available tissue-specific models remains incomplete compared with the large diversity of human tissues. We developed a method called metabolic Context-specificity Assessed by Deterministic Reaction Evaluation (mCADRE). mCADRE is able to infer a tissue-specific network based on gene expression data and metabolic network topology, along with evaluation of functional capabilities during model building. mCADRE produces models with similar or better functionality and achieves dramatic computational speed up over existing methods. Using our method, we reconstructed draft genome-scale metabolic models for 126 human tissue and cell types. Among these, there are models for 26 tumor tissues along with their normal counterparts, and 30 different brain tissues. We performed pathway-level analyses of this large collection of tissue-specific models and identified the eicosanoid metabolic pathway, especially reactions catalyzing the production of leukotrienes from arachidnoic acid, as potential drug targets that selectively affect tumor tissues. This large collection of 126 genome-scale draft metabolic models provides a useful resource for studying the metabolic basis for a variety of human diseases across many tissues. The functionality of the resulting models and the fast computational speed of the mCADRE algorithm make it a useful tool to build and update tissue-specific metabolic models.

  10. Pore-scale simulation of microbial growth using a genome-scale metabolic model: Implications for Darcy-scale reactive transport

    Science.gov (United States)

    Tartakovsky, G. D.; Tartakovsky, A. M.; Scheibe, T. D.; Fang, Y.; Mahadevan, R.; Lovley, D. R.

    2013-09-01

    Recent advances in microbiology have enabled the quantitative simulation of microbial metabolism and growth based on genome-scale characterization of metabolic pathways and fluxes. We have incorporated a genome-scale metabolic model of the iron-reducing bacteria Geobacter sulfurreducens into a pore-scale simulation of microbial growth based on coupling of iron reduction to oxidation of a soluble electron donor (acetate). In our model, fluid flow and solute transport is governed by a combination of the Navier-Stokes and advection-diffusion-reaction equations. Microbial growth occurs only on the surface of soil grains where solid-phase mineral iron oxides are available. Mass fluxes of chemical species associated with microbial growth are described by the genome-scale microbial model, implemented using a constraint-based metabolic model, and provide the Robin-type boundary condition for the advection-diffusion equation at soil grain surfaces. Conventional models of microbially-mediated subsurface reactions use a lumped reaction model that does not consider individual microbial reaction pathways, and describe reactions rates using empirically-derived rate formulations such as the Monod-type kinetics. We have used our pore-scale model to explore the relationship between genome-scale metabolic models and Monod-type formulations, and to assess the manifestation of pore-scale variability (microenvironments) in terms of apparent Darcy-scale microbial reaction rates. The genome-scale model predicted lower biomass yield, and different stoichiometry for iron consumption, in comparison to prior Monod formulations based on energetics considerations. We were able to fit an equivalent Monod model, by modifying the reaction stoichiometry and biomass yield coefficient, that could effectively match results of the genome-scale simulation of microbial behaviors under excess nutrient conditions, but predictions of the fitted Monod model deviated from those of the genome-scale model

  11. Pore-scale simulation of microbial growth using a genome-scale metabolic model: Implications for Darcy-scale reactive transport

    Energy Technology Data Exchange (ETDEWEB)

    Tartakovsky, Guzel D.; Tartakovsky, Alexandre M.; Scheibe, Timothy D.; Fang, Yilin; Mahadevan, Radhakrishnan; Lovley, Derek R.

    2013-09-07

    Recent advances in microbiology have enabled the quantitative simulation of microbial metabolism and growth based on genome-scale characterization of metabolic pathways and fluxes. We have incorporated a genome-scale metabolic model of the iron-reducing bacteria Geobacter sulfurreducens into a pore-scale simulation of microbial growth based on coupling of iron reduction to oxidation of a soluble electron donor (acetate). In our model, fluid flow and solute transport is governed by a combination of the Navier-Stokes and advection-diffusion-reaction equations. Microbial growth occurs only on the surface of soil grains where solid-phase mineral iron oxides are available. Mass fluxes of chemical species associated with microbial growth are described by the genome-scale microbial model, implemented using a constraint-based metabolic model, and provide the Robin-type boundary condition for the advection-diffusion equation at soil grain surfaces. Conventional models of microbially-mediated subsurface reactions use a lumped reaction model that does not consider individual microbial reaction pathways, and describe reactions rates using empirically-derived rate formulations such as the Monod-type kinetics. We have used our pore-scale model to explore the relationship between genome-scale metabolic models and Monod-type formulations, and to assess the manifestation of pore-scale variability (microenvironments) in terms of apparent Darcy-scale microbial reaction rates. The genome-scale model predicted lower biomass yield, and different stoichiometry for iron consumption, in comparisonto prior Monod formulations based on energetics considerations. We were able to fit an equivalent Monod model, by modifying the reaction stoichiometry and biomass yield coefficient, that could effectively match results of the genome-scale simulation of microbial behaviors under excess nutrient conditions, but predictions of the fitted Monod model deviated from those of the genome-scale model under

  12. Genome-scale dynamic modeling of the competition between Rhodoferax and Geobacter in anoxic subsurface environments.

    Science.gov (United States)

    Zhuang, Kai; Izallalen, Mounir; Mouser, Paula; Richter, Hanno; Risso, Carla; Mahadevan, Radhakrishnan; Lovley, Derek R

    2011-02-01

    The advent of rapid complete genome sequencing, and the potential to capture this information in genome-scale metabolic models, provide the possibility of comprehensively modeling microbial community interactions. For example, Rhodoferax and Geobacter species are acetate-oxidizing Fe(III)-reducers that compete in anoxic subsurface environments and this competition may have an influence on the in situ bioremediation of uranium-contaminated groundwater. Therefore, genome-scale models of Geobacter sulfurreducens and Rhodoferax ferrireducens were used to evaluate how Geobacter and Rhodoferax species might compete under diverse conditions found in a uranium-contaminated aquifer in Rifle, CO. The model predicted that at the low rates of acetate flux expected under natural conditions at the site, Rhodoferax will outcompete Geobacter as long as sufficient ammonium is available. The model also predicted that when high concentrations of acetate are added during in situ bioremediation, Geobacter species would predominate, consistent with field-scale observations. This can be attributed to the higher expected growth yields of Rhodoferax and the ability of Geobacter to fix nitrogen. The modeling predicted relative proportions of Geobacter and Rhodoferax in geochemically distinct zones of the Rifle site that were comparable to those that were previously documented with molecular techniques. The model also predicted that under nitrogen fixation, higher carbon and electron fluxes would be diverted toward respiration rather than biomass formation in Geobacter, providing a potential explanation for enhanced in situ U(VI) reduction in low-ammonium zones. These results show that genome-scale modeling can be a useful tool for predicting microbial interactions in subsurface environments and shows promise for designing bioremediation strategies.

  13. The future of genome-scale modeling of yeast through integration of a transcriptional regulatory network

    DEFF Research Database (Denmark)

    Liu, Guodong; Marras, Antonio; Nielsen, Jens

    2014-01-01

    regulatory information is necessary to improve the accuracy and predictive ability of metabolic models. Here we review the strategies for the reconstruction of a transcriptional regulatory network (TRN) for yeast and the integration of such a reconstruction into a flux balance analysis-based metabolic model......Metabolism is regulated at multiple levels in response to the changes of internal or external conditions. Transcriptional regulation plays an important role in regulating many metabolic reactions by altering the concentrations of metabolic enzymes. Thus, integration of the transcriptional...... transcriptional regulatory interactions to genome-scale metabolic models in a quantitative manner....

  14. Investigating host-pathogen behavior and their interaction using genome-scale metabolic network models.

    Science.gov (United States)

    Sadhukhan, Priyanka P; Raghunathan, Anu

    2014-01-01

    Genome Scale Metabolic Modeling methods represent one way to compute whole cell function starting from the genome sequence of an organism and contribute towards understanding and predicting the genotype-phenotype relationship. About 80 models spanning all the kingdoms of life from archaea to eukaryotes have been built till date and used to interrogate cell phenotype under varying conditions. These models have been used to not only understand the flux distribution in evolutionary conserved pathways like glycolysis and the Krebs cycle but also in applications ranging from value added product formation in Escherichia coli to predicting inborn errors of Homo sapiens metabolism. This chapter describes a protocol that delineates the process of genome scale metabolic modeling for analysing host-pathogen behavior and interaction using flux balance analysis (FBA). The steps discussed in the process include (1) reconstruction of a metabolic network from the genome sequence, (2) its representation in a precise mathematical framework, (3) its translation to a model, and (4) the analysis using linear algebra and optimization. The methods for biological interpretations of computed cell phenotypes in the context of individual host and pathogen models and their integration are also discussed.

  15. Metingear: a development environment for annotating genome-scale metabolic models

    Science.gov (United States)

    May, John W.; James, A. Gordon; Steinbeck, Christoph

    2013-01-01

    Summary: Genome-scale metabolic models often lack annotations that would allow them to be used for further analysis. Previous efforts have focused on associating metabolites in the model with a cross reference, but this can be problematic if the reference is not freely available, multiple resources are used or the metabolite is added from a literature review. Associating each metabolite with chemical structure provides unambiguous identification of the components and a more detailed view of the metabolism. We have developed an open-source desktop application that simplifies the process of adding database cross references and chemical structures to genome-scale metabolic models. Annotated models can be exported to the Systems Biology Markup Language open interchange format. Availability: Source code, binaries, documentation and tutorials are freely available at http://johnmay.github.com/metingear. The application is implemented in Java with bundles available for MS Windows and Macintosh OS X. Contact: johnmay@ebi.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23766418

  16. A genome-scale metabolic model of the lipid-accumulating yeast Yarrowia lipolytica

    Directory of Open Access Journals (Sweden)

    Loira Nicolas

    2012-05-01

    Full Text Available Abstract Background Yarrowia lipolytica is an oleaginous yeast which has emerged as an important microorganism for several biotechnological processes, such as the production of organic acids, lipases and proteases. It is also considered a good candidate for single-cell oil production. Although some of its metabolic pathways are well studied, its metabolic engineering is hindered by the lack of a genome-scale model that integrates the current knowledge about its metabolism. Results Combining in silico tools and expert manual curation, we have produced an accurate genome-scale metabolic model for Y. lipolytica. Using a scaffold derived from a functional metabolic model of the well-studied but phylogenetically distant yeast S. cerevisiae, we mapped conserved reactions, rewrote gene associations, added species-specific reactions and inserted specialized copies of scaffold reactions to account for species-specific expansion of protein families. We used physiological measures obtained under lab conditions to validate our predictions. Conclusions Y. lipolytica iNL895 represents the first well-annotated metabolic model of an oleaginous yeast, providing a base for future metabolic improvement, and a starting point for the metabolic reconstruction of other species in the Yarrowia clade and other oleaginous yeasts.

  17. Network thermodynamic curation of human and yeast genome-scale metabolic models.

    Science.gov (United States)

    Martínez, Verónica S; Quek, Lake-Ee; Nielsen, Lars K

    2014-07-15

    Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties.

  18. Principles of proteome allocation are revealed using proteomic data and genome-scale models

    DEFF Research Database (Denmark)

    Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.

    2016-01-01

    , prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thus represents a generalist ME model reflecting both growth rate maximization and "hedging" against uncertain environments and stresses, as indicated by significant enrichment...... of these sectors for the general stress response sigma factor sigma(S). Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally......Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked...

  19. A Method to Constrain Genome-Scale Models with 13C Labeling Data.

    Directory of Open Access Journals (Sweden)

    Héctor García Martín

    2015-09-01

    Full Text Available Current limitations in quantitatively predicting biological behavior hinder our efforts to engineer biological systems to produce biofuels and other desired chemicals. Here, we present a new method for calculating metabolic fluxes, key targets in metabolic engineering, that incorporates data from 13C labeling experiments and genome-scale models. The data from 13C labeling experiments provide strong flux constraints that eliminate the need to assume an evolutionary optimization principle such as the growth rate optimization assumption used in Flux Balance Analysis (FBA. This effective constraining is achieved by making the simple but biologically relevant assumption that flux flows from core to peripheral metabolism and does not flow back. The new method is significantly more robust than FBA with respect to errors in genome-scale model reconstruction. Furthermore, it can provide a comprehensive picture of metabolite balancing and predictions for unmeasured extracellular fluxes as constrained by 13C labeling data. A comparison shows that the results of this new method are similar to those found through 13C Metabolic Flux Analysis (13C MFA for central carbon metabolism but, additionally, it provides flux estimates for peripheral metabolism. The extra validation gained by matching 48 relative labeling measurements is used to identify where and why several existing COnstraint Based Reconstruction and Analysis (COBRA flux prediction algorithms fail. We demonstrate how to use this knowledge to refine these methods and improve their predictive capabilities. This method provides a reliable base upon which to improve the design of biological systems.

  20. Reliable and efficient solution of genome-scale models of Metabolism and macromolecular Expression

    Science.gov (United States)

    Ma, Ding; Yang, Laurence; Fleming, Ronan M. T.; Thiele, Ines; Palsson, Bernhard O.; Saunders, Michael A.

    2017-01-01

    Constraint-Based Reconstruction and Analysis (COBRA) is currently the only methodology that permits integrated modeling of Metabolism and macromolecular Expression (ME) at genome-scale. Linear optimization computes steady-state flux solutions to ME models, but flux values are spread over many orders of magnitude. Data values also have greatly varying magnitudes. Standard double-precision solvers may return inaccurate solutions or report that no solution exists. Exact simplex solvers based on rational arithmetic require a near-optimal warm start to be practical on large problems (current ME models have 70,000 constraints and variables and will grow larger). We have developed a quadruple-precision version of our linear and nonlinear optimizer MINOS, and a solution procedure (DQQ) involving Double and Quad MINOS that achieves reliability and efficiency for ME models and other challenging problems tested here. DQQ will enable extensive use of large linear and nonlinear models in systems biology and other applications involving multiscale data.

  1. A metabolite-centric view on flux distributions in genome-scale metabolic models.

    Science.gov (United States)

    Riemer, S Alexander; Rex, René; Schomburg, Dietmar

    2013-04-12

    Genome-scale metabolic models are important tools in systems biology. They permit the in-silico prediction of cellular phenotypes via mathematical optimisation procedures, most importantly flux balance analysis. Current studies on metabolic models mostly consider reaction fluxes in isolation. Based on a recently proposed metabolite-centric approach, we here describe a set of methods that enable the analysis and interpretation of flux distributions in an integrated metabolite-centric view. We demonstrate how this framework can be used for the refinement of genome-scale metabolic models. We applied the metabolite-centric view developed here to the most recent metabolic reconstruction of Escherichia coli. By compiling the balance sheets of a small number of currency metabolites, we were able to fully characterise the energy metabolism as predicted by the model and to identify a possibility for model refinement in NADPH metabolism. Selected branch points were examined in detail in order to demonstrate how a metabolite-centric view allows identifying functional roles of metabolites. Fructose 6-phosphate aldolase and the sedoheptulose bisphosphate bypass were identified as enzymatic reactions that can carry high fluxes in the model but are unlikely to exhibit significant activity in vivo. Performing a metabolite essentiality analysis, unconstrained import and export of iron ions could be identified as potentially problematic for the quality of model predictions. The system-wide analysis of split ratios and branch points allows a much deeper insight into the metabolic network than reaction-centric analyses. Extending an earlier metabolite-centric approach, the methods introduced here establish an integrated metabolite-centric framework for the interpretation of flux distributions in genome-scale metabolic networks that can complement the classical reaction-centric framework. Analysing fluxes and their metabolic context simultaneously opens the door to systems biological

  2. iAK692: A genome-scale metabolic model of Spirulina platensis C1

    Science.gov (United States)

    2012-01-01

    Background Spirulina (Arthrospira) platensis is a well-known filamentous cyanobacterium used in the production of many industrial products, including high value compounds, healthy food supplements, animal feeds, pharmaceuticals and cosmetics, for example. It has been increasingly studied around the world for scientific purposes, especially for its genome, biology, physiology, and also for the analysis of its small-scale metabolic network. However, the overall description of the metabolic and biotechnological capabilities of S. platensis requires the development of a whole cellular metabolism model. Recently, the S. platensis C1 (Arthrospira sp. PCC9438) genome sequence has become available, allowing systems-level studies of this commercial cyanobacterium. Results In this work, we present the genome-scale metabolic network analysis of S. platensis C1, iAK692, its topological properties, and its metabolic capabilities and functions. The network was reconstructed from the S. platensis C1 annotated genomic sequence using Pathway Tools software to generate a preliminary network. Then, manual curation was performed based on a collective knowledge base and a combination of genomic, biochemical, and physiological information. The genome-scale metabolic model consists of 692 genes, 837 metabolites, and 875 reactions. We validated iAK692 by conducting fermentation experiments and simulating the model under autotrophic, heterotrophic, and mixotrophic growth conditions using COBRA toolbox. The model predictions under these growth conditions were consistent with the experimental results. The iAK692 model was further used to predict the unique active reactions and essential genes for each growth condition. Additionally, the metabolic states of iAK692 during autotrophic and mixotrophic growths were described by phenotypic phase plane (PhPP) analysis. Conclusions This study proposes the first genome-scale model of S. platensis C1, iAK692, which is a predictive metabolic platform

  3. iAK692: A genome-scale metabolic model of Spirulina platensis C1

    Directory of Open Access Journals (Sweden)

    Klanchui Amornpan

    2012-06-01

    Full Text Available Abstract Background Spirulina (Arthrospira platensis is a well-known filamentous cyanobacterium used in the production of many industrial products, including high value compounds, healthy food supplements, animal feeds, pharmaceuticals and cosmetics, for example. It has been increasingly studied around the world for scientific purposes, especially for its genome, biology, physiology, and also for the analysis of its small-scale metabolic network. However, the overall description of the metabolic and biotechnological capabilities of S. platensis requires the development of a whole cellular metabolism model. Recently, the S. platensis C1 (Arthrospira sp. PCC9438 genome sequence has become available, allowing systems-level studies of this commercial cyanobacterium. Results In this work, we present the genome-scale metabolic network analysis of S. platensis C1, iAK692, its topological properties, and its metabolic capabilities and functions. The network was reconstructed from the S. platensis C1 annotated genomic sequence using Pathway Tools software to generate a preliminary network. Then, manual curation was performed based on a collective knowledge base and a combination of genomic, biochemical, and physiological information. The genome-scale metabolic model consists of 692 genes, 837 metabolites, and 875 reactions. We validated iAK692 by conducting fermentation experiments and simulating the model under autotrophic, heterotrophic, and mixotrophic growth conditions using COBRA toolbox. The model predictions under these growth conditions were consistent with the experimental results. The iAK692 model was further used to predict the unique active reactions and essential genes for each growth condition. Additionally, the metabolic states of iAK692 during autotrophic and mixotrophic growths were described by phenotypic phase plane (PhPP analysis. Conclusions This study proposes the first genome-scale model of S. platensis C1, iAK692, which is a

  4. Improved Evidence-Based Genome-scale Metabolic Models for Maize Leaf, Embryo, and Endosperm

    Energy Technology Data Exchange (ETDEWEB)

    Seaver, Samuel M.D.; Frelin, Oceane; Bradbury, Louis M.T.; Zarecki, Raphy; Ruppin, Eytan; Hanson, Andrew D.; Henry, Christopher S.

    2015-03-10

    There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions and possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes.

  5. Improved Evidence-Based Genome-scale Metabolic Models for Maize Leaf, Embryo, and Endosperm.

    Directory of Open Access Journals (Sweden)

    Samuel eSeaver

    2015-03-01

    Full Text Available There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions and possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes.

  6. Integration of gene expression data into genome-scale metabolic models

    DEFF Research Database (Denmark)

    Åkesson, M.; Förster, Jochen; Nielsen, Jens

    2004-01-01

    of gene expression from chemostat and batch cultures of Saccharomyces cerevisiae were combined with a recently developed genome-scale model, and the computed metabolic flux distributions were compared to experimental values from carbon labeling experiments and metabolic network analysis. The integration......A framework for integration of transcriptome data into stoichiometric metabolic models to obtain improved flux predictions is presented. The key idea is to exploit the regulatory information in the expression data to give additional constraints on the metabolic fluxes in the model. Measurements...... of expression data resulted in improved predictions of metabolic behavior in batch cultures, enabling quantitative predictions of exchange fluxes as well as qualitative estimations of changes in intracellular fluxes. A critical discussion of correlation between gene expression and metabolic fluxes is given....

  7. Identifying anti-growth factors for human cancer cell lines through genome-scale metabolic modeling

    DEFF Research Database (Denmark)

    Ghaffari, Pouyan; Mardinoglu, Adil; Asplund, Anna

    2015-01-01

    Human cancer cell lines are used as important model systems to study molecular mechanisms associated with tumor growth, hereunder how genomic and biological heterogeneity found in primary tumors affect cellular phenotypes. We reconstructed Genome scale metabolic models (GEMs) for eleven cell lines...... based on RNA-Seq data and validated the functionality of these models with data from metabolite profiling. We used cell line-specific GEMs to analyze the differences in the metabolism of cancer cell lines, and to explore the heterogeneous expression of the metabolic subsystems. Furthermore, we predicted...... antimetabolites using two cell lines with different phenotypic origins, and found that it is effective in inhibiting the growth of these cell lines. Using immunohistochemistry, we also showed high or moderate expression levels of proteins targeted by the validated antimetabolite. Identified anti-growth factors...

  8. Genome-scale modeling of the protein secretory machinery in yeast.

    Science.gov (United States)

    Feizi, Amir; Österlund, Tobias; Petranovic, Dina; Bordel, Sergio; Nielsen, Jens

    2013-01-01

    The protein secretory machinery in Eukarya is involved in post-translational modification (PTMs) and sorting of the secretory and many transmembrane proteins. While the secretory machinery has been well-studied using classic reductionist approaches, a holistic view of its complex nature is lacking. Here, we present the first genome-scale model for the yeast secretory machinery which captures the knowledge generated through more than 50 years of research. The model is based on the concept of a Protein Specific Information Matrix (PSIM: characterized by seven PTMs features). An algorithm was developed which mimics secretory machinery and assigns each secretory protein to a particular secretory class that determines the set of PTMs and transport steps specific to each protein. Protein abundances were integrated with the model in order to gain system level estimation of the metabolic demands associated with the processing of each specific protein as well as a quantitative estimation of the activity of each component of the secretory machinery.

  9. Genome scale models of yeast: towards standardized evaluation and consistent omic integration

    DEFF Research Database (Denmark)

    Sanchez, Benjamin J.; Nielsen, Jens

    2015-01-01

    Genome scale models (GEMs) have enabled remarkable advances in systems biology, acting as functional databases of metabolism, and as scaffolds for the contextualization of high-throughput data. In the case of Saccharomyces cerevisiae (budding yeast), several GEMs have been published...... and are currently used for metabolic engineering and elucidating biological interactions. Here we review the history of yeast's GEMs, focusing on recent developments. We study how these models are typically evaluated, using both descriptive and predictive metrics. Additionally, we analyze the different ways...... in which all levels of omics data (from gene expression to flux) have been integrated in yeast GEMs. Relevant conclusions and current challenges for both GEM evaluation and omic integration are highlighted....

  10. Improved annotation through genome-scale metabolic modeling of Aspergillus oryzae

    DEFF Research Database (Denmark)

    Vongsangnak, Wanwipa; Olsen, Peter; Hansen, Kim;

    2008-01-01

    to a genome scale metabolic model of A. oryzae. Results: Our assembled EST sequences we identified 1,046 newly predicted genes in the A. oryzae genome. Furthermore, it was possible to assign putative protein functions to 398 of the newly predicted genes. Noteworthy, our annotation strategy resulted......Background: Since ancient times the filamentous fungus Aspergillus oryzae has been used in the fermentation industry for the production of fermented sauces and the production of industrial enzymes. Recently, the genome sequence of A. oryzae with 12,074 annotated genes was released but the number...... of hypothetical proteins accounted for more than 50% of the annotated genes. Considering the industrial importance of this fungus, it is therefore valuable to improve the annotation and further integrate genomic information with biochemical and physiological information available for this microorganism and other...

  11. A Genome-Scale Model of Shewanella piezotolerans Simulates Mechanisms of Metabolic Diversity and Energy Conservation.

    Science.gov (United States)

    Dufault-Thompson, Keith; Jian, Huahua; Cheng, Ruixue; Li, Jiefu; Wang, Fengping; Zhang, Ying

    2017-01-01

    Shewanella piezotolerans strain WP3 belongs to the group 1 branch of the Shewanella genus and is a piezotolerant and psychrotolerant species isolated from the deep sea. In this study, a genome-scale model was constructed for WP3 using a combination of genome annotation, ortholog mapping, and physiological verification. The metabolic reconstruction contained 806 genes, 653 metabolites, and 922 reactions, including central metabolic functions that represented nonhomologous replacements between the group 1 and group 2 Shewanella species. Metabolic simulations with the WP3 model demonstrated consistency with existing knowledge about the physiology of the organism. A comparison of model simulations with experimental measurements verified the predicted growth profiles under increasing concentrations of carbon sources. The WP3 model was applied to study mechanisms of anaerobic respiration through investigating energy conservation, redox balancing, and the generation of proton motive force. Despite being an obligate respiratory organism, WP3 was predicted to use substrate-level phosphorylation as the primary source of energy conservation under anaerobic conditions, a trait previously identified in other Shewanella species. Further investigation of the ATP synthase activity revealed a positive correlation between the availability of reducing equivalents in the cell and the directionality of the ATP synthase reaction flux. Comparison of the WP3 model with an existing model of a group 2 species, Shewanella oneidensis MR-1, revealed that the WP3 model demonstrated greater flexibility in ATP production under the anaerobic conditions. Such flexibility could be advantageous to WP3 for its adaptation to fluctuating availability of organic carbon sources in the deep sea. IMPORTANCE The well-studied nature of the metabolic diversity of Shewanella bacteria makes species from this genus a promising platform for investigating the evolution of carbon metabolism and energy conservation

  12. Analysis of growth of Lactobacillus plantarum WCFS1 on a complex medium using a genome-scale metabolic model

    NARCIS (Netherlands)

    Teusink, B.; Wiersma, A.; Molenaar, D.; Francke, C.; Vos, de W.M.; Siezen, R.J.; Smid, E.J.

    2006-01-01

    A genome-scale metabolic model of the lactic acid bacterium Lactobacillus plantarum WCFS1 was constructed based on genomic content and experimental data. The complete model includes 721 genes, 643 reactions, and 531 metabolites. Different stoichiometric modeling techniques were used for interpretati

  13. Reframed Genome-Scale Metabolic Model to Facilitate Genetic Design and Integration with Expression Data.

    Science.gov (United States)

    Gu, Deqing; Jian, Xingxing; Zhang, Cheng; Hua, Qiang

    2016-06-08

    Genome-scale metabolic network models (GEMs) have played important roles in the design of genetically engineered strains and helped biologists to decipher metabolism. However, due to the complex gene-reaction relationships that exist in model systems, most algorithms have limited capabilities with respect to directly predicting accurate genetic design for metabolic engineering. In particular, methods that predict reaction knockout strategies leading to overproduction are often impractical in terms of gene manipulations. Recently, we proposed a method named LTM (logical transformation of model) to simplify the gene-reaction associations by introducing intermediate pseudo reactions, which makes it possible to generate genetic design. Here, we propose an alternative method to relieve researchers from deciphering complex gene-reactions by adding pseudo gene controlling reactions. In comparison to LTM, this new method introduces fewer pseudo reactions and generates a much smaller model system named as gModel. We showed that gModel allows two seldom reported applications: identification of minimal genomes and design of minimal cell factories within a modified OptKnock framework. In addition, gModel could be used to integrate expression data directly and improve the performance of the E-Fmin method for predicting fluxes. In conclusion, the model transformation procedure will facilitate genetic research based on GEMs, extending their applications.

  14. redGEM: Systematic reduction and analysis of genome-scale metabolic reconstructions for development of consistent core metabolic models.

    Science.gov (United States)

    Ataman, Meric; Hernandez Gardiol, Daniel F; Fengos, Georgios; Hatzimanikatis, Vassily

    2017-07-01

    Genome-scale metabolic reconstructions have proven to be valuable resources in enhancing our understanding of metabolic networks as they encapsulate all known metabolic capabilities of the organisms from genes to proteins to their functions. However the complexity of these large metabolic networks often hinders their utility in various practical applications. Although reduced models are commonly used for modeling and in integrating experimental data, they are often inconsistent across different studies and laboratories due to different criteria and detail, which can compromise transferability of the findings and also integration of experimental data from different groups. In this study, we have developed a systematic semi-automatic approach to reduce genome-scale models into core models in a consistent and logical manner focusing on the central metabolism or subsystems of interest. The method minimizes the loss of information using an approach that combines graph-based search and optimization methods. The resulting core models are shown to be able to capture key properties of the genome-scale models and preserve consistency in terms of biomass and by-product yields, flux and concentration variability and gene essentiality. The development of these "consistently-reduced" models will help to clarify and facilitate integration of different experimental data to draw new understanding that can be directly extendable to genome-scale models.

  15. redGEM: Systematic reduction and analysis of genome-scale metabolic reconstructions for development of consistent core metabolic models.

    Directory of Open Access Journals (Sweden)

    Meric Ataman

    2017-07-01

    Full Text Available Genome-scale metabolic reconstructions have proven to be valuable resources in enhancing our understanding of metabolic networks as they encapsulate all known metabolic capabilities of the organisms from genes to proteins to their functions. However the complexity of these large metabolic networks often hinders their utility in various practical applications. Although reduced models are commonly used for modeling and in integrating experimental data, they are often inconsistent across different studies and laboratories due to different criteria and detail, which can compromise transferability of the findings and also integration of experimental data from different groups. In this study, we have developed a systematic semi-automatic approach to reduce genome-scale models into core models in a consistent and logical manner focusing on the central metabolism or subsystems of interest. The method minimizes the loss of information using an approach that combines graph-based search and optimization methods. The resulting core models are shown to be able to capture key properties of the genome-scale models and preserve consistency in terms of biomass and by-product yields, flux and concentration variability and gene essentiality. The development of these "consistently-reduced" models will help to clarify and facilitate integration of different experimental data to draw new understanding that can be directly extendable to genome-scale models.

  16. Genome-Scale Metabolic Modeling of Archaea Lends Insight into Diversity of Metabolic Function

    Science.gov (United States)

    2017-01-01

    Decades of biochemical, bioinformatic, and sequencing data are currently being systematically compiled into genome-scale metabolic reconstructions (GEMs). Such reconstructions are knowledge-bases useful for engineering, modeling, and comparative analysis. Here we review the fifteen GEMs of archaeal species that have been constructed to date. They represent primarily members of the Euryarchaeota with three-quarters comprising representative of methanogens. Unlike other reviews on GEMs, we specially focus on archaea. We briefly review the GEM construction process and the genealogy of the archaeal models. The major insights gained during the construction of these models are then reviewed with specific focus on novel metabolic pathway predictions and growth characteristics. Metabolic pathway usage is discussed in the context of the composition of each organism's biomass and their specific energy and growth requirements. We show how the metabolic models can be used to study the evolution of metabolism in archaea. Conservation of particular metabolic pathways can be studied by comparing reactions using the genes associated with their enzymes. This demonstrates the utility of GEMs to evolutionary studies, far beyond their original purpose of metabolic modeling; however, much needs to be done before archaeal models are as extensively complete as those for bacteria. PMID:28133437

  17. MapMaker and PathTracer for tracking carbon in genome-scale metabolic models.

    Science.gov (United States)

    Tervo, Christopher J; Reed, Jennifer L

    2016-05-01

    Constraint-based reconstruction and analysis (COBRA) modeling results can be difficult to interpret given the large numbers of reactions in genome-scale models. While paths in metabolic networks can be found, existing methods are not easily combined with constraint-based approaches. To address this limitation, two tools (MapMaker and PathTracer) were developed to find paths (including cycles) between metabolites, where each step transfers carbon from reactant to product. MapMaker predicts carbon transfer maps (CTMs) between metabolites using only information on molecular formulae and reaction stoichiometry, effectively determining which reactants and products share carbon atoms. MapMaker correctly assigned CTMs for over 97% of the 2,251 reactions in an Escherichia coli metabolic model (iJO1366). Using CTMs as inputs, PathTracer finds paths between two metabolites. PathTracer was applied to iJO1366 to investigate the importance of using CTMs and COBRA constraints when enumerating paths, to find active and high flux paths in flux balance analysis (FBA) solutions, to identify paths for putrescine utilization, and to elucidate a potential CO2 fixation pathway in E. coli. These results illustrate how MapMaker and PathTracer can be used in combination with constraint-based models to identify feasible, active, and high flux paths between metabolites.

  18. Integration of Genome-Scale Metabolic Nodels of Iron-Reducing Bacteria With Subsurface Flow and Geochemical Reactive Transport Models

    Science.gov (United States)

    Scheibe, T. D.; Mahadevan, R.; Fang, Y.; Garg, S.; Long, P. E.; Lovley, D. M.

    2008-12-01

    Several field and laboratory experiments have demonstrated that the growth and activity of iron-reducing bacteria can be stimulated in many subsurface environments by amendment of groundwater with a soluble electron donor. Under strong iron-reducing conditions, these organisms mediate reactions that can impact a wide range of subsurface contaminants including chlorinated hydrocarbons, metals, and radionuclides. Therefore there is strong interest in in-situ bioremediation as a potential technology for cleanup of contaminated aquifers. To evaluate and design bioremediation systems, as well as to evaluate the viability of monitored natural attenuation as an alternative, quantitative models of biogeochemically reactive transport are needed. To date, most such models represent microbial activity in terms of kinetic rate (e.g., Monod- type) formulations. Such models do not account for fundamental changes in microbial functionality (such as utilization of alternative respiratory pathways) that occur as the result of spatial and temporal variations in the geochemical environment experienced by microorganisms. Constraint-based genome-scale in silico models of microbial metabolism present an alternative to simplified rate formulations that provide flexibility to account for changes in microbial function in response to local geochemical conditions. We have developed and applied a methodology for coupling a constraint-based in silico model of Geobacter sulfurreducens with a conventional model of groundwater flow, transport, and geochemical reaction. Two uses of the in silico model are tested: 1) incorporation of modified microbial growth yield coefficients based on the in silico model, and 2) variation of reaction rates in a reactive transport model based on in silico modeling of a range of local geochemical conditions. Preliminary results from this integrated model will be presented.

  19. Genome-Scale Metabolic Modeling in the Simulation of Field-Scale Uranium Bioremediation

    Science.gov (United States)

    Yabusaki, S.; Wilkins, M.; Fang, Y.; Williams, K. H.; Waichler, S.; Long, P. E.

    2015-12-01

    Coupled variably saturated flow and biogeochemical reactive transport modeling is used to improve understanding of the processes, properties, and conditions controlling uranium bio-immobilization in a field experiment where uranium-contaminated groundwater was amended with acetate and bicarbonate. The acetate stimulates indigenous microorganisms that catalyze metal reduction, including the conversion of aqueous U(VI) to solid-phase U(IV), which effectively removes uranium from solution. The initiation of the bicarbonate amendment prior to biostimulation was designed to promote U(VI) desorption that would increase the aqueous U(VI) available for bioreduction. The three-dimensional simulations were able to largely reproduce the timing and magnitude of the physical, chemical and biological responses to the acetate and bicarbonate amendment in the context of changing water table elevation and gradient. A time series of groundwater proteomic samples exhibited correlations between the most abundant Geobacter metallireducens proteins and the genome-scale metabolic model-predicted fluxes of intra-cellular reactions associated with each of those proteins. The desorption of U(VI) induced by the bicarbonate amendment led to initially higher rates of bioreduction compared to locations with minimal bicarbonate exposure. After bicarbonate amendment ceased, bioreduction continued at these locations whereas U(VI) sorption was the dominant removal mechanism at the bicarbonate-impacted sites.

  20. Deriving metabolic engineering strategies from genome-scale modeling with flux ratio constraints.

    Science.gov (United States)

    Yen, Jiun Y; Nazem-Bokaee, Hadi; Freedman, Benjamin G; Athamneh, Ahmad I M; Senger, Ryan S

    2013-05-01

    Optimized production of bio-based fuels and chemicals from microbial cell factories is a central goal of systems metabolic engineering. To achieve this goal, a new computational method of using flux balance analysis with flux ratios (FBrAtio) was further developed in this research and applied to five case studies to evaluate and design metabolic engineering strategies. The approach was implemented using publicly available genome-scale metabolic flux models. Synthetic pathways were added to these models along with flux ratio constraints by FBrAtio to achieve increased (i) cellulose production from Arabidopsis thaliana; (ii) isobutanol production from Saccharomyces cerevisiae; (iii) acetone production from Synechocystis sp. PCC6803; (iv) H2 production from Escherichia coli MG1655; and (v) isopropanol, butanol, and ethanol (IBE) production from engineered Clostridium acetobutylicum. The FBrAtio approach was applied to each case to simulate a metabolic engineering strategy already implemented experimentally, and flux ratios were continually adjusted to find (i) the end-limit of increased production using the existing strategy, (ii) new potential strategies to increase production, and (iii) the impact of these metabolic engineering strategies on product yield and culture growth. The FBrAtio approach has the potential to design "fine-tuned" metabolic engineering strategies in silico that can be implemented directly with available genomic tools.

  1. Revealing the mystery of metabolic adaptations using a genome scale model of Leishmania infantum.

    Science.gov (United States)

    Subramanian, Abhishek; Sarkar, Ram Rup

    2017-08-31

    Human macrophage phagolysosome and sandfly midgut provide antagonistic ecological niches for Leishmania parasites to survive and proliferate. Parasites optimize their metabolism to utilize the available inadequate resources by adapting to those environments. Lately, a number of metabolomics studies have revived the interest to understand metabolic strategies utilized by the Leishmania parasite for optimal survival within its hosts. For the first time, we propose a reconstructed genome-scale metabolic model for Leishmania infantum JPCM5, the analyses of which not only captures observations reported by metabolomics studies in other Leishmania species but also divulges novel features of the L. infantum metabolome. Our results indicate that Leishmania metabolism is organized in such a way that the parasite can select appropriate alternatives to compensate for limited external substrates. A dynamic non-essential amino acid motif exists within the network that promotes a restricted redistribution of resources to yield required essential metabolites. Further, subcellular compartments regulate this metabolic re-routing by reinforcing the physiological coupling of specific reactions. This unique metabolic organization is robust against accidental errors and provides a wide array of choices for the parasite to achieve optimal survival.

  2. Analysis of genetic variation and potential applications in genome-scale metabolic modeling

    Directory of Open Access Journals (Sweden)

    João Gonçalo Rocha Cardoso

    2015-02-01

    Full Text Available Genetic variation is the motor of evolution and allows organisms to overcome the environmental challenges they encounter. It can be both beneficial and harmful in the process of engineering cell factories for the production of proteins and chemicals. Throughout the history of biotechnology, there have been efforts to exploit genetic variation in our favor to create strains with favorable phenotypes. Genetic variation can either be present in natural populations or it can be artificially created by mutagenesis and selection or adaptive laboratory evolution. On the other hand, unintended genetic variation during a long term production process may lead to significant economic losses and it is important to understand how to control this type of variation. With the emergence of next-generation sequencing technologies, genetic variation in microbial strains can now be determined on an unprecedented scale and resolution by re-sequencing thousands of strains systematically. In this article, we review challenges in the integration and analysis of large-scale re-sequencing data, present an extensive overview of bioinformatics methods for predicting the effects of genetic variants on protein function, and discuss approaches for interfacing existing bioinformatics approaches with genome-scale models of cellular processes in order to predict effects of sequence variation on cellular phenotypes.

  3. Noise analysis of genome-scale protein synthesis using a discrete computational model of translation.

    Science.gov (United States)

    Racle, Julien; Stefaniuk, Adam Jan; Hatzimanikatis, Vassily

    2015-07-28

    Noise in genetic networks has been the subject of extensive experimental and computational studies. However, very few of these studies have considered noise properties using mechanistic models that account for the discrete movement of ribosomes and RNA polymerases along their corresponding templates (messenger RNA (mRNA) and DNA). The large size of these systems, which scales with the number of genes, mRNA copies, codons per mRNA, and ribosomes, is responsible for some of the challenges. Additionally, one should be able to describe the dynamics of ribosome exchange between the free ribosome pool and those bound to mRNAs, as well as how mRNA species compete for ribosomes. We developed an efficient algorithm for stochastic simulations that addresses these issues and used it to study the contribution and trade-offs of noise to translation properties (rates, time delays, and rate-limiting steps). The algorithm scales linearly with the number of mRNA copies, which allowed us to study the importance of genome-scale competition between mRNAs for the same ribosomes. We determined that noise is minimized under conditions maximizing the specific synthesis rate. Moreover, sensitivity analysis of the stochastic system revealed the importance of the elongation rate in the resultant noise, whereas the translation initiation rate constant was more closely related to the average protein synthesis rate. We observed significant differences between our results and the noise properties of the most commonly used translation models. Overall, our studies demonstrate that the use of full mechanistic models is essential for the study of noise in translation and transcription.

  4. Noise analysis of genome-scale protein synthesis using a discrete computational model of translation

    Energy Technology Data Exchange (ETDEWEB)

    Racle, Julien; Hatzimanikatis, Vassily, E-mail: vassily.hatzimanikatis@epfl.ch [Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne (Switzerland); Swiss Institute of Bioinformatics (SIB), CH-1015 Lausanne (Switzerland); Stefaniuk, Adam Jan [Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne (Switzerland)

    2015-07-28

    Noise in genetic networks has been the subject of extensive experimental and computational studies. However, very few of these studies have considered noise properties using mechanistic models that account for the discrete movement of ribosomes and RNA polymerases along their corresponding templates (messenger RNA (mRNA) and DNA). The large size of these systems, which scales with the number of genes, mRNA copies, codons per mRNA, and ribosomes, is responsible for some of the challenges. Additionally, one should be able to describe the dynamics of ribosome exchange between the free ribosome pool and those bound to mRNAs, as well as how mRNA species compete for ribosomes. We developed an efficient algorithm for stochastic simulations that addresses these issues and used it to study the contribution and trade-offs of noise to translation properties (rates, time delays, and rate-limiting steps). The algorithm scales linearly with the number of mRNA copies, which allowed us to study the importance of genome-scale competition between mRNAs for the same ribosomes. We determined that noise is minimized under conditions maximizing the specific synthesis rate. Moreover, sensitivity analysis of the stochastic system revealed the importance of the elongation rate in the resultant noise, whereas the translation initiation rate constant was more closely related to the average protein synthesis rate. We observed significant differences between our results and the noise properties of the most commonly used translation models. Overall, our studies demonstrate that the use of full mechanistic models is essential for the study of noise in translation and transcription.

  5. A Genome-Scale Modeling Approach to Quantify Biofilm Component Growth of Salmonella Typhimurium.

    Science.gov (United States)

    Ribaudo, Nicholas; Li, Xianhua; Davis, Brett; Wood, Thomas K; Huang, Zuyi Jacky

    2017-01-01

    Salmonella typhimurium (S. typhimurium) is an extremely dangerous foodborne bacterium that infects both animal and human subjects, causing fatal diseases around the world. Salmonella's robust virulence, antibiotic-resistant nature, and capacity to survive under harsh conditions are largely due to its ability to form resilient biofilms. Multiple genome-scale metabolic models have been developed to study the complex and diverse nature of this organism's metabolism; however, none of these models fully integrated the reactions and mechanisms required to study the influence of biofilm formation. This work developed a systems-level approach to study the adjustment of intracellular metabolism of S. typhimurium during biofilm formation. The most advanced metabolic reconstruction currently available, STM_v1.0, was 1st extended to include the formation of the extracellular biofilm matrix. Flux balance analysis was then employed to study the influence of biofilm formation on cellular growth rate and the production rates of biofilm components. With biofilm formation present, biomass growth was examined under nutrient rich and nutrient deficient conditions, resulting in overall growth rates of 0.8675 and 0.6238 h(-1) respectively. Investigation of intracellular flux variation during biofilm formation resulted in the elucidation of 32 crucial reactions, and associated genes, whose fluxes most significantly adapt during the physiological response. Experimental data were found in the literature to validate the importance of these genes for the biofilm formation of S. typhimurium. This preliminary investigation on the adjustment of intracellular metabolism of S. typhimurium during biofilm formation will serve as a platform to generate hypotheses for further experimental study on the biofilm formation of this virulent bacterium.

  6. Genome-scale modeling using flux ratio constraints to enable metabolic engineering of clostridial metabolism in silico

    Directory of Open Access Journals (Sweden)

    McAnulty Michael J

    2012-05-01

    Full Text Available Abstract Background Genome-scale metabolic networks and flux models are an effective platform for linking an organism genotype to its phenotype. However, few modeling approaches offer predictive capabilities to evaluate potential metabolic engineering strategies in silico. Results A new method called “flux balance analysis with flux ratios (FBrAtio” was developed in this research and applied to a new genome-scale model of Clostridium acetobutylicum ATCC 824 (iCAC490 that contains 707 metabolites and 794 reactions. FBrAtio was used to model wild-type metabolism and metabolically engineered strains of C. acetobutylicum where only flux ratio constraints and thermodynamic reversibility of reactions were required. The FBrAtio approach allowed solutions to be found through standard linear programming. Five flux ratio constraints were required to achieve a qualitative picture of wild-type metabolism for C. acetobutylicum for the production of: (i acetate, (ii lactate, (iii butyrate, (iv acetone, (v butanol, (vi ethanol, (vii CO2 and (viii H2. Results of this simulation study coincide with published experimental results and show the knockdown of the acetoacetyl-CoA transferase increases butanol to acetone selectivity, while the simultaneous over-expression of the aldehyde/alcohol dehydrogenase greatly increases ethanol production. Conclusions FBrAtio is a promising new method for constraining genome-scale models using internal flux ratios. The method was effective for modeling wild-type and engineered strains of C. acetobutylicum.

  7. Genome-scale metabolic model for Lactococcus lactis MG1363 and its application to the analysis of flavor formation.

    Science.gov (United States)

    Flahaut, Nicolas A L; Wiersma, Anne; van de Bunt, Bert; Martens, Dirk E; Schaap, Peter J; Sijtsma, Lolke; Dos Santos, Vitor A Martins; de Vos, Willem M

    2013-10-01

    Lactococcus lactis subsp. cremoris MG1363 is a paradigm strain for lactococci used in industrial dairy fermentations. However, despite of its importance for process development, no genome-scale metabolic model has been reported thus far. Moreover, current models for other lactococci only focus on growth and sugar degradation. A metabolic model that includes nitrogen metabolism and flavor-forming pathways is instrumental for the understanding and designing new industrial applications of these lactic acid bacteria. A genome-scale, constraint-based model of the metabolism and transport in L. lactis MG1363, accounting for 518 genes, 754 reactions, and 650 metabolites, was developed and experimentally validated. Fifty-nine reactions are directly or indirectly involved in flavor formation. Flux Balance Analysis and Flux Variability Analysis were used to investigate flux distributions within the whole metabolic network. Anaerobic carbon-limited continuous cultures were used for estimating the energetic parameters. A thorough model-driven analysis showing a highly flexible nitrogen metabolism, e.g., branched-chain amino acid catabolism which coupled with the redox balance, is pivotal for the prediction of the formation of different flavor compounds. Furthermore, the model predicted the formation of volatile sulfur compounds as a result of the fermentation. These products were subsequently identified in the experimental fermentations carried out. Thus, the genome-scale metabolic model couples the carbon and nitrogen metabolism in L. lactis MG1363 with complete known catabolic pathways leading to flavor formation. The model provided valuable insights into the metabolic networks underlying flavor formation and has the potential to contribute to new developments in dairy industries and cheese-flavor research.

  8. Quantitative assessment of thermodynamic constraints on the solution space of genome-scale metabolic models.

    Science.gov (United States)

    Hamilton, Joshua J; Dwivedi, Vivek; Reed, Jennifer L

    2013-07-16

    Constraint-based methods provide powerful computational techniques to allow understanding and prediction of cellular behavior. These methods rely on physiochemical constraints to eliminate infeasible behaviors from the space of available behaviors. One such constraint is thermodynamic feasibility, the requirement that intracellular flux distributions obey the laws of thermodynamics. The past decade has seen several constraint-based methods that interpret this constraint in different ways, including those that are limited to small networks, rely on predefined reaction directions, and/or neglect the relationship between reaction free energies and metabolite concentrations. In this work, we utilize one such approach, thermodynamics-based metabolic flux analysis (TMFA), to make genome-scale, quantitative predictions about metabolite concentrations and reaction free energies in the absence of prior knowledge of reaction directions, while accounting for uncertainties in thermodynamic estimates. We applied TMFA to a genome-scale network reconstruction of Escherichia coli and examined the effect of thermodynamic constraints on the flux space. We also assessed the predictive performance of TMFA against gene essentiality and quantitative metabolomics data, under both aerobic and anaerobic, and optimal and suboptimal growth conditions. Based on these results, we propose that TMFA is a useful tool for validating phenotypes and generating hypotheses, and that additional types of data and constraints can improve predictions of metabolite concentrations.

  9. Direct coupling of a genome-scale microbial in silico model and a groundwater reactive transport model

    Science.gov (United States)

    Fang, Yilin; Scheibe, Timothy D.; Mahadevan, Radhakrishnan; Garg, Srinath; Long, Philip E.; Lovley, Derek R.

    2011-03-01

    The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint-based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species and multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The

  10. Using a Genome-Scale Metabolic Network Model to Elucidate the Mechanism of Chloroquine Action in Plasmodium falciparum

    Science.gov (United States)

    2017-03-22

    Parasitology: Drugs and Drug Resistance journal homepage: www.elsevier .com/locate/ i jpddrUsing a genome-scale metabolic network model to elucidate...the mechanism of chloroquine action in Plasmodium falciparum Shivendra G. Tewari a , *, Sean T. Prigge b, Jaques Reifman a , Anders Wallqvist a , * a ...authors. E-mail addresses: stewari@bhsai.org (S.G. (S.T. Prigge), jaques.reifman.civ@mail.mil (J. Reifma mil ( A . Wallqvist). http://dx.doi.org/10.1016

  11. Construction of a Genome-Scale Metabolic Model of Arthrospira platensis NIES-39 and Metabolic Design for Cyanobacterial Bioproduction.

    Science.gov (United States)

    Yoshikawa, Katsunori; Aikawa, Shimpei; Kojima, Yuta; Toya, Yoshihiro; Furusawa, Chikara; Kondo, Akihiko; Shimizu, Hiroshi

    2015-01-01

    Arthrospira (Spirulina) platensis is a promising feedstock and host strain for bioproduction because of its high accumulation of glycogen and superior characteristics for industrial production. Metabolic simulation using a genome-scale metabolic model and flux balance analysis is a powerful method that can be used to design metabolic engineering strategies for the improvement of target molecule production. In this study, we constructed a genome-scale metabolic model of A. platensis NIES-39 including 746 metabolic reactions and 673 metabolites, and developed novel strategies to improve the production of valuable metabolites, such as glycogen and ethanol. The simulation results obtained using the metabolic model showed high consistency with experimental results for growth rates under several trophic conditions and growth capabilities on various organic substrates. The metabolic model was further applied to design a metabolic network to improve the autotrophic production of glycogen and ethanol. Decreased flux of reactions related to the TCA cycle and phosphoenolpyruvate reaction were found to improve glycogen production. Furthermore, in silico knockout simulation indicated that deletion of genes related to the respiratory chain, such as NAD(P)H dehydrogenase and cytochrome-c oxidase, could enhance ethanol production by using ammonium as a nitrogen source.

  12. Construction of a Genome-Scale Metabolic Model of Arthrospira platensis NIES-39 and Metabolic Design for Cyanobacterial Bioproduction.

    Directory of Open Access Journals (Sweden)

    Katsunori Yoshikawa

    Full Text Available Arthrospira (Spirulina platensis is a promising feedstock and host strain for bioproduction because of its high accumulation of glycogen and superior characteristics for industrial production. Metabolic simulation using a genome-scale metabolic model and flux balance analysis is a powerful method that can be used to design metabolic engineering strategies for the improvement of target molecule production. In this study, we constructed a genome-scale metabolic model of A. platensis NIES-39 including 746 metabolic reactions and 673 metabolites, and developed novel strategies to improve the production of valuable metabolites, such as glycogen and ethanol. The simulation results obtained using the metabolic model showed high consistency with experimental results for growth rates under several trophic conditions and growth capabilities on various organic substrates. The metabolic model was further applied to design a metabolic network to improve the autotrophic production of glycogen and ethanol. Decreased flux of reactions related to the TCA cycle and phosphoenolpyruvate reaction were found to improve glycogen production. Furthermore, in silico knockout simulation indicated that deletion of genes related to the respiratory chain, such as NAD(PH dehydrogenase and cytochrome-c oxidase, could enhance ethanol production by using ammonium as a nitrogen source.

  13. The RAVEN toolbox and its use for generating a genome-scale metabolic model for Penicillium chrysogenum.

    Science.gov (United States)

    Agren, Rasmus; Liu, Liming; Shoaie, Saeed; Vongsangnak, Wanwipa; Nookaew, Intawat; Nielsen, Jens

    2013-01-01

    We present the RAVEN (Reconstruction, Analysis and Visualization of Metabolic Networks) Toolbox: a software suite that allows for semi-automated reconstruction of genome-scale models. It makes use of published models and/or the KEGG database, coupled with extensive gap-filling and quality control features. The software suite also contains methods for visualizing simulation results and omics data, as well as a range of methods for performing simulations and analyzing the results. The software is a useful tool for system-wide data analysis in a metabolic context and for streamlined reconstruction of metabolic networks based on protein homology. The RAVEN Toolbox workflow was applied in order to reconstruct a genome-scale metabolic model for the important microbial cell factory Penicillium chrysogenum Wisconsin54-1255. The model was validated in a bibliomic study of in total 440 references, and it comprises 1471 unique biochemical reactions and 1006 ORFs. It was then used to study the roles of ATP and NADPH in the biosynthesis of penicillin, and to identify potential metabolic engineering targets for maximization of penicillin production.

  14. The RAVEN toolbox and its use for generating a genome-scale metabolic model for Penicillium chrysogenum.

    Directory of Open Access Journals (Sweden)

    Rasmus Agren

    Full Text Available We present the RAVEN (Reconstruction, Analysis and Visualization of Metabolic Networks Toolbox: a software suite that allows for semi-automated reconstruction of genome-scale models. It makes use of published models and/or the KEGG database, coupled with extensive gap-filling and quality control features. The software suite also contains methods for visualizing simulation results and omics data, as well as a range of methods for performing simulations and analyzing the results. The software is a useful tool for system-wide data analysis in a metabolic context and for streamlined reconstruction of metabolic networks based on protein homology. The RAVEN Toolbox workflow was applied in order to reconstruct a genome-scale metabolic model for the important microbial cell factory Penicillium chrysogenum Wisconsin54-1255. The model was validated in a bibliomic study of in total 440 references, and it comprises 1471 unique biochemical reactions and 1006 ORFs. It was then used to study the roles of ATP and NADPH in the biosynthesis of penicillin, and to identify potential metabolic engineering targets for maximization of penicillin production.

  15. Integrated genome-scale analysis of the transcriptional regulatory landscape in a blood stem/progenitor cell model.

    Science.gov (United States)

    Wilson, Nicola K; Schoenfelder, Stefan; Hannah, Rebecca; Sánchez Castillo, Manuel; Schütte, Judith; Ladopoulos, Vasileios; Mitchelmore, Joanna; Goode, Debbie K; Calero-Nieto, Fernando J; Moignard, Victoria; Wilkinson, Adam C; Jimenez-Madrid, Isabel; Kinston, Sarah; Spivakov, Mikhail; Fraser, Peter; Göttgens, Berthold

    2016-03-31

    Comprehensive study of transcriptional control processes will be required to enhance our understanding of both normal and malignant hematopoiesis. Modern sequencing technologies have revolutionized our ability to generate genome-scale expression and histone modification profiles, transcription factor (TF)-binding maps, and also comprehensive chromatin-looping information. Many of these technologies, however, require large numbers of cells, and therefore cannot be applied to rare hematopoietic stem/progenitor cell (HSPC) populations. The stem cell factor-dependent multipotent progenitor cell line HPC-7 represents a well-recognized cell line model for HSPCs. Here we report genome-wide maps for 17 TFs, 3 histone modifications, DNase I hypersensitive sites, and high-resolution promoter-enhancer interactomes in HPC-7 cells. Integrated analysis of these complementary data sets revealed TF occupancy patterns of genomic regions involved in promoter-anchored loops. Moreover, preferential associations between pairs of TFs bound at either ends of chromatin loops led to the identification of 4 previously unrecognized protein-protein interactions between key blood stem cell regulators. All HPC-7 data sets are freely available both through standard repositories and a user-friendly Web interface. Together with previously generated genome-wide data sets, this study integrates HPC-7 data into a genomic resource on par with ENCODE tier 1 cell lines and, importantly, is the only current model with comprehensive genome-scale data that is relevant to HSPC biology. © 2016 by The American Society of Hematology.

  16. Further developments towards a genome-scale metabolic model of yeast

    Directory of Open Access Journals (Sweden)

    Dunn Warwick B

    2010-10-01

    Full Text Available Abstract Background To date, several genome-scale network reconstructions have been used to describe the metabolism of the yeast Saccharomyces cerevisiae, each differing in scope and content. The recent community-driven reconstruction, while rigorously evidenced and well annotated, under-represented metabolite transport, lipid metabolism and other pathways, and was not amenable to constraint-based analyses because of lack of pathway connectivity. Results We have expanded the yeast network reconstruction to incorporate many new reactions from the literature and represented these in a well-annotated and standards-compliant manner. The new reconstruction comprises 1102 unique metabolic reactions involving 924 unique metabolites - significantly larger in scope than any previous reconstruction. The representation of lipid metabolism in particular has improved, with 234 out of 268 enzymes linked to lipid metabolism now present in at least one reaction. Connectivity is emphatically improved, with more than 90% of metabolites now reachable from the growth medium constituents. The present updates allow constraint-based analyses to be performed; viability predictions of single knockouts are comparable to results from in vivo experiments and to those of previous reconstructions. Conclusions We report the development of the most complete reconstruction of yeast metabolism to date that is based upon reliable literature evidence and richly annotated according to MIRIAM standards. The reconstruction is available in the Systems Biology Markup Language (SBML and via a publicly accessible database http://www.comp-sys-bio.org/yeastnet/.

  17. IMGMD: A platform for the integration and standardisation of In silico Microbial Genome-scale Metabolic Models.

    Science.gov (United States)

    Ye, Chao; Xu, Nan; Dong, Chuan; Ye, Yuannong; Zou, Xuan; Chen, Xiulai; Guo, Fengbiao; Liu, Liming

    2017-04-07

    Genome-scale metabolic models (GSMMs) constitute a platform that combines genome sequences and detailed biochemical information to quantify microbial physiology at the system level. To improve the unity, integrity, correctness, and format of data in published GSMMs, a consensus IMGMD database was built in the LAMP (Linux + Apache + MySQL + PHP) system by integrating and standardizing 328 GSMMs constructed for 139 microorganisms. The IMGMD database can help microbial researchers download manually curated GSMMs, rapidly reconstruct standard GSMMs, design pathways, and identify metabolic targets for strategies on strain improvement. Moreover, the IMGMD database facilitates the integration of wet-lab and in silico data to gain an additional insight into microbial physiology. The IMGMD database is freely available, without any registration requirements, at http://imgmd.jiangnan.edu.cn/database.

  18. Understanding the Causes and Implications of Endothelial Metabolic Variation in Cardiovascular Disease through Genome-Scale Metabolic Modeling

    DEFF Research Database (Denmark)

    McGarrity, Sarah; Halldórsson, Haraldur; Palsson, Sirus

    2016-01-01

    of endothelial cell (EC) metabolism and its connections to cardiovascular disease (CVD) and explore the use of genome-scale metabolic models (GEMs) for integrating metabolic and genomic data. GEMs combine gene expression and metabolic data acting as frameworks for their analysis and, ultimately, afford...... mechanistic understanding of how genetic variation impacts metabolism. We demonstrate how GEMs can be used to investigate CVD-related genetic variation, drug resistance mechanisms, and novel metabolic pathways in ECs. The application of GEMs in personalized medicine is also highlighted. Particularly, we focus...... on the potential of GEMs to identify metabolic biomarkers of endothelial dysfunction and to discover methods of stratifying treatments for CVDs based on individual genetic markers. Recent advances in systems biology methodology, and how these methodologies can be applied to understand EC metabolism in both health...

  19. Comparative genome-scale modelling of Staphylococcus aureus strains identifies strain-specific metabolic capabilities linked to pathogenicity.

    Science.gov (United States)

    Bosi, Emanuele; Monk, Jonathan M; Aziz, Ramy K; Fondi, Marco; Nizet, Victor; Palsson, Bernhard Ø

    2016-06-28

    Staphylococcus aureus is a preeminent bacterial pathogen capable of colonizing diverse ecological niches within its human host. We describe here the pangenome of S. aureus based on analysis of genome sequences from 64 strains of S. aureus spanning a range of ecological niches, host types, and antibiotic resistance profiles. Based on this set, S. aureus is expected to have an open pangenome composed of 7,411 genes and a core genome composed of 1,441 genes. Metabolism was highly conserved in this core genome; however, differences were identified in amino acid and nucleotide biosynthesis pathways between the strains. Genome-scale models (GEMs) of metabolism were constructed for the 64 strains of S. aureus These GEMs enabled a systems approach to characterizing the core metabolic and panmetabolic capabilities of the S. aureus species. All models were predicted to be auxotrophic for the vitamins niacin (vitamin B3) and thiamin (vitamin B1), whereas strain-specific auxotrophies were predicted for riboflavin (vitamin B2), guanosine, leucine, methionine, and cysteine, among others. GEMs were used to systematically analyze growth capabilities in more than 300 different growth-supporting environments. The results identified metabolic capabilities linked to pathogenic traits and virulence acquisitions. Such traits can be used to differentiate strains responsible for mild vs. severe infections and preference for hosts (e.g., animals vs. humans). Genome-scale analysis of multiple strains of a species can thus be used to identify metabolic determinants of virulence and increase our understanding of why certain strains of this deadly pathogen have spread rapidly throughout the world.

  20. Comparative genome-scale modelling of Staphylococcus aureus strains identifies strain-specific metabolic capabilities linked to pathogenicity

    Science.gov (United States)

    Bosi, Emanuele; Monk, Jonathan M.; Aziz, Ramy K.; Fondi, Marco; Nizet, Victor; Palsson, Bernhard Ø.

    2016-01-01

    Staphylococcus aureus is a preeminent bacterial pathogen capable of colonizing diverse ecological niches within its human host. We describe here the pangenome of S. aureus based on analysis of genome sequences from 64 strains of S. aureus spanning a range of ecological niches, host types, and antibiotic resistance profiles. Based on this set, S. aureus is expected to have an open pangenome composed of 7,411 genes and a core genome composed of 1,441 genes. Metabolism was highly conserved in this core genome; however, differences were identified in amino acid and nucleotide biosynthesis pathways between the strains. Genome-scale models (GEMs) of metabolism were constructed for the 64 strains of S. aureus. These GEMs enabled a systems approach to characterizing the core metabolic and panmetabolic capabilities of the S. aureus species. All models were predicted to be auxotrophic for the vitamins niacin (vitamin B3) and thiamin (vitamin B1), whereas strain-specific auxotrophies were predicted for riboflavin (vitamin B2), guanosine, leucine, methionine, and cysteine, among others. GEMs were used to systematically analyze growth capabilities in more than 300 different growth-supporting environments. The results identified metabolic capabilities linked to pathogenic traits and virulence acquisitions. Such traits can be used to differentiate strains responsible for mild vs. severe infections and preference for hosts (e.g., animals vs. humans). Genome-scale analysis of multiple strains of a species can thus be used to identify metabolic determinants of virulence and increase our understanding of why certain strains of this deadly pathogen have spread rapidly throughout the world. PMID:27286824

  1. Designing intracellular metabolism for production of target compounds by introducing a heterologous metabolic reaction based on a Synechosystis sp. 6803 genome-scale model.

    Science.gov (United States)

    Shirai, Tomokazu; Osanai, Takashi; Kondo, Akihiko

    2016-01-18

    Designing optimal intracellular metabolism is essential for using microorganisms to produce useful compounds. Computerized calculations for flux balance analysis utilizing a genome-scale model have been performed for such designs. Many genome-scale models have been developed for different microorganisms. However, optimal designs of intracellular metabolism aimed at producing a useful compound often utilize metabolic reactions of only the host microbial cells. In the present study, we added reactions other than the metabolic reactions with Synechosystis sp. 6803 as a host to its genome-scale model, and constructed a metabolic model of hybrid cells (SyHyMeP) using computerized analysis. Using this model provided a metabolic design that improves the theoretical yield of succinic acid, which is a useful compound. Constructing the SyHyMeP model enabled new metabolic designs for producing useful compounds. In the present study, we developed a metabolic design that allowed for improved theoretical yield in the production of succinic acid during glycogen metabolism by Synechosystis sp. 6803. The theoretical yield of succinic acid production using a genome-scale model of these cells was 1.00 mol/mol-glucose, but use of the SyHyMeP model enabled a metabolic design with which a 33 % increase in theoretical yield is expected due to the introduction of isocitrate lyase, adding activations of endogenous tree reactions via D-glycerate in Synechosystis sp. 6803. The SyHyMeP model developed in this study has provided a new metabolic design that is not restricted only to the metabolic reactions of individual microbial cells. The concept of construction of this model requires only replacement of the genome-scale model of the host microbial cells and can thus be applied to various useful microorganisms for metabolic design to produce compounds.

  2. In silico method for modelling metabolism and gene product expression at genome scale

    Energy Technology Data Exchange (ETDEWEB)

    Lerman, Joshua A.; Hyduke, Daniel R.; Latif, Haythem; Portnoy, Vasiliy A.; Lewis, Nathan E.; Orth, Jeffrey D.; Rutledge, Alexandra C.; Smith, Richard D.; Adkins, Joshua N.; Zengler, Karsten; Palsson, Bernard O.

    2012-07-03

    Transcription and translation use raw materials and energy generated metabolically to create the macromolecular machinery responsible for all cellular functions, including metabolism. A biochemically accurate model of molecular biology and metabolism will facilitate comprehensive and quantitative computations of an organism's molecular constitution as a function of genetic and environmental parameters. Here we formulate a model of metabolism and macromolecular expression. Prototyping it using the simple microorganism Thermotoga maritima, we show our model accurately simulates variations in cellular composition and gene expression. Moreover, through in silico comparative transcriptomics, the model allows the discovery of new regulons and improving the genome and transcription unit annotations. Our method presents a framework for investigating molecular biology and cellular physiology in silico and may allow quantitative interpretation of multi-omics data sets in the context of an integrated biochemical description of an organism.

  3. MetaboTools: A comprehensive toolbox for analysis of genome-scale metabolic models

    OpenAIRE

    2016-01-01

    Metabolomic data sets provide a direct read-out of cellular phenotypes and are increasingly generated to study biological questions. Previous work, by us and others, revealed the potential of analyzing extracellular metabolomic data in the context of the metabolic model using constraint-based modeling. With the MetaboTools, we make our methods available to the broader scientific community. The MetaboTools consist of a protocol, a toolbox, and tutorials of two use cases. The protocol describes...

  4. MetaboTools: A comprehensive toolbox for analysis of genome-scale metabolic models

    Directory of Open Access Journals (Sweden)

    Maike Kathrin Aurich

    2016-08-01

    Full Text Available Metabolomic data sets provide a direct read-out of cellular phenotypes and are increasingly generated to study biological questions. Previous work, by us and others, revealed the potential of analyzing extracellular metabolomic data in the context of the metabolic model using constraint-based modeling. With the MetaboTools , we make our methods available to the broader scientific community. The MetaboTools consist of a protocol, a toolbox, and tutorials of two use cases. The protocol describes, in a step-wise manner, the workflow of data integration and computational analysis. The MetaboTools comprise the Matlab code required to complete the workflow described in the protocol. Tutorials explain the computational steps for integration of two different data sets and demonstrate a comprehensive set of methods for the computational analysis of metabolic models and stratification thereof into different phenotypes. The presented workflow supports integrative analysis of multiple omics data sets. Importantly, all analysis tools can be applied to metabolic models without performing the entire workflow. Taken together, the MetaboTools constitute a comprehensive guide to the intra-model analysis of extracellular metabolomic data from microbial, plant, or human cells. This computational modeling resource offers a broad set of computational analysis tools for a wide biomedical and non-biomedical research community.

  5. MetaboTools: A Comprehensive Toolbox for Analysis of Genome-Scale Metabolic Models.

    Science.gov (United States)

    Aurich, Maike K; Fleming, Ronan M T; Thiele, Ines

    2016-01-01

    Metabolomic data sets provide a direct read-out of cellular phenotypes and are increasingly generated to study biological questions. Previous work, by us and others, revealed the potential of analyzing extracellular metabolomic data in the context of the metabolic model using constraint-based modeling. With the MetaboTools, we make our methods available to the broader scientific community. The MetaboTools consist of a protocol, a toolbox, and tutorials of two use cases. The protocol describes, in a step-wise manner, the workflow of data integration, and computational analysis. The MetaboTools comprise the Matlab code required to complete the workflow described in the protocol. Tutorials explain the computational steps for integration of two different data sets and demonstrate a comprehensive set of methods for the computational analysis of metabolic models and stratification thereof into different phenotypes. The presented workflow supports integrative analysis of multiple omics data sets. Importantly, all analysis tools can be applied to metabolic models without performing the entire workflow. Taken together, the MetaboTools constitute a comprehensive guide to the intra-model analysis of extracellular metabolomic data from microbial, plant, or human cells. This computational modeling resource offers a broad set of computational analysis tools for a wide biomedical and non-biomedical research community.

  6. Integration of genome-scale modeling and transcript profiling reveals metabolic pathways underlying light and temperature acclimation in Arabidopsis.

    Science.gov (United States)

    Töpfer, Nadine; Caldana, Camila; Grimbs, Sergio; Willmitzer, Lothar; Fernie, Alisdair R; Nikoloski, Zoran

    2013-04-01

    Understanding metabolic acclimation of plants to challenging environmental conditions is essential for dissecting the role of metabolic pathways in growth and survival. As stresses involve simultaneous physiological alterations across all levels of cellular organization, a comprehensive characterization of the role of metabolic pathways in acclimation necessitates integration of genome-scale models with high-throughput data. Here, we present an integrative optimization-based approach, which, by coupling a plant metabolic network model and transcriptomics data, can predict the metabolic pathways affected in a single, carefully controlled experiment. Moreover, we propose three optimization-based indices that characterize different aspects of metabolic pathway behavior in the context of the entire metabolic network. We demonstrate that the proposed approach and indices facilitate quantitative comparisons and characterization of the plant metabolic response under eight different light and/or temperature conditions. The predictions of the metabolic functions involved in metabolic acclimation of Arabidopsis thaliana to the changing conditions are in line with experimental evidence and result in a hypothesis about the role of homocysteine-to-Cys interconversion and Asn biosynthesis. The approach can also be used to reveal the role of particular metabolic pathways in other scenarios, while taking into consideration the entirety of characterized plant metabolism.

  7. Data-driven integration of genome-scale regulatory and metabolic network models

    Directory of Open Access Journals (Sweden)

    Saheed eImam

    2015-05-01

    Full Text Available Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription and signaling have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert – a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system.

  8. Dissecting the energy metabolism in Mycoplasma pneumoniae through genome-scale metabolic modeling

    NARCIS (Netherlands)

    Wodke, J.A.; Puchalka, J.; Lluch-Senar, M.; Marcos, J.; Yus, E.; Godinho, M.; Gutierrez-Gallego, R.; Martins Dos Santos, V.A.P.; Serrano, L.; Klipp, E.; Maier, T.

    2013-01-01

    Mycoplasma pneumoniae, a threatening pathogen with a minimal genome, is a model organism for bacterial systems biology for which substantial experimental information is available. With the goal of understanding the complex interactions underlying its metabolism, we analyzed and characterized the met

  9. Incorporating Protein Biosynthesis into the Saccharomyces cerevisiae Genome-scale Metabolic Model

    DEFF Research Database (Denmark)

    Olivares Hernandez, Roberto

    by a rapidly growing cell. To extend the model including protein synthesis, from the survey of the available literature was possible to identify a few enzymatic reactions and gene functions in the early steps of gene expression for proteins: mRNA transcription, mRNA processing, mRNA export out of the nucleus...

  10. Flux balance analysis of genome-scale metabolic model of rice (Oryza sativa): Aiming to increase biomass

    Indian Academy of Sciences (India)

    Rahul Shaw; Sudip Kundu

    2015-10-01

    Due to socio-economic reasons, it is essential to design efficient stress-tolerant, more nutritious, high yielding rice varieties. A systematic understanding of the rice cellular metabolism is essential for this purpose. Here, we analyse a genome-scale metabolic model of rice leaf using Flux Balance Analysis to investigate whether it has potential metabolic flexibility to increase the biosynthesis of any of the biomass components. We initially simulate the metabolic responses under an objective to maximize the biomass components. Using the estimated maximum value of biomass synthesis as a constraint, we further simulate the metabolic responses optimizing the cellular economy. Depending on the physiological conditions of a cell, the transport capacities of intracellular transporters (ICTs) can vary. To mimic this physiological state, we randomly vary the ICTs’ transport capacities and investigate their effects. The results show that the rice leaf has the potential to increase glycine and starch in a wide range depending on the ICTs’ transport capacities. The predicted biosynthesis pathways vary slightly at the two different optimization conditions. With the constraint of biomass composition, the cell also has the metabolic plasticity to fix a wide range of carbon-nitrogen ratio.

  11. Reconstruction and analysis of genome-scale metabolic model of a photosynthetic bacterium

    Directory of Open Access Journals (Sweden)

    Urchueguía Javier F

    2010-11-01

    Full Text Available Abstract Background Synechocystis sp. PCC6803 is a cyanobacterium considered as a candidate photo-biological production platform - an attractive cell factory capable of using CO2 and light as carbon and energy source, respectively. In order to enable efficient use of metabolic potential of Synechocystis sp. PCC6803, it is of importance to develop tools for uncovering stoichiometric and regulatory principles in the Synechocystis metabolic network. Results We report the most comprehensive metabolic model of Synechocystis sp. PCC6803 available, iSyn669, which includes 882 reactions, associated with 669 genes, and 790 metabolites. The model includes a detailed biomass equation which encompasses elementary building blocks that are needed for cell growth, as well as a detailed stoichiometric representation of photosynthesis. We demonstrate applicability of iSyn669 for stoichiometric analysis by simulating three physiologically relevant growth conditions of Synechocystis sp. PCC6803, and through in silico metabolic engineering simulations that allowed identification of a set of gene knock-out candidates towards enhanced succinate production. Gene essentiality and hydrogen production potential have also been assessed. Furthermore, iSyn669 was used as a transcriptomic data integration scaffold and thereby we found metabolic hot-spots around which gene regulation is dominant during light-shifting growth regimes. Conclusions iSyn669 provides a platform for facilitating the development of cyanobacteria as microbial cell factories.

  12. Using a genome-scale metabolic network model to elucidate the mechanism of chloroquine action in Plasmodium falciparum

    Directory of Open Access Journals (Sweden)

    Shivendra G. Tewari

    2017-08-01

    Full Text Available Chloroquine, long the default first-line treatment against malaria, is now abandoned in large parts of the world because of widespread drug-resistance in Plasmodium falciparum. In spite of its importance as a cost-effective and efficient drug, a coherent understanding of the cellular mechanisms affected by chloroquine and how they influence the fitness and survival of the parasite remains elusive. Here, we used a systems biology approach to integrate genome-scale transcriptomics to map out the effects of chloroquine, identify targeted metabolic pathways, and translate these findings into mechanistic insights. Specifically, we first developed a method that integrates transcriptomic and metabolomic data, which we independently validated against a recently published set of such data for Krebs-cycle mutants of P. falciparum. We then used the method to calculate the effect of chloroquine treatment on the metabolic flux profiles of P. falciparum during the intraerythrocytic developmental cycle. The model predicted dose-dependent inhibition of DNA replication, in agreement with earlier experimental results for both drug-sensitive and drug-resistant P. falciparum strains. Our simulations also corroborated experimental findings that suggest differences in chloroquine sensitivity between ring- and schizont-stage P. falciparum. Our analysis also suggests that metabolic fluxes that govern reduced thioredoxin and phosphoenolpyruvate synthesis are significantly decreased and are pivotal to chloroquine-based inhibition of P. falciparum DNA replication. The consequences of impaired phosphoenolpyruvate synthesis and redox metabolism are reduced carbon fixation and increased oxidative stress, respectively, both of which eventually facilitate killing of the parasite. Our analysis suggests that a combination of chloroquine (or an analogue and another drug, which inhibits carbon fixation and/or increases oxidative stress, should increase the clearance of P

  13. Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism

    Science.gov (United States)

    2016-03-15

    one antimicrobial or have human homologs (see Materials and Methods). This resulted in a set of 56 putative target reactions against P. aer- uginosa...diphosphate; amp, adenylate. See S1 Supporting Information for the definition of the remaining of the abbreviations. doi:10.1371/journal.pcbi.1004452.g001...reducing or biofilm-increasing reactions, respectively). Then, for the inhibition of each reaction not used in the definition of any one of the metabo

  14. Acorn: A grid computing system for constraint based modeling and visualization of the genome scale metabolic reaction networks via a web interface

    Directory of Open Access Journals (Sweden)

    Bushell Michael E

    2011-05-01

    Full Text Available Abstract Background Constraint-based approaches facilitate the prediction of cellular metabolic capabilities, based, in turn on predictions of the repertoire of enzymes encoded in the genome. Recently, genome annotations have been used to reconstruct genome scale metabolic reaction networks for numerous species, including Homo sapiens, which allow simulations that provide valuable insights into topics, including predictions of gene essentiality of pathogens, interpretation of genetic polymorphism in metabolic disease syndromes and suggestions for novel approaches to microbial metabolic engineering. These constraint-based simulations are being integrated with the functional genomics portals, an activity that requires efficient implementation of the constraint-based simulations in the web-based environment. Results Here, we present Acorn, an open source (GNU GPL grid computing system for constraint-based simulations of genome scale metabolic reaction networks within an interactive web environment. The grid-based architecture allows efficient execution of computationally intensive, iterative protocols such as Flux Variability Analysis, which can be readily scaled up as the numbers of models (and users increase. The web interface uses AJAX, which facilitates efficient model browsing and other search functions, and intuitive implementation of appropriate simulation conditions. Research groups can install Acorn locally and create user accounts. Users can also import models in the familiar SBML format and link reaction formulas to major functional genomics portals of choice. Selected models and simulation results can be shared between different users and made publically available. Users can construct pathway map layouts and import them into the server using a desktop editor integrated within the system. Pathway maps are then used to visualise numerical results within the web environment. To illustrate these features we have deployed Acorn and created a

  15. Genome-scale modeling of light-driven reductant partitioning and carbon fluxes in diazotrophic unicellular cyanobacterium Cyanothece sp. ATCC 51142.

    Directory of Open Access Journals (Sweden)

    Trang T Vu

    Full Text Available Genome-scale metabolic models have proven useful for answering fundamental questions about metabolic capabilities of a variety of microorganisms, as well as informing their metabolic engineering. However, only a few models are available for oxygenic photosynthetic microorganisms, particularly in cyanobacteria in which photosynthetic and respiratory electron transport chains (ETC share components. We addressed the complexity of cyanobacterial ETC by developing a genome-scale model for the diazotrophic cyanobacterium, Cyanothece sp. ATCC 51142. The resulting metabolic reconstruction, iCce806, consists of 806 genes associated with 667 metabolic reactions and includes a detailed representation of the ETC and a biomass equation based on experimental measurements. Both computational and experimental approaches were used to investigate light-driven metabolism in Cyanothece sp. ATCC 51142, with a particular focus on reductant production and partitioning within the ETC. The simulation results suggest that growth and metabolic flux distributions are substantially impacted by the relative amounts of light going into the individual photosystems. When growth is limited by the flux through photosystem I, terminal respiratory oxidases are predicted to be an important mechanism for removing excess reductant. Similarly, under photosystem II flux limitation, excess electron carriers must be removed via cyclic electron transport. Furthermore, in silico calculations were in good quantitative agreement with the measured growth rates whereas predictions of reaction usage were qualitatively consistent with protein and mRNA expression data, which we used to further improve the resolution of intracellular flux values.

  16. Genome-scale modeling of light-driven reductant partitioning and carbon fluxes in diazotrophic unicellular cyanobacterium Cyanothece sp. ATCC 51142.

    Science.gov (United States)

    Vu, Trang T; Stolyar, Sergey M; Pinchuk, Grigoriy E; Hill, Eric A; Kucek, Leo A; Brown, Roslyn N; Lipton, Mary S; Osterman, Andrei; Fredrickson, Jim K; Konopka, Allan E; Beliaev, Alexander S; Reed, Jennifer L

    2012-01-01

    Genome-scale metabolic models have proven useful for answering fundamental questions about metabolic capabilities of a variety of microorganisms, as well as informing their metabolic engineering. However, only a few models are available for oxygenic photosynthetic microorganisms, particularly in cyanobacteria in which photosynthetic and respiratory electron transport chains (ETC) share components. We addressed the complexity of cyanobacterial ETC by developing a genome-scale model for the diazotrophic cyanobacterium, Cyanothece sp. ATCC 51142. The resulting metabolic reconstruction, iCce806, consists of 806 genes associated with 667 metabolic reactions and includes a detailed representation of the ETC and a biomass equation based on experimental measurements. Both computational and experimental approaches were used to investigate light-driven metabolism in Cyanothece sp. ATCC 51142, with a particular focus on reductant production and partitioning within the ETC. The simulation results suggest that growth and metabolic flux distributions are substantially impacted by the relative amounts of light going into the individual photosystems. When growth is limited by the flux through photosystem I, terminal respiratory oxidases are predicted to be an important mechanism for removing excess reductant. Similarly, under photosystem II flux limitation, excess electron carriers must be removed via cyclic electron transport. Furthermore, in silico calculations were in good quantitative agreement with the measured growth rates whereas predictions of reaction usage were qualitatively consistent with protein and mRNA expression data, which we used to further improve the resolution of intracellular flux values.

  17. Evaluation of a genome-scale in silico metabolic model for Geobacter metallireducens by using proteomic data from a field biostimulation experiment.

    Science.gov (United States)

    Fang, Yilin; Wilkins, Michael J; Yabusaki, Steven B; Lipton, Mary S; Long, Philip E

    2012-12-01

    Accurately predicting the interactions between microbial metabolism and the physical subsurface environment is necessary to enhance subsurface energy development, soil and groundwater cleanup, and carbon management. This study was an initial attempt to confirm the metabolic functional roles within an in silico model using environmental proteomic data collected during field experiments. Shotgun global proteomics data collected during a subsurface biostimulation experiment were used to validate a genome-scale metabolic model of Geobacter metallireducens-specifically, the ability of the metabolic model to predict metal reduction, biomass yield, and growth rate under dynamic field conditions. The constraint-based in silico model of G. metallireducens relates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes. Proteomic analysis showed that 180 of the 637 G. metallireducens proteins detected during the 2008 experiment were associated with specific metabolic reactions in the in silico model. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through the in silico model reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low abundances of proteins associated with amino acid transport and metabolism, revealed pathways or flux constraints in the in silico model that could be updated to more accurately predict metabolic processes that occur in the subsurface environment.

  18. Oxidative desulfurization: kinetic modelling.

    Science.gov (United States)

    Dhir, S; Uppaluri, R; Purkait, M K

    2009-01-30

    Increasing environmental legislations coupled with enhanced production of petroleum products demand, the deployment of novel technologies to remove organic sulfur efficiently. This work represents the kinetic modeling of ODS using H(2)O(2) over tungsten-containing layered double hydroxide (LDH) using the experimental data provided by Hulea et al. [V. Hulea, A.L. Maciuca, F. Fajula, E. Dumitriu, Catalytic oxidation of thiophenes and thioethers with hydrogen peroxide in the presence of W-containing layered double hydroxides, Appl. Catal. A: Gen. 313 (2) (2006) 200-207]. The kinetic modeling approach in this work initially targets the scope of the generation of a superstructure of micro-kinetic reaction schemes and models assuming Langmuir-Hinshelwood (LH) and Eley-Rideal (ER) mechanisms. Subsequently, the screening and selection of above models is initially based on profile-based elimination of incompetent schemes followed by non-linear regression search performed using the Levenberg-Marquardt algorithm (LMA) for the chosen models. The above analysis inferred that Eley-Rideal mechanism describes the kinetic behavior of ODS process using tungsten-containing LDH, with adsorption of reactant and intermediate product only taking place on the catalyst surface. Finally, an economic index is presented that scopes the economic aspects of the novel catalytic technology with the parameters obtained during regression analysis to conclude that the cost factor for the catalyst is 0.0062-0.04759 US $ per barrel.

  19. Modeling the Differences in Biochemical Capabilities of Pseudomonas Species by Flux Balance Analysis: How Good Are Genome-Scale Metabolic Networks at Predicting the Differences?

    Directory of Open Access Journals (Sweden)

    Parizad Babaei

    2014-01-01

    Full Text Available To date, several genome-scale metabolic networks have been reconstructed. These models cover a wide range of organisms, from bacteria to human. Such models have provided us with a framework for systematic analysis of metabolism. However, little effort has been put towards comparing biochemical capabilities of closely related species using their metabolic models. The accuracy of a model is highly dependent on the reconstruction process, as some errors may be included in the model during reconstruction. In this study, we investigated the ability of three Pseudomonas metabolic models to predict the biochemical differences, namely, iMO1086, iJP962, and iSB1139, which are related to P. aeruginosa PAO1, P. putida KT2440, and P. fluorescens SBW25, respectively. We did a comprehensive literature search for previous works containing biochemically distinguishable traits over these species. Amongst more than 1700 articles, we chose a subset of them which included experimental results suitable for in silico simulation. By simulating the conditions provided in the actual biological experiment, we performed case-dependent tests to compare the in silico results to the biological ones. We found out that iMO1086 and iJP962 were able to predict the experimental data and were much more accurate than iSB1139.

  20. Construction of robust dynamic genome-scale metabolic model structures of Saccharomyces cerevisiae through iterative re-parameterization.

    Science.gov (United States)

    Sánchez, Benjamín J; Pérez-Correa, José R; Agosin, Eduardo

    2014-09-01

    Dynamic flux balance analysis (dFBA) has been widely employed in metabolic engineering to predict the effect of genetic modifications and environmental conditions in the cell׳s metabolism during dynamic cultures. However, the importance of the model parameters used in these methodologies has not been properly addressed. Here, we present a novel and simple procedure to identify dFBA parameters that are relevant for model calibration. The procedure uses metaheuristic optimization and pre/post-regression diagnostics, fixing iteratively the model parameters that do not have a significant role. We evaluated this protocol in a Saccharomyces cerevisiae dFBA framework calibrated for aerobic fed-batch and anaerobic batch cultivations. The model structures achieved have only significant, sensitive and uncorrelated parameters and are able to calibrate different experimental data. We show that consumption, suboptimal growth and production rates are more useful for calibrating dynamic S. cerevisiae metabolic models than Boolean gene expression rules, biomass requirements and ATP maintenance.

  1. Integration and Validation of the Genome-Scale Metabolic Models of Pichia pastoris: A Comprehensive Update of Protein Glycosylation Pathways, Lipid and Energy Metabolism.

    Science.gov (United States)

    Tomàs-Gamisans, Màrius; Ferrer, Pau; Albiol, Joan

    2016-01-01

    Genome-scale metabolic models (GEMs) are tools that allow predicting a phenotype from a genotype under certain environmental conditions. GEMs have been developed in the last ten years for a broad range of organisms, and are used for multiple purposes such as discovering new properties of metabolic networks, predicting new targets for metabolic engineering, as well as optimizing the cultivation conditions for biochemicals or recombinant protein production. Pichia pastoris is one of the most widely used organisms for heterologous protein expression. There are different GEMs for this methylotrophic yeast of which the most relevant and complete in the published literature are iPP668, PpaMBEL1254 and iLC915. However, these three models differ regarding certain pathways, terminology for metabolites and reactions and annotations. Moreover, GEMs for some species are typically built based on the reconstructed models of related model organisms. In these cases, some organism-specific pathways could be missing or misrepresented. In order to provide an updated and more comprehensive GEM for P. pastoris, we have reconstructed and validated a consensus model integrating and merging all three existing models. In this step a comprehensive review and integration of the metabolic pathways included in each one of these three versions was performed. In addition, the resulting iMT1026 model includes a new description of some metabolic processes. Particularly new information described in recently published literature is included, mainly related to fatty acid and sphingolipid metabolism, glycosylation and cell energetics. Finally the reconstructed model was tested and validated, by comparing the results of the simulations with available empirical physiological datasets results obtained from a wide range of experimental conditions, such as different carbon sources, distinct oxygen availability conditions, as well as producing of two different recombinant proteins. In these simulations, the

  2. Integration and Validation of the Genome-Scale Metabolic Models of Pichia pastoris: A Comprehensive Update of Protein Glycosylation Pathways, Lipid and Energy Metabolism.

    Directory of Open Access Journals (Sweden)

    Màrius Tomàs-Gamisans

    Full Text Available Genome-scale metabolic models (GEMs are tools that allow predicting a phenotype from a genotype under certain environmental conditions. GEMs have been developed in the last ten years for a broad range of organisms, and are used for multiple purposes such as discovering new properties of metabolic networks, predicting new targets for metabolic engineering, as well as optimizing the cultivation conditions for biochemicals or recombinant protein production. Pichia pastoris is one of the most widely used organisms for heterologous protein expression. There are different GEMs for this methylotrophic yeast of which the most relevant and complete in the published literature are iPP668, PpaMBEL1254 and iLC915. However, these three models differ regarding certain pathways, terminology for metabolites and reactions and annotations. Moreover, GEMs for some species are typically built based on the reconstructed models of related model organisms. In these cases, some organism-specific pathways could be missing or misrepresented.In order to provide an updated and more comprehensive GEM for P. pastoris, we have reconstructed and validated a consensus model integrating and merging all three existing models. In this step a comprehensive review and integration of the metabolic pathways included in each one of these three versions was performed. In addition, the resulting iMT1026 model includes a new description of some metabolic processes. Particularly new information described in recently published literature is included, mainly related to fatty acid and sphingolipid metabolism, glycosylation and cell energetics. Finally the reconstructed model was tested and validated, by comparing the results of the simulations with available empirical physiological datasets results obtained from a wide range of experimental conditions, such as different carbon sources, distinct oxygen availability conditions, as well as producing of two different recombinant proteins. In

  3. A Comprehensively Curated Genome-Scale Two-Cell Model for the Heterocystous Cyanobacterium Anabaena sp. PCC 7120.

    Science.gov (United States)

    Malatinszky, David; Steuer, Ralf; Jones, Patrik R

    2017-01-01

    Anabaena sp. PCC 7120 is a nitrogen-fixing filamentous cyanobacterium. Under nitrogen-limiting conditions, a fraction of the vegetative cells in each filament terminally differentiate to nongrowing heterocysts. Heterocysts are metabolically and structurally specialized to enable O2-sensitive nitrogen fixation. The functionality of the filament, as an association of vegetative cells and heterocysts, is postulated to depend on metabolic exchange of electrons, carbon, and fixed nitrogen. In this study, we compile and evaluate a comprehensive curated stoichiometric model of this two-cell system, with the objective function based on the growth of the filament under diazotrophic conditions. The predicted growth rate under nitrogen-replete and -deplete conditions, as well as the effect of external carbon and nitrogen sources, was thereafter verified. Furthermore, the model was utilized to comprehensively evaluate the optimality of putative metabolic exchange reactions between heterocysts and vegetative cells. The model suggested that optimal growth requires at least four exchange metabolites. Several combinations of exchange metabolites resulted in predicted growth rates that are higher than growth rates achieved by only considering exchange of metabolites previously suggested in the literature. The curated model of the metabolic network of Anabaena sp. PCC 7120 enhances our ability to understand the metabolic organization of multicellular cyanobacteria and provides a platform for further study and engineering of their metabolism.

  4. Chemical kinetics modeling

    Energy Technology Data Exchange (ETDEWEB)

    Westbrook, C.K.; Pitz, W.J. [Lawrence Livermore National Laboratory, CA (United States)

    1993-12-01

    This project emphasizes numerical modeling of chemical kinetics of combustion, including applications in both practical combustion systems and in controlled laboratory experiments. Elementary reaction rate parameters are combined into mechanisms which then describe the overall reaction of the fuels being studied. Detailed sensitivity analyses are used to identify those reaction rates and product species distributions to which the results are most sensitive and therefore warrant the greatest attention from other experimental and theoretical research programs. Experimental data from a variety of environments are combined together to validate the reaction mechanisms, including results from laminar flames, shock tubes, flow systems, detonations, and even internal combustion engines.

  5. Using proteomic data to assess a genome-scale "in silico" model of metal reducing bacteria in the simulation of field-scale uranium bioremediation

    Science.gov (United States)

    Yabusaki, S.; Fang, Y.; Wilkins, M. J.; Long, P.; Rifle IFRC Science Team

    2011-12-01

    A series of field experiments in a shallow alluvial aquifer at a former uranium mill tailings site have demonstrated that indigenous bacteria can be stimulated with acetate to catalyze the conversion of hexavalent uranium in a groundwater plume to immobile solid-associated uranium in the +4 oxidation state. While this bioreduction of uranium has been shown to lower groundwater concentrations below actionable standards, a viable remediation methodology will need a mechanistic, predictive and quantitative understanding of the microbially-mediated reactions that catalyze the reduction of uranium in the context of site-specific processes, properties, and conditions. At the Rifle IFRC site, we are investigating the impacts on uranium behavior of pulsed acetate amendment, acetate-oxidizing iron and sulfate reducing bacteria, seasonal water table variation, spatially-variable physical (hydraulic conductivity, porosity) and geochemical (reactive surface area) material properties. The simulation of three-dimensional, variably saturated flow and biogeochemical reactive transport during a uranium bioremediation field experiment includes a genome-scale in silico model of Geobacter sp. to represent the Fe(III) terminal electron accepting process (TEAP). The Geobacter in silico model of cell-scale physiological metabolic pathways is comprised of hundreds of intra-cellular and environmental exchange reactions. One advantage of this approach is that the TEAP reaction stoichiometry and rate are now functions of the metabolic status of the microorganism. The linkage of in silico model reactions to specific Geobacter proteins has enabled the use of groundwater proteomic analyses to assess the accuracy of the model under evolving hydrologic and biogeochemical conditions. In this case, the largest predicted fluxes through in silico model reactions generally correspond to high abundances of proteins linked to those reactions (e.g. the condensation reaction catalyzed by the protein

  6. The OME Framework for genome-scale systems biology

    Energy Technology Data Exchange (ETDEWEB)

    Palsson, Bernhard O. [Univ. of California, San Diego, CA (United States); Ebrahim, Ali [Univ. of California, San Diego, CA (United States); Federowicz, Steve [Univ. of California, San Diego, CA (United States)

    2014-12-19

    The life sciences are undergoing continuous and accelerating integration with computational and engineering sciences. The biology that many in the field have been trained on may be hardly recognizable in ten to twenty years. One of the major drivers for this transformation is the blistering pace of advancements in DNA sequencing and synthesis. These advances have resulted in unprecedented amounts of new data, information, and knowledge. Many software tools have been developed to deal with aspects of this transformation and each is sorely needed [1-3]. However, few of these tools have been forced to deal with the full complexity of genome-scale models along with high throughput genome- scale data. This particular situation represents a unique challenge, as it is simultaneously necessary to deal with the vast breadth of genome-scale models and the dizzying depth of high-throughput datasets. It has been observed time and again that as the pace of data generation continues to accelerate, the pace of analysis significantly lags behind [4]. It is also evident that, given the plethora of databases and software efforts [5-12], it is still a significant challenge to work with genome-scale metabolic models, let alone next-generation whole cell models [13-15]. We work at the forefront of model creation and systems scale data generation [16-18]. The OME Framework was borne out of a practical need to enable genome-scale modeling and data analysis under a unified framework to drive the next generation of genome-scale biological models. Here we present the OME Framework. It exists as a set of Python classes. However, we want to emphasize the importance of the underlying design as an addition to the discussions on specifications of a digital cell. A great deal of work and valuable progress has been made by a number of communities [13, 19-24] towards interchange formats and implementations designed to achieve similar goals. While many software tools exist for handling genome-scale

  7. Modelling heart rate kinetics.

    Science.gov (United States)

    Zakynthinaki, Maria S

    2015-01-01

    The objective of the present study was to formulate a simple and at the same time effective mathematical model of heart rate kinetics in response to movement (exercise). Based on an existing model, a system of two coupled differential equations which give the rate of change of heart rate and the rate of change of exercise intensity is used. The modifications introduced to the existing model are justified and discussed in detail, while models of blood lactate accumulation in respect to time and exercise intensity are also presented. The main modification is that the proposed model has now only one parameter which reflects the overall cardiovascular condition of the individual. The time elapsed after the beginning of the exercise, the intensity of the exercise, as well as blood lactate are also taken into account. Application of the model provides information regarding the individual's cardiovascular condition and is able to detect possible changes in it, across the data recording periods. To demonstrate examples of successful numerical fit of the model, constant intensity experimental heart rate data sets of two individuals have been selected and numerical optimization was implemented. In addition, numerical simulations provided predictions for various exercise intensities and various cardiovascular condition levels. The proposed model can serve as a powerful tool for a complete means of heart rate analysis, not only in exercise physiology (for efficiently designing training sessions for healthy subjects) but also in the areas of cardiovascular health and rehabilitation (including application in population groups for which direct heart rate recordings at intense exercises are not possible or not allowed, such as elderly or pregnant women).

  8. Modelling heart rate kinetics.

    Directory of Open Access Journals (Sweden)

    Maria S Zakynthinaki

    Full Text Available The objective of the present study was to formulate a simple and at the same time effective mathematical model of heart rate kinetics in response to movement (exercise. Based on an existing model, a system of two coupled differential equations which give the rate of change of heart rate and the rate of change of exercise intensity is used. The modifications introduced to the existing model are justified and discussed in detail, while models of blood lactate accumulation in respect to time and exercise intensity are also presented. The main modification is that the proposed model has now only one parameter which reflects the overall cardiovascular condition of the individual. The time elapsed after the beginning of the exercise, the intensity of the exercise, as well as blood lactate are also taken into account. Application of the model provides information regarding the individual's cardiovascular condition and is able to detect possible changes in it, across the data recording periods. To demonstrate examples of successful numerical fit of the model, constant intensity experimental heart rate data sets of two individuals have been selected and numerical optimization was implemented. In addition, numerical simulations provided predictions for various exercise intensities and various cardiovascular condition levels. The proposed model can serve as a powerful tool for a complete means of heart rate analysis, not only in exercise physiology (for efficiently designing training sessions for healthy subjects but also in the areas of cardiovascular health and rehabilitation (including application in population groups for which direct heart rate recordings at intense exercises are not possible or not allowed, such as elderly or pregnant women.

  9. Modelling Heart Rate Kinetics

    Science.gov (United States)

    Zakynthinaki, Maria S.

    2015-01-01

    The objective of the present study was to formulate a simple and at the same time effective mathematical model of heart rate kinetics in response to movement (exercise). Based on an existing model, a system of two coupled differential equations which give the rate of change of heart rate and the rate of change of exercise intensity is used. The modifications introduced to the existing model are justified and discussed in detail, while models of blood lactate accumulation in respect to time and exercise intensity are also presented. The main modification is that the proposed model has now only one parameter which reflects the overall cardiovascular condition of the individual. The time elapsed after the beginning of the exercise, the intensity of the exercise, as well as blood lactate are also taken into account. Application of the model provides information regarding the individual’s cardiovascular condition and is able to detect possible changes in it, across the data recording periods. To demonstrate examples of successful numerical fit of the model, constant intensity experimental heart rate data sets of two individuals have been selected and numerical optimization was implemented. In addition, numerical simulations provided predictions for various exercise intensities and various cardiovascular condition levels. The proposed model can serve as a powerful tool for a complete means of heart rate analysis, not only in exercise physiology (for efficiently designing training sessions for healthy subjects) but also in the areas of cardiovascular health and rehabilitation (including application in population groups for which direct heart rate recordings at intense exercises are not possible or not allowed, such as elderly or pregnant women). PMID:25876164

  10. Onsager reciprocity principle for kinetic models and kinetic schemes

    CERN Document Server

    Mahendra, Ajit Kumar

    2013-01-01

    Boltzmann equation requires some alternative simpler kinetic model like BGK to replace the collision term. Such a kinetic model which replaces the Boltzmann collision integral should preserve the basic properties and characteristics of the Boltzmann equation and comply with the requirements of non equilibrium thermodynamics. Most of the research in development of kinetic theory based methods have focused more on entropy conditions, stability and ignored the crucial aspect of non equilibrium thermodynamics. The paper presents a new kinetic model formulated based on the principles of non equilibrium thermodynamics. The new kinetic model yields correct transport coefficients and satisfies Onsager's reciprocity relationship. The present work also describes a novel kinetic particle method and gas kinetic scheme based on this linkage of non-equilibrium thermodynamics and kinetic theory. The work also presents derivation of kinetic theory based wall boundary condition which complies with the principles of non-equili...

  11. Kinetics Modeling of Cancer Immunology.

    Science.gov (United States)

    1986-05-09

    CANCER IMMUNOLOGY -1 DTICS ELECTED SEP 9 8 UNITED STATES NAVAL ACADEMY ANNAPOLIS, MARYLAND V ,1986 %,e docment ha le approved for public A." I and sale...1986 4. TITLE (and Subtitle) S. TYPE OF REPORT & PERIOD COVERED KINETICS MODELING OF CANCER IMMUNOLOGY Final: 1985/1986 6. PERFORMING ORG. REPORT...137 (1986) "Kinetics Modeling of Cancer Immunology " A Trident Scholar Project Report by Midn I/C Scott Helmers, Class of 1986 United States Naval

  12. Crystallization Kinetics within a Generic Modelling Framework

    DEFF Research Database (Denmark)

    Meisler, Kresten Troelstrup; von Solms, Nicolas; Gernaey, Krist

    2013-01-01

    An existing generic modelling framework has been expanded with tools for kinetic model analysis. The analysis of kinetics is carried out within the framework where kinetic constitutive models are collected, analysed and utilized for the simulation of crystallization operations. A modelling...... procedure is proposed to gain the information of crystallization operation kinetic model analysis and utilize this for faster evaluation of crystallization operations....

  13. Integrated stoichiometric, thermodynamic and kinetic modelling of steady state metabolism.

    Science.gov (United States)

    Fleming, R M T; Thiele, I; Provan, G; Nasheuer, H P

    2010-06-07

    The quantitative analysis of biochemical reactions and metabolites is at frontier of biological sciences. The recent availability of high-throughput technology data sets in biology has paved the way for new modelling approaches at various levels of complexity including the metabolome of a cell or an organism. Understanding the metabolism of a single cell and multi-cell organism will provide the knowledge for the rational design of growth conditions to produce commercially valuable reagents in biotechnology. Here, we demonstrate how equations representing steady state mass conservation, energy conservation, the second law of thermodynamics, and reversible enzyme kinetics can be formulated as a single system of linear equalities and inequalities, in addition to linear equalities on exponential variables. Even though the feasible set is non-convex, the reformulation is exact and amenable to large-scale numerical analysis, a prerequisite for computationally feasible genome scale modelling. Integrating flux, concentration and kinetic variables in a unified constraint-based formulation is aimed at increasing the quantitative predictive capacity of flux balance analysis. Incorporation of experimental and theoretical bounds on thermodynamic and kinetic variables ensures that the predicted steady state fluxes are both thermodynamically and biochemically feasible. The resulting in silico predictions are tested against fluxomic data for central metabolism in Escherichia coli and compare favourably with in silico prediction by flux balance analysis.

  14. Chemical kinetics and combustion modeling

    Energy Technology Data Exchange (ETDEWEB)

    Miller, J.A. [Sandia National Laboratories, Livermore, CA (United States)

    1993-12-01

    The goal of this program is to gain qualitative insight into how pollutants are formed in combustion systems and to develop quantitative mathematical models to predict their formation rates. The approach is an integrated one, combining low-pressure flame experiments, chemical kinetics modeling, theory, and kinetics experiments to gain as clear a picture as possible of the process in question. These efforts are focused on problems involved with the nitrogen chemistry of combustion systems and on the formation of soot and PAH in flames.

  15. Kinetic Modeling of Biological Systems

    Energy Technology Data Exchange (ETDEWEB)

    Resat, Haluk; Petzold, Linda; Pettigrew, Michel F.

    2009-04-21

    The dynamics of how its constituent components interact define the spatio-temporal response of a natural system to stimuli. Modeling the kinetics of the processes that represent a biophysical system has long been pursued with the aim of improving our understanding of the studied system. Due to the unique properties of biological systems, in addition to the usual difficulties faced in modeling the dynamics of physical or chemical systems, biological simulations encounter difficulties that result from intrinsic multiscale and stochastic nature of the biological processes. This chapter discusses the implications for simulation of models involving interacting species with very low copy numbers, which often occur in biological systems and give rise to significant relative fluctuations. The conditions necessitating the use of stochastic kinetic simulation methods and the mathematical foundations of the stochastic simulation algorithms are presented. How the well-organized structural hierarchies often seen in biological systems can lead to multiscale problems, and possible ways to address the encountered computational difficulties are discussed. We present the details of the existing kinetic simulation methods, and discuss their strengths and shortcomings. A list of the publicly available kinetic simulation tools and our reflections for future prospects are also provided.

  16. Genome scale engineering techniques for metabolic engineering.

    Science.gov (United States)

    Liu, Rongming; Bassalo, Marcelo C; Zeitoun, Ramsey I; Gill, Ryan T

    2015-11-01

    Metabolic engineering has expanded from a focus on designs requiring a small number of genetic modifications to increasingly complex designs driven by advances in genome-scale engineering technologies. Metabolic engineering has been generally defined by the use of iterative cycles of rational genome modifications, strain analysis and characterization, and a synthesis step that fuels additional hypothesis generation. This cycle mirrors the Design-Build-Test-Learn cycle followed throughout various engineering fields that has recently become a defining aspect of synthetic biology. This review will attempt to summarize recent genome-scale design, build, test, and learn technologies and relate their use to a range of metabolic engineering applications.

  17. Effect of amino acid supplementation on titer and glycosylation distribution in hybridoma cell cultures-Systems biology-based interpretation using genome-scale metabolic flux balance model and multivariate data analysis.

    Science.gov (United States)

    Reimonn, Thomas M; Park, Seo-Young; Agarabi, Cyrus D; Brorson, Kurt A; Yoon, Seongkyu

    2016-09-01

    Genome-scale flux balance analysis (FBA) is a powerful systems biology tool to characterize intracellular reaction fluxes during cell cultures. FBA estimates intracellular reaction rates by optimizing an objective function, subject to the constraints of a metabolic model and media uptake/excretion rates. A dynamic extension to FBA, dynamic flux balance analysis (DFBA), can calculate intracellular reaction fluxes as they change during cell cultures. In a previous study by Read et al. (2013), a series of informed amino acid supplementation experiments were performed on twelve parallel murine hybridoma cell cultures, and this data was leveraged for further analysis (Read et al., Biotechnol Prog. 2013;29:745-753). In order to understand the effects of media changes on the model murine hybridoma cell line, a systems biology approach is applied in the current study. Dynamic flux balance analysis was performed using a genome-scale mouse metabolic model, and multivariate data analysis was used for interpretation. The calculated reaction fluxes were examined using partial least squares and partial least squares discriminant analysis. The results indicate media supplementation increases product yield because it raises nutrient levels extending the growth phase, and the increased cell density allows for greater culture performance. At the same time, the directed supplementation does not change the overall metabolism of the cells. This supports the conclusion that product quality, as measured by glycoform assays, remains unchanged because the metabolism remains in a similar state. Additionally, the DFBA shows that metabolic state varies more at the beginning of the culture but less by the middle of the growth phase, possibly due to stress on the cells during inoculation. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1163-1173, 2016.

  18. Kinetic modelling of enzymatic starch hydrolysis

    NARCIS (Netherlands)

    Bednarska, K.A.

    2015-01-01

    Kinetic modelling of enzymatic starch hydrolysis – a summary K.A. Bednarska The dissertation entitled ‘Kinetic modelling of enzymatic starch hydrolysis’ describes the enzymatic hydrolysis and kinetic modelling of liquefaction and saccharification of wheat starch. A

  19. Kinetic models of conjugated metabolic cycles

    Science.gov (United States)

    Ershov, Yu. A.

    2016-01-01

    A general method is developed for the quantitative kinetic analysis of conjugated metabolic cycles in the human organism. This method is used as a basis for constructing a kinetic graph and model of the conjugated citric acid and ureapoiesis cycles. The results from a kinetic analysis of the model for these cycles are given.

  20. 13C metabolic flux analysis at a genome-scale.

    Science.gov (United States)

    Gopalakrishnan, Saratram; Maranas, Costas D

    2015-11-01

    Metabolic models used in 13C metabolic flux analysis generally include a limited number of reactions primarily from central metabolism. They typically omit degradation pathways, complete cofactor balances, and atom transition contributions for reactions outside central metabolism. This study addresses the impact on prediction fidelity of scaling-up mapping models to a genome-scale. The core mapping model employed in this study accounts for (75 reactions and 65 metabolites) primarily from central metabolism. The genome-scale metabolic mapping model (GSMM) (697 reaction and 595 metabolites) is constructed using as a basis the iAF1260 model upon eliminating reactions guaranteed not to carry flux based on growth and fermentation data for a minimal glucose growth medium. Labeling data for 17 amino acid fragments obtained from cells fed with glucose labeled at the second carbon was used to obtain fluxes and ranges. Metabolic fluxes and confidence intervals are estimated, for both core and genome-scale mapping models, by minimizing the sum of square of differences between predicted and experimentally measured labeling patterns using the EMU decomposition algorithm. Overall, we find that both topology and estimated values of the metabolic fluxes remain largely consistent between core and GSM model. Stepping up to a genome-scale mapping model leads to wider flux inference ranges for 20 key reactions present in the core model. The glycolysis flux range doubles due to the possibility of active gluconeogenesis, the TCA flux range expanded by 80% due to the availability of a bypass through arginine consistent with labeling data, and the transhydrogenase reaction flux was essentially unresolved due to the presence of as many as five routes for the inter-conversion of NADPH to NADH afforded by the genome-scale model. By globally accounting for ATP demands in the GSMM model the unused ATP decreased drastically with the lower bound matching the maintenance ATP requirement. A non

  1. A model of reactor kinetics

    Energy Technology Data Exchange (ETDEWEB)

    Thompson, A.S.; Thompson, B.R.

    1988-09-01

    The analytical model of nuclear reactor transients, incorporating both mechanical and nuclear effects, simulates reactor kinetics. Linear analysis shows the stability borderline for small power perturbations. In a stable system, initial power disturbances die out with time. With an unstable combination of nuclear and mechanical characteristics, initial disturbances persist and may increase with time. With large instability, oscillations of great magnitude occur. Stability requirements set limits on the power density at which particular reactors can operate. The limiting power density depends largely on the product of two terms: the fraction of delayed neutrons and the frictional damping of vibratory motion in reactor core components. As the fraction of delayed neutrons is essentially fixed, mechanical damping largely determines the maximum power density. A computer program, based on the analytical model, calculates and plots reactor power as a nonlinear function of time in response to assigned values of mechanical and nuclear characteristics.

  2. Kinetics model for lutate dosimetry

    Energy Technology Data Exchange (ETDEWEB)

    Lima, M.F.; Mesquita, C.H., E-mail: mflima@ipen.br, E-mail: chmesqui@ipen.br [Instituto de Pesquisas Energeticas (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

    2013-11-01

    The use of compartmental analysis to predict the behavior of drugs in the organism is considered the better option among numerous methods employed in pharmacodynamics. A six compartments model was developed to determinate the kinetic constants of 177Lu-DOTATATO biodistribution using data from one published study with 67 patients treated by PRRT (Peptide receptor radionuclide therapy) and followed by CT during 68,25 hours. The compartmental analysis was made using the software AnaComp Registered-Sign . The influence of the time pos-injection over the dose assessment was studied taking into account the renal excretion management by aminoacid coinfusion, whose direct effects persist in the first day. The biodistribution curve was split in five sectors: 0-0.25h; 0-3.25h; 3.25-24.25h; 24.25-68.25h and 3.25-68.25h. After the examination of that influence, the study was concentrated in separate the biodistribution curve in two phases. Phase 1: governed by uptake from the blood, considering the time pos-injection until 3.25h and phase 2: governed by renal excretion, considering the time pos-injection from 3.25h to 68.25h. The model considered the organs and tissues superposition in the CT image acquisition by sampling parameters as the contribution of the the activity concentration in blood and relation between the sizes of the whole body and measured organs. The kinetic constants obtained from each phase (1 and 2) were used in dose assessment to patients in 26 organs and tissues described by MIRD. Dosimetry results were in agreement with the available results from literature, restrict to whole body, kidneys, bone marrow, spleen and liver. The advantage of the proposed model is the compartmental method quickness and power to estimate dose in organs and tissues, including tumor that, in the most part, were not discriminate by voxels of phantoms built using CT images. (author)

  3. Crystallization Kinetics within a Generic Modeling Framework

    DEFF Research Database (Denmark)

    Meisler, Kresten Troelstrup; von Solms, Nicolas; Gernaey, Krist V.

    2014-01-01

    to the modeling of various kinetic phenomena like nucleation, growth, agglomeration, and breakage are discussed in terms of model forms, model parameters, their availability and/or estimation, and their selection and application for specific crystallization operational scenarios under study. The advantages......A new and extended version of a generic modeling framework for analysis and design of crystallization operations is presented. The new features of this framework are described, with focus on development, implementation, identification, and analysis of crystallization kinetic models. Issues related...... of employing a well-structured model library for storage, use/reuse, and analysis of the kinetic models are highlighted. Examples illustrating the application of the modeling framework for kinetic model discrimination related to simulation of specific crystallization scenarios and for kinetic model parameter...

  4. Analysis of Sensitive CO2 Pathways and Genes Related to Carbon Uptake and Accumulation in Chlamydomonas reinhardtii through Genomic Scale Modeling and Experimental Validation

    Science.gov (United States)

    Winck, Flavia V.; Melo, David O. Páez; Riaño-Pachón, Diego M.; Martins, Marina C. M.; Caldana, Camila; Barrios, Andrés F. González

    2016-01-01

    The development of microalgae sustainable applications needs better understanding of microalgae biology. Moreover, how cells coordinate their metabolism toward biomass accumulation is not fully understood. In this present study, flux balance analysis (FBA) was performed to identify sensitive metabolic pathways of Chlamydomonas reinhardtii under varied CO2 inputs. The metabolic network model of Chlamydomonas was updated based on the genome annotation data and sensitivity analysis revealed CO2 sensitive reactions. Biological experiments were performed with cells cultivated at 0.04% (air), 2.5, 5, 8, and 10% CO2 concentration under controlled conditions and cell growth profiles and biomass content were measured. Pigments, lipids, proteins, and starch were further quantified for the reference low (0.04%) and high (10%) CO2 conditions. The expression level of candidate genes of sensitive reactions was measured and validated by quantitative real time PCR. The sensitive analysis revealed mitochondrial compartment as the major affected by changes on the CO2 concentrations and glycolysis/gluconeogenesis, glyoxylate, and dicarboxylate metabolism among the affected metabolic pathways. Genes coding for glycerate kinase (GLYK), glycine cleavage system, H-protein (GCSH), NAD-dependent malate dehydrogenase (MDH3), low-CO2 inducible protein A (LCIA), carbonic anhydrase 5 (CAH5), E1 component, alpha subunit (PDC3), dual function alcohol dehydrogenase/acetaldehyde dehydrogenase (ADH1), and phosphoglucomutase (GPM2), were defined, among other genes, as sensitive nodes in the metabolic network simulations. These genes were experimentally responsive to the changes in the carbon fluxes in the system. We performed metabolomics analysis using mass spectrometry validating the modulation of carbon dioxide responsive pathways and metabolites. The changes on CO2 levels mostly affected the metabolism of amino acids found in the photorespiration pathway. Our updated metabolic network was

  5. Analysis of sensitive CO2 pathways and genes related to carbon uptake and accumulation in Chlamydomonas reinhardtii through genomic scale modeling and experimental validation

    Directory of Open Access Journals (Sweden)

    Flavia Vischi Winck

    2016-02-01

    Full Text Available The development of microalgae sustainable applications needs better understanding of microalgae biology. Moreover, how cells coordinate their metabolism towards biomass accumulation is not fully understood. In this present study, flux balance analysis (FBA was performed to identify sensitive metabolic pathways of Chlamydomonas reinhardtii under varied CO2 inputs. The metabolic network model of Chlamydomonas was updated based on the genome annotation data and sensitivity analysis revealed CO2 sensitive reactions. Biological experiments were performed with cells cultivated at 0.04% (air, 2.5%, 5%, 8% and 10% CO2 concentration under controlled conditions and cell growth profiles and biomass content were measured. Pigments, lipids, proteins and starch were further quantified for the reference low (0.04% and high (10% CO2 conditions. The expression level of candidate genes of sensitive reactions was measured and validated by quantitative real time qPCR. The sensitive analysis revealed mitochondrial compartment as the major affected by high CO2 levels and glycolysis/gluconeogenesis, glyoxylate and dicarboxylate metabolism among the affected metabolic pathways. Genes coding for glycerate kinase (GLYK, glycine cleavage system, H-protein (GCSH, NAD-dependent malate dehydrogenase (MDH3, low-CO2 inducible protein A (LCIA, carbonic anhydrase 5 (CAH5, E1 component, alpha subunit (PDC3, dual function alcohol dehydrogenase/acetaldehyde dehydrogenase (ADH1 and phosphoglucomutase (GPM2, were defined, among other genes, as sensitive nodes in the metabolic network simulations. These genes were experimentally responsive to the changes in the carbon fluxes in the system. We performed metabolomics analysis using mass spectrometry validating the modulation of carbon dioxide responsive pathways and metabolites. The changes on CO2 levels mostly affected the metabolism of amino acids found in the photorespiration pathway. Our updated metabolic network was compared to

  6. Chemical Kinetic Modeling of 2-Methylhexane Combustion

    KAUST Repository

    Mohamed, Samah Y.

    2015-03-30

    Accurate chemical kinetic combustion models of lightly branched alkanes (e.g., 2-methylalkanes) are important for investigating the combustion behavior of diesel, gasoline, and aviation fuels. Improving the fidelity of existing kinetic models is a necessity, as new experiments and advanced theories show inaccuracy in certain portions of the models. This study focuses on updating thermodynamic data and kinetic model for a gasoline surrogate fuel, 2-methylhexane, with recently published group values and rate rules. These update provides a better agreement with rapid compression machine measurements of ignition delay time, while also strengthening the fundamental basis of the model.

  7. Modeling of Reactor Kinetics and Dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Matthew Johnson; Scott Lucas; Pavel Tsvetkov

    2010-09-01

    In order to model a full fuel cycle in a nuclear reactor, it is necessary to simulate the short time-scale kinetic behavior of the reactor as well as the long time-scale dynamics that occur with fuel burnup. The former is modeled using the point kinetics equations, while the latter is modeled by coupling fuel burnup equations with the kinetics equations. When the equations are solved simultaneously with a nonlinear equation solver, the end result is a code with the unique capability of modeling transients at any time during a fuel cycle.

  8. New types of experimental data shape the use of enzyme kinetics for dynamic network modeling.

    Science.gov (United States)

    Tummler, Katja; Lubitz, Timo; Schelker, Max; Klipp, Edda

    2014-01-01

    Since the publication of Leonor Michaelis and Maude Menten's paper on the reaction kinetics of the enzyme invertase in 1913, molecular biology has evolved tremendously. New measurement techniques allow in vivo characterization of the whole genome, proteome or transcriptome of cells, whereas the classical enzyme essay only allows determination of the two Michaelis-Menten parameters V and K(m). Nevertheless, Michaelis-Menten kinetics are still commonly used, not only in the in vitro context of enzyme characterization but also as a rate law for enzymatic reactions in larger biochemical reaction networks. In this review, we give an overview of the historical development of kinetic rate laws originating from Michaelis-Menten kinetics over the past 100 years. Furthermore, we briefly summarize the experimental techniques used for the characterization of enzymes, and discuss web resources that systematically store kinetic parameters and related information. Finally, describe the novel opportunities that arise from using these data in dynamic mathematical modeling. In this framework, traditional in vitro approaches may be combined with modern genome-scale measurements to foster thorough understanding of the underlying complex mechanisms.

  9. An equilibrium and kinetic modeling

    African Journals Online (AJOL)

    SERVER

    2007-06-18

    Jun 18, 2007 ... Potato dextrose agar medium was prepared by taking 200 g of peeled and sliced potato with .... of glucose as carbon source and ammonium chloride as nitrogen source each. .... Pore and solid diffusion kinetics in fixed bed ...

  10. Kinetic exchange models for social opinion formation

    CERN Document Server

    Lallouache, Mehdi; Chakrabarti, Bikas K

    2010-01-01

    We propose a minimal model for the collective dynamics of opinion formation in the society, by modifying kinetic exchange dynamics studied in the context of income, money or wealth distributions in a society.

  11. Systems biology as a foundation for genome-scale synthetic biology.

    Science.gov (United States)

    Barrett, Christian L; Kim, Tae Yong; Kim, Hyun Uk; Palsson, Bernhard Ø; Lee, Sang Yup

    2006-10-01

    As the ambitions of synthetic biology approach genome-scale engineering, comprehensive characterization of cellular systems is required, as well as a means to accurately model cell-scale molecular interactions. These requirements are coincident with the goals of systems biology and, thus, systems biology will become the foundation for genome-scale synthetic biology. Systems biology will form this foundation through its efforts to reconstruct and integrate cellular systems, develop the mathematics, theory and software tools for the accurate modeling of these integrated systems, and through evolutionary mechanisms. As genome-scale synthetic biology is so enabled, it will prove to be a positive feedback driver of systems biology by exposing and forcing researchers to confront those aspects of systems biology which are inadequately understood.

  12. New approach for phylogenetic tree recovery based on genome-scale metabolic networks.

    Science.gov (United States)

    Gamermann, Daniel; Montagud, Arnaud; Conejero, J Alberto; Urchueguía, Javier F; de Córdoba, Pedro Fernández

    2014-07-01

    A wide range of applications and research has been done with genome-scale metabolic models. In this work, we describe an innovative methodology for comparing metabolic networks constructed from genome-scale metabolic models and how to apply this comparison in order to infer evolutionary distances between different organisms. Our methodology allows a quantification of the metabolic differences between different species from a broad range of families and even kingdoms. This quantification is then applied in order to reconstruct phylogenetic trees for sets of various organisms.

  13. Chemical Kinetic Modeling of Advanced Transportation Fuels

    Energy Technology Data Exchange (ETDEWEB)

    PItz, W J; Westbrook, C K; Herbinet, O

    2009-01-20

    Development of detailed chemical kinetic models for advanced petroleum-based and nonpetroleum based fuels is a difficult challenge because of the hundreds to thousands of different components in these fuels and because some of these fuels contain components that have not been considered in the past. It is important to develop detailed chemical kinetic models for these fuels since the models can be put into engine simulation codes used for optimizing engine design for maximum efficiency and minimal pollutant emissions. For example, these chemistry-enabled engine codes can be used to optimize combustion chamber shape and fuel injection timing. They also allow insight into how the composition of advanced petroleum-based and non-petroleum based fuels affect engine performance characteristics. Additionally, chemical kinetic models can be used separately to interpret important in-cylinder experimental data and gain insight into advanced engine combustion processes such as HCCI and lean burn engines. The objectives are: (1) Develop detailed chemical kinetic reaction models for components of advanced petroleum-based and non-petroleum based fuels. These fuels models include components from vegetable-oil-derived biodiesel, oil-sand derived fuel, alcohol fuels and other advanced bio-based and alternative fuels. (2) Develop detailed chemical kinetic reaction models for mixtures of non-petroleum and petroleum-based components to represent real fuels and lead to efficient reduced combustion models needed for engine modeling codes. (3) Characterize the role of fuel composition on efficiency and pollutant emissions from practical automotive engines.

  14. Genome-scale reconstruction of the Streptococcus pyogenes M49 metabolic network reveals growth requirements and indicates potential drug targets

    NARCIS (Netherlands)

    Levering, J.; Fiedler, T.; Sieg, A.; van Grinsven, K.W.A.; Hering, S.; Veith, N.; Olivier, B.G.; Klett, L.; Hugenholtz, J.; Teusink, B.; Kreikemeyer, B.; Kummer, U.

    2016-01-01

    Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes M49

  15. A kinetic model for predicting biodegradation.

    Science.gov (United States)

    Dimitrov, S; Pavlov, T; Nedelcheva, D; Reuschenbach, P; Silvani, M; Bias, R; Comber, M; Low, L; Lee, C; Parkerton, T; Mekenyan, O

    2007-01-01

    Biodegradation plays a key role in the environmental risk assessment of organic chemicals. The need to assess biodegradability of a chemical for regulatory purposes supports the development of a model for predicting the extent of biodegradation at different time frames, in particular the extent of ultimate biodegradation within a '10 day window' criterion as well as estimating biodegradation half-lives. Conceptually this implies expressing the rate of catabolic transformations as a function of time. An attempt to correlate the kinetics of biodegradation with molecular structure of chemicals is presented. A simplified biodegradation kinetic model was formulated by combining the probabilistic approach of the original formulation of the CATABOL model with the assumption of first order kinetics of catabolic transformations. Nonlinear regression analysis was used to fit the model parameters to OECD 301F biodegradation kinetic data for a set of 208 chemicals. The new model allows the prediction of biodegradation multi-pathways, primary and ultimate half-lives and simulation of related kinetic biodegradation parameters such as biological oxygen demand (BOD), carbon dioxide production, and the nature and amount of metabolites as a function of time. The model may also be used for evaluating the OECD ready biodegradability potential of a chemical within the '10-day window' criterion.

  16. Adsorption studies of molasse's wastewaters on activated carbon: modelling with a new fractal kinetic equation and evaluation of kinetic models.

    Science.gov (United States)

    Figaro, S; Avril, J P; Brouers, F; Ouensanga, A; Gaspard, S

    2009-01-30

    Adsorption kinetic of molasses wastewaters after anaerobic digestion (MSWD) and melanoidin respectively on activated carbon was studied at different pH. The kinetic parameters could be determined using classical kinetic equations and a recently published fractal kinetic equation. A linear form of this equation can also be used to fit adsorption data. Even with lower correlation coefficients the fractal kinetic equation gives lower normalized standard deviation values than the pseudo-second order model generally used to fit adsorption kinetic data, indicating that the fractal kinetic model is much more accurate for describing the kinetic adsorption data than the pseudo-second order kinetic model.

  17. Chemical Kinetic Models for Advanced Engine Combustion

    Energy Technology Data Exchange (ETDEWEB)

    Pitz, William J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Mehl, Marco [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Westbrook, Charles K. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2014-10-22

    The objectives for this project are as follows: Develop detailed chemical kinetic models for fuel components used in surrogate fuels for compression ignition (CI), homogeneous charge compression ignition (HCCI) and reactivity-controlled compression-ignition (RCCI) engines; and Combine component models into surrogate fuel models to represent real transportation fuels. Use them to model low-temperature combustion strategies in HCCI, RCCI, and CI engines that lead to low emissions and high efficiency.

  18. Kinetic models with randomly perturbed binary collisions

    CERN Document Server

    Bassetti, Federico; Toscani, Giuseppe

    2010-01-01

    We introduce a class of Kac-like kinetic equations on the real line, with general random collisional rules, which include as particular cases models for wealth redistribution in an agent-based market or models for granular gases with a background heat bath. Conditions on these collisional rules which guarantee both the existence and uniqueness of equilibrium profiles and their main properties are found. We show that the characterization of these stationary solutions is of independent interest, since the same profiles are shown to be solutions of different evolution problems, both in the econophysics context and in the kinetic theory of rarefied gases.

  19. Kinetic and hydrodynamic models of chemotactic aggregation

    CERN Document Server

    Chavanis, Pierre-Henri

    2007-01-01

    We derive general kinetic and hydrodynamic models of chemotactic aggregation that describe certain features of the morphogenesis of biological colonies (like bacteria, amoebae, endothelial cells or social insects). Starting from a stochastic model defined in terms of N coupled Langevin equations, we derive a nonlinear mean field Fokker-Planck equation governing the evolution of the distribution function of the system in phase space. By taking the successive moments of this kinetic equation and using a local thermodynamic equilibrium condition, we derive a set of hydrodynamic equations involving a damping term. In the limit of small frictions, we obtain a hyperbolic model describing the formation of network patterns (filaments) and in the limit of strong frictions we obtain a parabolic model which is a generalization of the standard Keller-Segel model describing the formation of clusters (clumps). Our approach connects and generalizes several models introduced in the chemotactic literature. We discuss the anal...

  20. A kinetic model of zircon thermoluminescence

    NARCIS (Netherlands)

    Turkin, A.A.; Es, H.J. van; Vainshtein, D.I.; Hartog, H.W. den

    A kinetic model of zircon thermoluminescence (TL) has been constructed to simulate the processes and stages relevant to thermoluminescent dating such as: filling of electron and hole traps during the excitation stage both for natural and laboratory irradiation; the time dependence of fading after

  1. Kinetic modeling of reactions in Foods

    NARCIS (Netherlands)

    Boekel, van M.A.J.S.

    2008-01-01

    The level of quality that food maintains as it travels down the production-to-consumption path is largely determined by the chemical, biochemical, physical, and microbiological changes that take place during its processing and storage. Kinetic Modeling of Reactions in Foods demonstrates how to effec

  2. Gaussian kinetic model for granular gases.

    Science.gov (United States)

    Dufty, James W; Baskaran, Aparna; Zogaib, Lorena

    2004-05-01

    A kinetic model for the Boltzmann equation is proposed and explored as a practical means to investigate the properties of a dilute granular gas. It is shown that all spatially homogeneous initial distributions approach a universal "homogeneous cooling solution" after a few collisions. The homogeneous cooling solution (HCS) is studied in some detail and the exact solution is compared with known results for the hard sphere Boltzmann equation. It is shown that all qualitative features of the HCS, including the nature of overpopulation at large velocities, are reproduced by the kinetic model. It is also shown that all the transport coefficients are in excellent agreement with those from the Boltzmann equation. Also, the model is specialized to one having a velocity independent collision frequency and the resulting HCS and transport coefficients are compared to known results for the Maxwell model. The potential of the model for the study of more complex spatially inhomogeneous states is discussed.

  3. In Silico Genome-Scale Reconstruction and Validation of the Corynebacterium glutamicum Metabolic Network

    DEFF Research Database (Denmark)

    Kjeldsen, Kjeld Raunkjær; Nielsen, J.

    2009-01-01

    A genome-scale metabolic model of the Gram-positive bacteria Corynebacterium glutamicum ATCC 13032 was constructed comprising 446 reactions and 411 metabolite, based on the annotated genome and available biochemical information. The network was analyzed using constraint based methods. The model...... and lactate. Comparable flux values between in silico model and experimental values were seen, although some differences in the phenotypic behavior between the model and the experimental data were observed,...

  4. Kinetics model development of cocoa bean fermentation

    Science.gov (United States)

    Kresnowati, M. T. A. P.; Gunawan, Agus Yodi; Muliyadini, Winny

    2015-12-01

    Although Indonesia is one of the biggest cocoa beans producers in the world, Indonesian cocoa beans are oftenly of low quality and thereby frequently priced low in the world market. In order to improve the quality, adequate post-harvest cocoa processing techniques are required. Fermentation is the vital stage in series of cocoa beans post harvest processing which could improve the quality of cocoa beans, in particular taste, aroma, and colours. During the fermentation process, combination of microbes grow producing metabolites that serve as the precursors for cocoa beans flavour. Microbial composition and thereby their activities will affect the fermentation performance and influence the properties of cocoa beans. The correlation could be reviewed using a kinetic model that includes unstructured microbial growth, substrate utilization and metabolic product formation. The developed kinetic model could be further used to design cocoa bean fermentation process to meet the expected quality. Further the development of kinetic model of cocoa bean fermentation also serve as a good case study of mixed culture solid state fermentation, that has rarely been studied. This paper presents the development of a kinetic model for solid-state cocoa beans fermentation using an empirical approach. Series of lab scale cocoa bean fermentations, either natural fermentations without starter addition or fermentations with mixed yeast and lactic acid bacteria starter addition, were used for model parameters estimation. The results showed that cocoa beans fermentation can be modelled mathematically and the best model included substrate utilization, microbial growth, metabolites production and its transport. Although the developed model still can not explain the dynamics in microbial population, this model can sufficiently explained the observed changes in sugar concentration as well as metabolic products in the cocoa bean pulp.

  5. Computational model for Halorhodopsin photocurrent kinetics

    Science.gov (United States)

    Bravo, Jaime; Stefanescu, Roxana; Talathi, Sachin

    2013-03-01

    Optogenetics is a rapidly developing novel optical stimulation technique that employs light activated ion channels to excite (using channelrhodopsin (ChR)) or suppress (using halorhodopsin (HR)) impulse activity in neurons with high temporal and spatial resolution. This technique holds enormous potential to externally control activity states in neuronal networks. The channel kinetics of ChR and HR are well understood and amenable for mathematical modeling. Significant progress has been made in recent years to develop models for ChR channel kinetics. To date however, there is no model to mimic photocurrents produced by HR. Here, we report the first model developed for HR photocurrents based on a four-state model of the HR photocurrent kinetics. The model provides an excellent fit (root-mean-square error of 3.1862x10-4, to an empirical profile of experimentally measured HR photocurrents. In combination, mathematical models for ChR and HR photocurrents can provide effective means to design test light based control systems to regulate neural activity, which in turn may have implications for the development of novel light based stimulation paradigms for brain disease control. I would like to thank the University of Florida and the Physics Research Experience for Undergraduates (REU) program, funded through NSF DMR-1156737. This research was also supported through start-up funds provided to Dr. Sachin Talathi

  6. Modeling inhomogeneous DNA replication kinetics.

    Directory of Open Access Journals (Sweden)

    Michel G Gauthier

    Full Text Available In eukaryotic organisms, DNA replication is initiated at a series of chromosomal locations called origins, where replication forks are assembled proceeding bidirectionally to replicate the genome. The distribution and firing rate of these origins, in conjunction with the velocity at which forks progress, dictate the program of the replication process. Previous attempts at modeling DNA replication in eukaryotes have focused on cases where the firing rate and the velocity of replication forks are homogeneous, or uniform, across the genome. However, it is now known that there are large variations in origin activity along the genome and variations in fork velocities can also take place. Here, we generalize previous approaches to modeling replication, to allow for arbitrary spatial variation of initiation rates and fork velocities. We derive rate equations for left- and right-moving forks and for replication probability over time that can be solved numerically to obtain the mean-field replication program. This method accurately reproduces the results of DNA replication simulation. We also successfully adapted our approach to the inverse problem of fitting measurements of DNA replication performed on single DNA molecules. Since such measurements are performed on specified portion of the genome, the examined DNA molecules may be replicated by forks that originate either within the studied molecule or outside of it. This problem was solved by using an effective flux of incoming replication forks at the model boundaries to represent the origin activity outside the studied region. Using this approach, we show that reliable inferences can be made about the replication of specific portions of the genome even if the amount of data that can be obtained from single-molecule experiments is generally limited.

  7. Reduced Chemical Kinetic Model for Titan Entries

    Directory of Open Access Journals (Sweden)

    Romain Savajano

    2011-01-01

    Full Text Available A reduced chemical kinetic model for Titan's atmosphere has been developed. This new model with 18 species and 28 reactions includes the mainfeatures of a more complete scheme, respecting the radiative fluxes. It has been verified against three key elements: a sensitivity analysis, the equilibrium chemical composition using shock tube simulations in CHEMKIN, and the results of computational fluid dynamics (CFDs simulations.

  8. Compartmental modeling and tracer kinetics

    CERN Document Server

    Anderson, David H

    1983-01-01

    This monograph is concerned with mathematical aspects of compartmental an­ alysis. In particular, linear models are closely analyzed since they are fully justifiable as an investigative tool in tracer experiments. The objective of the monograph is to bring the reader up to date on some of the current mathematical prob­ lems of interest in compartmental analysis. This is accomplished by reviewing mathematical developments in the literature, especially over the last 10-15 years, and by presenting some new thoughts and directions for future mathematical research. These notes started as a series of lectures that I gave while visiting with the Division of Applied ~1athematics, Brown University, 1979, and have developed in­ to this collection of articles aimed at the reader with a beginning graduate level background in mathematics. The text can be used as a self-paced reading course. With this in mind, exercises have been appropriately placed throughout the notes. As an aid in reading the material, the e~d of a ...

  9. Thermodynamic and kinetic modelling: creep resistant materials

    DEFF Research Database (Denmark)

    Hald, John; Korcakova, L.; Danielsen, Hilmar Kjartansson

    2008-01-01

    particles and coarsening of MX, M23C6 and Laves phase particles. The modelling provided new insight into the long term stability of new steels. Modelling of the detrimental precipitation of Z phase Cr(V,Nb)N is described, which points to new approaches in alloy development for higher temperatures......The use of thermodynamic and kinetic modelling of microstructure evolution in materials exposed to high temperatures in power plants is demonstrated with two examples. Precipitate stability in martensitic 9–12%Cr steels is modelled including equilibrium phase stability, growth of Laves phase...

  10. MODELING STYRENE HYDROGENATION KINETICS USING PALLADIUM CATALYSTS

    Directory of Open Access Journals (Sweden)

    G. T. Justino

    Full Text Available Abstract The high octane number of pyrolysis gasoline (PYGAS explains its insertion in the gasoline pool. However, its use is troublesome due to the presence of gum-forming chemicals which, in turn, can be removed via hydrogenation. The use of Langmuir-Hinshelwood kinetic models was evaluated for hydrogenation of styrene, a typical gum monomer, using Pd/9%Nb2O5-Al2O3 as catalyst. Kinetic models accounting for hydrogen dissociative and non-dissociative adsorption were considered. The availability of one or two kinds of catalytic sites was analyzed. Experiments were carried out in a semi-batch reactor at constant temperature and pressure in the absence of transport limitations. The conditions used in each experiment varied between 16 - 56 bar and 60 - 100 ºC for pressure and temperature, respectively. The kinetic models were evaluated using MATLAB and EMSO software. Models using adsorption of hydrogen and organic molecules on the same type of site fitted the data best.

  11. A kinetic model for chemical neurotransmission

    Science.gov (United States)

    Ramirez-Santiago, Guillermo; Martinez-Valencia, Alejandro; Fernandez de Miguel, Francisco

    Recent experimental observations in presynaptic terminals at the neuromuscular junction indicate that there are stereotyped patterns of cooperativeness in the fusion of adjacent vesicles. That is, a vesicle in hemifusion process appears on the side of a fused vesicle and which is followed by another vesicle in a priming state while the next one is in a docking state. In this talk we present a kinetic model for this morphological pattern in which each vesicle state previous to the exocytosis is represented by a kinetic state. This chain states kinetic model can be analyzed by means of a Master equation whose solution is simulated with the stochastic Gillespie algorithm. With this approach we have reproduced the responses to the basal release in the absence of stimulation evoked by the electrical activity and the phenomena of facilitation and depression of neuromuscular synapses. This model offers new perspectives to understand the underlying phenomena in chemical neurotransmission based on molecular interactions that result in the cooperativity between vesicles during neurotransmitter release. DGAPA Grants IN118410 and IN200914 and Conacyt Grant 130031.

  12. Kinetic effects in edge plasma: kinetic modeling for edge plasma and detached divertor

    Science.gov (United States)

    Takizuka, T.

    2017-03-01

    Detached divertor is considered a solution for the heat control in magnetic-confinement fusion reactors. Numerical simulations using the comprehensive divertor codes based on the plasma fluid modeling are indispensable for the design of the detached divertor in future reactors. Since the agreement in the results between detached-divertor experiments and simulations has been rather fair but not satisfactory, further improvement of the modeling is required. The kinetic effect is one of key issues for improving the modeling. Complete kinetic behaviors are able to be simulated by the kinetic modeling. In this paper at first, major kinetic effects in edge plasma and detached divertor are listed. One of the most powerful kinetic models, particle-in-cell (PIC) model, is described in detail. Several results of PIC simulations of edge-plasma kinetic natures are presented. Future works on PIC modeling and simulation for the deeper understanding of edge plasma and detached divertor are discussed.

  13. Basic and applied uses of genome-scale metabolic network reconstructions of Escherichia coli

    DEFF Research Database (Denmark)

    McCloskey, Douglas; Palsson, Bernhard; Feist, Adam

    2013-01-01

    The genome-scale model (GEM) of metabolism in the bacterium Escherichia coli K-12 has been in development for over a decade and is now in wide use. GEM-enabled studies of E. coli have been primarily focused on six applications: (1) metabolic engineering, (2) model-driven discovery, (3) prediction...... of cellular phenotypes, (4) analysis of biological network properties, (5) studies of evolutionary processes, and (6) models of interspecies interactions. In this review, we provide an overview of these applications along with a critical assessment of their successes and limitations, and a perspective...... on likely future developments in the field. Taken together, the studies performed over the past decade have established a genome-scale mechanistic understanding of genotype-phenotype relationships in E. coli metabolism that forms the basis for similar efforts for other microbial species. Future challenges...

  14. Integration of expression data in genome-scale metabolic network reconstructions

    Directory of Open Access Journals (Sweden)

    Anna S. Blazier

    2012-08-01

    Full Text Available With the advent of high-throughput technologies, the field of systems biology has amassed an abundance of omics data, quantifying thousands of cellular components across a variety of scales, ranging from mRNA transcript levels to metabolite quantities. Methods are needed to not only integrate this omics data but to also use this data to heighten the predictive capabilities of computational models. Several recent studies have successfully demonstrated how flux balance analysis (FBA, a constraint-based modeling approach, can be used to integrate transcriptomic data into genome-scale metabolic network reconstructions to generate predictive computational models. In this review, we summarize such FBA-based methods for integrating expression data into genome-scale metabolic network reconstructions, highlighting their advantages as well as their limitations.

  15. MATHEMATICAL MODELING OF ORANGE SEED DRYING KINETICS

    Directory of Open Access Journals (Sweden)

    Daniele Penteado Rosa

    2015-06-01

    Full Text Available Drying of orange seeds representing waste products from juice processing was studied in the temperatures of 40, 50, 60 and 70 °C and drying velocities of 0.6, 1.0 and 1.4 m/s. Experimental drying kinetics of orange seeds were obtained using a convective air forced dryer. Three thin-layer models: Page model, Lewis model, and the Henderson-Pabis model and the diffusive model were used to predict the drying curves. The Henderson-Pabis and the diffusive models show the best fitting performance and statistical evaluations. Moreover, the temperature dependence on the effective diffusivity followed an Arrhenius relationship, and the activation energies ranging from 16.174 to 16.842 kJ/mol

  16. Modelling dimercaptosuccinic acid (DMSA) plasma kinetics in humans

    NARCIS (Netherlands)

    van Eijkeren, Jan C H; Olie, J Daniël N; Bradberry, Sally M; Vale, J Allister; de Vries, Irma; Meulenbelt, Jan; Hunault, Claudine C

    2016-01-01

    CONTEXT: No kinetic models presently exist which simulate the effect of chelation therapy on lead blood concentrations in lead poisoning. OBJECTIVE: Our aim was to develop a kinetic model that describes the kinetics of dimercaptosuccinic acid (DMSA; succimer), a commonly used chelating agent, that c

  17. A kinetic model of plasma turbulence

    Science.gov (United States)

    Servidio, S.; Valentini, F.; Perrone, D.; Greco, A.; Califano, F.; Matthaeus, W. H.; Veltri, P.

    2015-01-01

    A Hybrid Vlasov-Maxwell (HVM) model is presented and recent results about the link between kinetic effects and turbulence are reviewed. Using five-dimensional (2D in space and 3D in the velocity space) simulations of plasma turbulence, it is found that kinetic effects (or non-fluid effects) manifest through the deformation of the proton velocity distribution function (DF), with patterns of non-Maxwellian features being concentrated near regions of strong magnetic gradients. The direction of the proper temperature anisotropy, calculated in the main reference frame of the distribution itself, has a finite probability of being along or across the ambient magnetic field, in general agreement with the classical definition of anisotropy T ⊥/T ∥ (where subscripts refer to the magnetic field direction). Adopting the latter conventional definition, by varying the global plasma beta (β) and fluctuation level, simulations explore distinct regions of the space given by T ⊥/T ∥ and β∥, recovering solar wind observations. Moreover, as in the solar wind, HVM simulations suggest that proton anisotropy is not only associated with magnetic intermittent events, but also with gradient-type structures in the flow and in the density. The role of alpha particles is reviewed using multi-ion kinetic simulations, revealing a similarity between proton and helium non-Maxwellian effects. The techniques presented here are applied to 1D spacecraft-like analysis, establishing a link between non-fluid phenomena and solar wind magnetic discontinuities. Finally, the dimensionality of turbulence is investigated, for the first time, via 6D HVM simulations (3D in both spaces). These preliminary results provide support for several previously reported studies based on 2.5D simulations, confirming several basic conclusions. This connection between kinetic features and turbulence open a new path on the study of processes such as heating, particle acceleration, and temperature

  18. Mathematical Modelling of Thermal Degradation Kinetics of Ascorbic ...

    African Journals Online (AJOL)

    However, adequate study has not been conducted to exploit the potential of this ... of ascorbic acid in yeabesha gomen fitted first-order reaction kinetic model ... Activation energy for ascorbic degeneration kinetics of yeabesha gomen was ...

  19. Thermodynamic and kinetic modeling of transcriptional pausing.

    Science.gov (United States)

    Tadigotla, Vasisht R; O Maoiléidigh, Dáibhid; Sengupta, Anirvan M; Epshtein, Vitaly; Ebright, Richard H; Nudler, Evgeny; Ruckenstein, Andrei E

    2006-03-21

    We present a statistical mechanics approach for the prediction of backtracked pauses in bacterial transcription elongation derived from structural models of the transcription elongation complex (EC). Our algorithm is based on the thermodynamic stability of the EC along the DNA template calculated from the sequence-dependent free energy of DNA-DNA, DNA-RNA, and RNA-RNA base pairing associated with (i) the translocational and size fluctuations of the transcription bubble; (ii) changes in the associated DNA-RNA hybrid; and (iii) changes in the cotranscriptional RNA secondary structure upstream of the RNA exit channel. The calculations involve no adjustable parameters except for a cutoff used to discriminate paused from nonpaused complexes. When applied to 100 experimental pauses in transcription elongation by Escherichia coli RNA polymerase on 10 DNA templates, the approach produces statistically significant results. We also present a kinetic model for the rate of recovery of backtracked paused complexes. A crucial ingredient of our model is the incorporation of kinetic barriers to backtracking resulting from steric clashes of EC with the cotranscriptionally generated RNA secondary structure, an aspect not included explicitly in previous attempts at modeling the transcription elongation process.

  20. Thermodynamically consistent model calibration in chemical kinetics

    Directory of Open Access Journals (Sweden)

    Goutsias John

    2011-05-01

    Full Text Available Abstract Background The dynamics of biochemical reaction systems are constrained by the fundamental laws of thermodynamics, which impose well-defined relationships among the reaction rate constants characterizing these systems. Constructing biochemical reaction systems from experimental observations often leads to parameter values that do not satisfy the necessary thermodynamic constraints. This can result in models that are not physically realizable and may lead to inaccurate, or even erroneous, descriptions of cellular function. Results We introduce a thermodynamically consistent model calibration (TCMC method that can be effectively used to provide thermodynamically feasible values for the parameters of an open biochemical reaction system. The proposed method formulates the model calibration problem as a constrained optimization problem that takes thermodynamic constraints (and, if desired, additional non-thermodynamic constraints into account. By calculating thermodynamically feasible values for the kinetic parameters of a well-known model of the EGF/ERK signaling cascade, we demonstrate the qualitative and quantitative significance of imposing thermodynamic constraints on these parameters and the effectiveness of our method for accomplishing this important task. MATLAB software, using the Systems Biology Toolbox 2.1, can be accessed from http://www.cis.jhu.edu/~goutsias/CSS lab/software.html. An SBML file containing the thermodynamically feasible EGF/ERK signaling cascade model can be found in the BioModels database. Conclusions TCMC is a simple and flexible method for obtaining physically plausible values for the kinetic parameters of open biochemical reaction systems. It can be effectively used to recalculate a thermodynamically consistent set of parameter values for existing thermodynamically infeasible biochemical reaction models of cellular function as well as to estimate thermodynamically feasible values for the parameters of new

  1. Modeling in applied sciences a kinetic theory approach

    CERN Document Server

    Pulvirenti, Mario

    2000-01-01

    Modeling complex biological, chemical, and physical systems, in the context of spatially heterogeneous mediums, is a challenging task for scientists and engineers using traditional methods of analysis Modeling in Applied Sciences is a comprehensive survey of modeling large systems using kinetic equations, and in particular the Boltzmann equation and its generalizations An interdisciplinary group of leading authorities carefully develop the foundations of kinetic models and discuss the connections and interactions between model theories, qualitative and computational analysis and real-world applications This book provides a thoroughly accessible and lucid overview of the different aspects, models, computations, and methodology for the kinetic-theory modeling process Topics and Features * Integrated modeling perspective utilized in all chapters * Fluid dynamics of reacting gases * Self-contained introduction to kinetic models * Becker–Doring equations * Nonlinear kinetic models with chemical reactions * Kinet...

  2. Genome-scale reconstruction of the sigma factor network in Escherichia coli: topology and functional states

    DEFF Research Database (Denmark)

    Cho, Byung-Kwan; Kim, Donghyuk; Knight, Eric M.

    2014-01-01

    to transcription units (TUs), representing an increase of more than 300% over what has been previously reported. The reconstructed network was used to investigate competition between alternative sigma-factors (the sigma(70) and sigma(38) regulons), confirming the competition model of sigma substitution......Background: At the beginning of the transcription process, the RNA polymerase (RNAP) core enzyme requires a sigma-factor to recognize the genomic location at which the process initiates. Although the crucial role of sigma-factors has long been appreciated and characterized for many individual...... promoters, we do not yet have a genome-scale assessment of their function. Results: Using multiple genome-scale measurements, we elucidated the network of s-factor and promoter interactions in Escherichia coli. The reconstructed network includes 4,724 sigma-factor-specific promoters corresponding...

  3. On Kinetics Modeling of Vibrational Energy Transfer

    Science.gov (United States)

    Gilmore, John O.; Sharma, Surendra P.; Cavolowsky, John A. (Technical Monitor)

    1996-01-01

    Two models of vibrational energy exchange are compared at equilibrium to the elementary vibrational exchange reaction for a binary mixture. The first model, non-linear in the species vibrational energies, was derived by Schwartz, Slawsky, and Herzfeld (SSH) by considering the detailed kinetics of vibrational energy levels. This model recovers the result demanded at equilibrium by the elementary reaction. The second model is more recent, and is gaining use in certain areas of computational fluid dynamics. This model, linear in the species vibrational energies, is shown not to recover the required equilibrium result. Further, this more recent model is inconsistent with its suggested rate constants in that those rate constants were inferred from measurements by using the SSH model to reduce the data. The non-linear versus linear nature of these two models can lead to significant differences in vibrational energy coupling. Use of the contemporary model may lead to significant misconceptions, especially when integrated in computer codes considering multiple energy coupling mechanisms.

  4. MODELLING OF KINETICS OF FLUORINE ADSORPTION ONTO MODIFIED DIATOMITE

    Directory of Open Access Journals (Sweden)

    VEACESLAV ZELENTSOV

    2017-03-01

    Full Text Available The paper presents kinetics modelling of adsorption of fluorine onto modified diatomite, its fundamental characteristics and mathematical derivations. Three models of defluoridation kinetics were used to fit the experimental results on adsorption fluorine onto diatomite: the pseudo-first order model Lagergren, the pseudo-second order model G. McKay and H.S. Ho and intraparticle diffusion model of W.J. Weber and J.C. Morris. Kinetics studies revealed that the adsorption of fluorine followed second-order rate model, complimented by intraparticle diffusion kinetics. The adsorption mechanism of fluorine involved three stages – external surface adsorption, intraparticle diffusion and the stage of equilibrium.

  5. Kinetic depletion model for pellet ablation

    Energy Technology Data Exchange (ETDEWEB)

    Kuteev, Boris V. [State Technical Univ., St. Petersburg (Russian Federation)

    2001-11-01

    A kinetic model for depletion effect, which determines pellet ablation when the pellet passes a rational magnetic surface, is formulated. The model predicts a moderate decrease of the ablation rate compared with the earlier considered monoenergy versions [1, 2]. For typical T-10 conditions the ablation rate reduces by a reactor of 2.5 when the 1-mm pellet penetrates through the plasma center. A substantial deceleration of pellets -about 15% per centimeter of low shire rational q region; is predicted. Penetration for Low Field Side and High Field Side injections is considered taking into account modification of the electron distribution function by toroidal magnetic field. It is shown that Shafranov shift and toroidal effects yield the penetration length for HFS injection higher by a factor of 1.5. This fact should be taken into account when plasma-shielding effects on penetration are considered. (author)

  6. Holographic kinetic k-essence model

    Energy Technology Data Exchange (ETDEWEB)

    Cruz, Norman [Departamento de Fisica, Facultad de Ciencia, Universidad de Santiago de Chile, Casilla 307, Santiago (Chile)], E-mail: ncruz@lauca.usach.cl; Gonzalez-Diaz, Pedro F.; Rozas-Fernandez, Alberto [Colina de los Chopos, Instituto de Fisica Fundamental, Consejo Superior de Investigaciones Cientificas, Serrano 121, 28006 Madrid (Spain)], E-mail: a.rozas@cfmac.csic.es; Sanchez, Guillermo [Departamento de Matematica y Ciencia de la Computacion, Facultad de Ciencia, Universidad de Santiago de Chile, Casilla 307, Santiago (Chile)], E-mail: gsanchez@usach.cl

    2009-08-31

    We consider a connection between the holographic dark energy density and the kinetic k-essence energy density in a flat FRW universe. With the choice c{>=}1, the holographic dark energy can be described by a kinetic k-essence scalar field in a certain way. In this Letter we show this kinetic k-essential description of the holographic dark energy with c{>=}1 and reconstruct the kinetic k-essence function F(X)

  7. Population balance modeling of antibodies aggregation kinetics.

    Science.gov (United States)

    Arosio, Paolo; Rima, Simonetta; Lattuada, Marco; Morbidelli, Massimo

    2012-06-21

    The aggregates morphology and the aggregation kinetics of a model monoclonal antibody under acidic conditions have been investigated. Growth occurs via irreversible cluster-cluster coagulation forming compact, fractal aggregates with fractal dimension of 2.6. We measured the time evolution of the average radius of gyration, , and the average hydrodynamic radius, , by in situ light scattering, and simulated the aggregation kinetics by a modified Smoluchowski's population balance equations. The analysis indicates that aggregation does not occur under diffusive control, and allows quantification of effective intermolecular interactions, expressed in terms of the Fuchs stability ratio (W). In particular, by introducing a dimensionless time weighed on W, the time evolutions of measured under various operating conditions (temperature, pH, type and concentration of salt) collapse on a single master curve. The analysis applies also to data reported in the literature when growth by cluster-cluster coagulation dominates, showing a certain level of generality in the antibodies aggregation behavior. The quantification of the stability ratio gives important physical insights into the process, including the Arrhenius dependence of the aggregation rate constant and the relationship between monomer-monomer and cluster-cluster interactions. Particularly, it is found that the reactivity of non-native monomers is larger than that of non-native aggregates, likely due to the reduction of the number of available hydrophobic patches during aggregation.

  8. Kinetic modelling of coupled transport across biological membranes.

    Science.gov (United States)

    Korla, Kalyani; Mitra, Chanchal K

    2014-04-01

    In this report, we have modelled a secondary active co-transporter (symport and antiport), based on the classical kinetics model. Michaelis-Menten model of enzyme kinetics for a single substrate, single intermediate enzyme catalyzed reaction was proposed more than a hundred years ago. However, no single model for the kinetics of co-transport of molecules across a membrane is available in the literature We have made several simplifying assumptions and have followed the basic Michaelis-Menten approach. The results have been simulated using GNU Octave. The results will be useful in general kinetic simulations and modelling.

  9. Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network

    DEFF Research Database (Denmark)

    Förster, Jochen; Famili, I.; Fu, P.

    2003-01-01

    and the environment were included. A total of 708 structural open reading frames (ORFs) were accounted for in the reconstructed network, corresponding to 1035 metabolic reactions. Further, 140 reactions were included on the basis of biochemical evidence resulting in a genome-scale reconstructed metabolic network...... with Escherichia coli. The reconstructed metabolic network is the first comprehensive network for a eukaryotic organism, and it may be used as the basis for in silico analysis of phenotypic functions....

  10. Electrothermal Model of Kinetic Inductance Detectors

    CERN Document Server

    Thomas, Christopher N; Goldie, David J

    2014-01-01

    An electrothermal model of Kinetic Inductance Detectors (KIDs) is described. The non-equilibrium state of the resonator's quasiparticle system is characterized by an effective temperature, which because of readout-power heating is higher than that of the bath. By balancing the flow of energy into the quasiparticle system, it is possible to calculate the steady-state large-signal, small-signal and noise behaviour. Resonance-curve distortion and hysteretic switching appear naturally within the framework. It is shown that an electrothermal feedback process exists, which affects all aspects of behaviour. It is also shown that generation-recombination noise can be interpreted in terms of the thermal fluctuation noise in the effective thermal conductance that links the quasiparticle and phonon systems of the resonator. Because the scheme is based on electrothermal considerations, multiple elements can be added to simulate the behaviour of complex devices, such as resonators on membranes, again taking into account r...

  11. Determination of sample size in genome-scale RNAi screens.

    Science.gov (United States)

    Zhang, Xiaohua Douglas; Heyse, Joseph F

    2009-04-01

    For genome-scale RNAi research, it is critical to investigate sample size required for the achievement of reasonably low false negative rate (FNR) and false positive rate. The analysis in this article reveals that current design of sample size contributes to the occurrence of low signal-to-noise ratio in genome-scale RNAi projects. The analysis suggests that (i) an arrangement of 16 wells per plate is acceptable and an arrangement of 20-24 wells per plate is preferable for a negative control to be used for hit selection in a primary screen without replicates; (ii) in a confirmatory screen or a primary screen with replicates, a sample size of 3 is not large enough, and there is a large reduction in FNRs when sample size increases from 3 to 4. To search a tradeoff between benefit and cost, any sample size between 4 and 11 is a reasonable choice. If the main focus is the selection of siRNAs with strong effects, a sample size of 4 or 5 is a good choice. If we want to have enough power to detect siRNAs with moderate effects, sample size needs to be 8, 9, 10 or 11. These discoveries about sample size bring insight to the design of a genome-scale RNAi screen experiment.

  12. A review on solar wind modeling: kinetic and fluid aspects

    CERN Document Server

    Echim, Marius; Lie-Svendsen, Oystein

    2013-01-01

    We review the main advantages and limitations of the kinetic exospheric and fluid models of the solar wind (SW). We discuss the hydrostatic model imagined by Chapman, the first supersonic hydrodynamic models published by Parker and the first generation subsonic kinetic model proposed by Chamberlain. It is shown that a correct estimation of the electric field as in the second generation kinetic exospheric models developed by Lemaire and Scherer, provides a supersonic expansion of the corona, reconciling the hydrodynamic and the kinetic approach. The third generation kinetic exospheric models considers kappa velocity distribution function (VDF) instead of a Maxwellian at the exobase and in addition they treat a non-monotonic variation of the electric potential with the radial distance; the fourth generation exospheric models include Coulomb collisions based on the Fokker--Planck collision term. Multi-fluid models of the solar wind provide a coarse grained description and reproduce with success the spatio-tempor...

  13. Chemical Kinetic Modeling of Biofuel Combustion

    Science.gov (United States)

    Sarathy, Subram Maniam

    Bioalcohols, such as bioethanol and biobutanol, are suitable replacements for gasoline, while biodiesel can replace petroleum diesel. Improving biofuel engine performance requires understanding its fundamental combustion properties and the pathways of combustion. This study's contribution is experimentally validated chemical kinetic combustion mechanisms for biobutanol and biodiesel. Fundamental combustion data and chemical kinetic mechanisms are presented and discussed to improve our understanding of biofuel combustion. The net environmental impact of biobutanol (i.e., n-butanol) has not been studied extensively, so this study first assesses the sustainability of n-butanol derived from corn. The results indicate that technical advances in fuel production are required before commercializing biobutanol. The primary contribution of this research is new experimental data and a novel chemical kinetic mechanism for n-butanol combustion. The results indicate that under the given experimental conditions, n-butanol is consumed primarily via abstraction of hydrogen atoms to produce fuel radical molecules, which subsequently decompose to smaller hydrocarbon and oxygenated species. The hydroxyl moiety in n-butanol results in the direct production of the oxygenated species such as butanal, acetaldehyde, and formaldehyde. The formation of these compounds sequesters carbon from forming soot precursors, but they may introduce other adverse environmental and health effects. Biodiesel is a mixture of long chain fatty acid methyl esters derived from fats and oils. This research study presents high quality experimental data for one large fatty acid methyl ester, methyl decanoate, and models its combustion using an improved skeletal mechanism. The results indicate that methyl decanoate is consumed via abstraction of hydrogen atoms to produce fuel radicals, which ultimately lead to the production of alkenes. The ester moiety in methyl decanoate leads to the formation of low molecular

  14. Thermoluminescence of zircon: a kinetic model

    CERN Document Server

    Turkin, A A; Vainshtein, D I; Hartog, H W D

    2003-01-01

    The mineral zircon, ZrSiO sub 4 , belongs to a class of promising materials for geochronometry by means of thermoluminescence (TL) dating. The development of a reliable and reproducible method for TL dating with zircon requires detailed knowledge of the processes taking place during exposure to ionizing radiation, long-term storage, annealing at moderate temperatures and heating at a constant rate (TL measurements). To understand these processes one needs a kinetic model of TL. This paper is devoted to the construction of such a model. The goal is to study the qualitative behaviour of the system and to determine the parameters and processes controlling TL phenomena of zircon. The model considers the following processes: (i) Filling of electron and hole traps at the excitation stage as a function of the dose rate and the dose for both (low dose rate) natural and (high dose rate) laboratory irradiation. (ii) Time dependence of TL fading in samples irradiated under laboratory conditions. (iii) Short time anneali...

  15. Kinetic modelling of krypton fluoride laser systems

    Energy Technology Data Exchange (ETDEWEB)

    Jancaitis, K.S.

    1983-11-01

    A kinetic model has been developed for the KrF* rare gas halide laser system, specifically for electron-beam pumped mixtures of krypton, fluorine, and either helium or argon. The excitation produced in the laser gas by the e-beam was calculated numerically using an algorithm checked by comparing the predicted ionization yields in the pure rare gases with their experimental values. The excitation of the laser media by multi-kilovolt x-rays was also modeled and shown to be similar to that produced by high energy electrons. A system of equations describing the transfer of the initial gas excitation into the laser upper level was assembled using reaction rate constants from both experiment and theory. A one-dimensional treatment of the interaction of the laser radiation with the gas was formulated which considered spontaneous and stimulated emission and absorption. The predictions of this model were in good agreement with the fluorescence signals and gain and absorption measured experimentally.

  16. Shear-Driven Reconnection in Kinetic Models

    Science.gov (United States)

    Black, C.; Antiochos, S. K.; Germaschewski, K.; Karpen, J. T.; DeVore, C. R.; Bessho, N.

    2015-12-01

    The explosive energy release in solar eruptive phenomena is believed to be due to magnetic reconnection. In the standard model for coronal mass ejections (CME) and/or solar flares, the free energy for the event resides in the strongly sheared magnetic field of a filament channel. The pre-eruption force balance consists of an upward force due to the magnetic pressure of the sheared field countered by a downward tension due to overlying unsheared field. Magnetic reconnection disrupts this force balance; therefore, it is critical for understanding CME/flare initiation, to model the onset of reconnection driven by the build-up of magnetic shear. In MHD simulations, the application of a magnetic-field shear is a trivial matter. However, kinetic effects are dominant in the diffusion region and thus, it is important to examine this process with PIC simulations as well. The implementation of such a driver in PIC methods is challenging, however, and indicates the necessity of a true multiscale model for such processes in the solar environment. The field must be sheared self-consistently and indirectly to prevent the generation of waves that destroy the desired system. Plasma instabilities can arise nonetheless. In the work presented here, we show that we can control this instability and generate a predicted out-of-plane magnetic flux. This material is based upon work supported by the National Science Foundation under Award No. AGS-1331356.

  17. Reflected kinetics model for nuclear space reactor kinetics and control scoping calculations

    Energy Technology Data Exchange (ETDEWEB)

    Washington, K.E.

    1986-05-01

    The objective of this research is to develop a model that offers an alternative to the point kinetics (PK) modelling approach in the analysis of space reactor kinetics and control studies. Modelling effort will focus on the explicit treatment of control drums as reactivity input devices so that the transition to automatic control can be smoothly done. The proposed model is developed for the specific integration of automatic control and the solution of the servo mechanism problem. The integration of the kinetics model with an automatic controller will provide a useful tool for performing space reactor scoping studies for different designs and configurations. Such a tool should prove to be invaluable in the design phase of a space nuclear system from the point of view of kinetics and control limitations.

  18. Systematic planning of genome-scale experiments in poorly studied species.

    Science.gov (United States)

    Guan, Yuanfang; Dunham, Maitreya; Caudy, Amy; Troyanskaya, Olga

    2010-03-05

    Genome-scale datasets have been used extensively in model organisms to screen for specific candidates or to predict functions for uncharacterized genes. However, despite the availability of extensive knowledge in model organisms, the planning of genome-scale experiments in poorly studied species is still based on the intuition of experts or heuristic trials. We propose that computational and systematic approaches can be applied to drive the experiment planning process in poorly studied species based on available data and knowledge in closely related model organisms. In this paper, we suggest a computational strategy for recommending genome-scale experiments based on their capability to interrogate diverse biological processes to enable protein function assignment. To this end, we use the data-rich functional genomics compendium of the model organism to quantify the accuracy of each dataset in predicting each specific biological process and the overlap in such coverage between different datasets. Our approach uses an optimized combination of these quantifications to recommend an ordered list of experiments for accurately annotating most proteins in the poorly studied related organisms to most biological processes, as well as a set of experiments that target each specific biological process. The effectiveness of this experiment- planning system is demonstrated for two related yeast species: the model organism Saccharomyces cerevisiae and the comparatively poorly studied Saccharomyces bayanus. Our system recommended a set of S. bayanus experiments based on an S. cerevisiae microarray data compendium. In silico evaluations estimate that less than 10% of the experiments could achieve similar functional coverage to the whole microarray compendium. This estimation was confirmed by performing the recommended experiments in S. bayanus, therefore significantly reducing the labor devoted to characterize the poorly studied genome. This experiment-planning framework could

  19. Fully implicit kinetic modelling of collisional plasmas

    Energy Technology Data Exchange (ETDEWEB)

    Mousseau, V.A.

    1996-05-01

    This dissertation describes a numerical technique, Matrix-Free Newton Krylov, for solving a simplified Vlasov-Fokker-Planck equation. This method is both deterministic and fully implicit, and may not have been a viable option before current developments in numerical methods. Results are presented that indicate the efficiency of the Matrix-Free Newton Krylov method for these fully-coupled, nonlinear integro-differential equations. The use and requirement for advanced differencing is also shown. To this end, implementations of Chang-Cooper differencing and flux limited Quadratic Upstream Interpolation for Convective Kinematics (QUICK) are presented. Results are given for a fully kinetic ion-electron problem with a self consistent electric field calculated from the ion and electron distribution functions. This numerical method, including advanced differencing, provides accurate solutions, which quickly converge on workstation class machines. It is demonstrated that efficient steady-state solutions can be achieved to the non-linear integro-differential equation, obtaining quadratic convergence, without incurring the large memory requirements of an integral operator. Model problems are presented which simulate plasma impinging on a plate with both high and low neutral particle recycling typical of a divertor in a Tokamak device. These model problems demonstrate the performance of the new solution method.

  20. Kinetic modeling in pre-clinical positron emission tomography

    Energy Technology Data Exchange (ETDEWEB)

    Kuntner, Claudia [AIT Austrian Institute of Technology GmbH, Seibersdorf (Austria). Biomedical Systems, Health and Environment Dept.

    2014-07-01

    Pre-clinical positron emission tomography (PET) has evolved in the last few years from pure visualization of radiotracer uptake and distribution towards quantification of the physiological parameters. For reliable and reproducible quantification the kinetic modeling methods used to obtain relevant parameters of radiotracer tissue interaction are important. Here we present different kinetic modeling techniques with a focus on compartmental models including plasma input models and reference tissue input models. The experimental challenges of deriving the plasma input function in rodents and the effect of anesthesia are discussed. Finally, in vivo application of kinetic modeling in various areas of pre-clinical research is presented and compared to human data.

  1. Genome-scale reconstruction of metabolic networks of Lactobacillus casei ATCC 334 and 12A.

    Directory of Open Access Journals (Sweden)

    Elena Vinay-Lara

    Full Text Available Lactobacillus casei strains are widely used in industry and the utility of this organism in these industrial applications is strain dependent. Hence, tools capable of predicting strain specific phenotypes would have utility in the selection of strains for specific industrial processes. Genome-scale metabolic models can be utilized to better understand genotype-phenotype relationships and to compare different organisms. To assist in the selection and development of strains with enhanced industrial utility, genome-scale models for L. casei ATCC 334, a well characterized strain, and strain 12A, a corn silage isolate, were constructed. Draft models were generated from RAST genome annotations using the Model SEED database and refined by evaluating ATP generating cycles, mass-and-charge-balances of reactions, and growth phenotypes. After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors. We conclude that the metabolic capabilities of the two networks are highly similar. The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes. The developed L. casei ATCC 334 and 12A metabolic models will enable better understanding of the physiology of these organisms and be valuable tools in the development and selection of strains with enhanced utility in a variety of industrial applications.

  2. A Review of Kinetic Modeling Methodologies for Complex Processes

    Directory of Open Access Journals (Sweden)

    de Oliveira Luís P.

    2016-05-01

    Full Text Available In this paper, kinetic modeling techniques for complex chemical processes are reviewed. After a brief historical overview of chemical kinetics, an overview is given of the theoretical background of kinetic modeling of elementary steps and of multistep reactions. Classic lumping techniques are introduced and analyzed. Two examples of lumped kinetic models (atmospheric gasoil hydrotreating and residue hydroprocessing developed at IFP Energies nouvelles (IFPEN are presented. The largest part of this review describes advanced kinetic modeling strategies, in which the molecular detail is retained, i.e. the reactions are represented between molecules or even subdivided into elementary steps. To be able to retain this molecular level throughout the kinetic model and the reactor simulations, several hurdles have to be cleared first: (i the feedstock needs to be described in terms of molecules, (ii large reaction networks need to be automatically generated, and (iii a large number of rate equations with their rate parameters need to be derived. For these three obstacles, molecular reconstruction techniques, deterministic or stochastic network generation programs, and single-event micro-kinetics and/or linear free energy relationships have been applied at IFPEN, as illustrated by several examples of kinetic models for industrial refining processes.

  3. SATL MODEL LESSON IN CHEMICAL KINETICS

    African Journals Online (AJOL)

    Preferred Customer

    Department of Chemistry, The Federal Urdu University of Arts, Science and ... are several strategies, through which teaching and learning of scientific subjects in ... the linear relationships among various factors involved in chemical kinetics.

  4. Innovative first order elimination kinetics working model for easy learning

    Directory of Open Access Journals (Sweden)

    Navin Budania

    2016-06-01

    Conclusions: First order elimination kinetics is easily understood with the help of above working model. More and more working models could be developed for teaching difficult topics. [Int J Basic Clin Pharmacol 2016; 5(3.000: 862-864

  5. MODELLING OF BACTERIAL SULPHATE REDUCTION IN ANAEROBIC PONDS : KINETIC INVESTIGATIONS

    OpenAIRE

    Harerimana, Casimir; Vasel, Jean-Luc; Jupsin, Hugues; Ouali, Amira

    2011-01-01

    The aim of the study was first to develop a simple and practical model of anaerobic digestion including sulphate-reduction in anaerobic ponds. The basic microbiology of our model consists of three steps, namely, acidogenesis, methanogenesis, and sulphate reduction. This model includes multiple reaction stoichiometry and substrate utilization kinetics. The second aim was to determine some kinetic parameters associated with this model. The values of these parameters for sulfidogenic bacteria ar...

  6. A kinetic model for the penicillin biosynthetic pathway in

    DEFF Research Database (Denmark)

    Nielsen, Jens; Jørgensen, Henrik

    1996-01-01

    A kinetic model for the first two steps in the penicillin biosynthetic pathway, i.e. the ACV synthetase (ACVS) and the isopenicillin N synthetase (IPNS) is proposed. The model is based on Michaelis-Menten type kinetics with non-competitive inhibition of the ACVS by ACV, and competitive inhibition...... of the IPNS by glutathione. The model predicted flux through the pathway corresponds well with the measured rate of penicillin biosynthesis. From the kinetic model the elasticity coefficients and the flux control coefficients are calculated throughout a fed-batch cultivation, and it is found...

  7. Genome Scale Transcriptomics of Baculovirus-Insect Interactions

    Directory of Open Access Journals (Sweden)

    Steven Reid

    2013-11-01

    Full Text Available Baculovirus-insect cell technologies are applied in the production of complex proteins, veterinary and human vaccines, gene delivery vectors‚ and biopesticides. Better understanding of how baculoviruses and insect cells interact would facilitate baculovirus-based production. While complete genomic sequences are available for over 58 baculovirus species, little insect genomic information is known. The release of the Bombyx mori and Plutella xylostella genomes, the accumulation of EST sequences for several Lepidopteran species, and especially the availability of two genome-scale analysis tools, namely oligonucleotide microarrays and next generation sequencing (NGS, have facilitated expression studies to generate a rich picture of insect gene responses to baculovirus infections. This review presents current knowledge on the interaction dynamics of the baculovirus-insect system‚ which is relatively well studied in relation to nucleocapsid transportation, apoptosis, and heat shock responses, but is still poorly understood regarding responses involved in pro-survival pathways, DNA damage pathways, protein degradation, translation, signaling pathways, RNAi pathways, and importantly metabolic pathways for energy, nucleotide and amino acid production. We discuss how the two genome-scale transcriptomic tools can be applied for studying such pathways and suggest that proteomics and metabolomics can produce complementary findings to transcriptomic studies.

  8. Genome scale transcriptomics of baculovirus-insect interactions.

    Science.gov (United States)

    Nguyen, Quan; Nielsen, Lars K; Reid, Steven

    2013-11-12

    Baculovirus-insect cell technologies are applied in the production of complex proteins, veterinary and human vaccines, gene delivery vectors' and biopesticides. Better understanding of how baculoviruses and insect cells interact would facilitate baculovirus-based production. While complete genomic sequences are available for over 58 baculovirus species, little insect genomic information is known. The release of the Bombyx mori and Plutella xylostella genomes, the accumulation of EST sequences for several Lepidopteran species, and especially the availability of two genome-scale analysis tools, namely oligonucleotide microarrays and next generation sequencing (NGS), have facilitated expression studies to generate a rich picture of insect gene responses to baculovirus infections. This review presents current knowledge on the interaction dynamics of the baculovirus-insect system' which is relatively well studied in relation to nucleocapsid transportation, apoptosis, and heat shock responses, but is still poorly understood regarding responses involved in pro-survival pathways, DNA damage pathways, protein degradation, translation, signaling pathways, RNAi pathways, and importantly metabolic pathways for energy, nucleotide and amino acid production. We discuss how the two genome-scale transcriptomic tools can be applied for studying such pathways and suggest that proteomics and metabolomics can produce complementary findings to transcriptomic studies.

  9. Comparative Genome-Scale Reconstruction of Gapless Metabolic Networks for Present and Ancestral Species

    Science.gov (United States)

    Pitkänen, Esa; Jouhten, Paula; Hou, Jian; Syed, Muhammad Fahad; Blomberg, Peter; Kludas, Jana; Oja, Merja; Holm, Liisa; Penttilä, Merja; Rousu, Juho; Arvas, Mikko

    2014-01-01

    We introduce a novel computational approach, CoReCo, for comparative metabolic reconstruction and provide genome-scale metabolic network models for 49 important fungal species. Leveraging on the exponential growth in sequenced genome availability, our method reconstructs genome-scale gapless metabolic networks simultaneously for a large number of species by integrating sequence data in a probabilistic framework. High reconstruction accuracy is demonstrated by comparisons to the well-curated Saccharomyces cerevisiae consensus model and large-scale knock-out experiments. Our comparative approach is particularly useful in scenarios where the quality of available sequence data is lacking, and when reconstructing evolutionary distant species. Moreover, the reconstructed networks are fully carbon mapped, allowing their use in 13C flux analysis. We demonstrate the functionality and usability of the reconstructed fungal models with computational steady-state biomass production experiment, as these fungi include some of the most important production organisms in industrial biotechnology. In contrast to many existing reconstruction techniques, only minimal manual effort is required before the reconstructed models are usable in flux balance experiments. CoReCo is available at http://esaskar.github.io/CoReCo/. PMID:24516375

  10. Comparative genome-scale reconstruction of gapless metabolic networks for present and ancestral species.

    Directory of Open Access Journals (Sweden)

    Esa Pitkänen

    2014-02-01

    Full Text Available We introduce a novel computational approach, CoReCo, for comparative metabolic reconstruction and provide genome-scale metabolic network models for 49 important fungal species. Leveraging on the exponential growth in sequenced genome availability, our method reconstructs genome-scale gapless metabolic networks simultaneously for a large number of species by integrating sequence data in a probabilistic framework. High reconstruction accuracy is demonstrated by comparisons to the well-curated Saccharomyces cerevisiae consensus model and large-scale knock-out experiments. Our comparative approach is particularly useful in scenarios where the quality of available sequence data is lacking, and when reconstructing evolutionary distant species. Moreover, the reconstructed networks are fully carbon mapped, allowing their use in 13C flux analysis. We demonstrate the functionality and usability of the reconstructed fungal models with computational steady-state biomass production experiment, as these fungi include some of the most important production organisms in industrial biotechnology. In contrast to many existing reconstruction techniques, only minimal manual effort is required before the reconstructed models are usable in flux balance experiments. CoReCo is available at http://esaskar.github.io/CoReCo/.

  11. Kinetic models in spin chemistry. 1. The hyperfine interaction

    DEFF Research Database (Denmark)

    Mojaza, M.; Pedersen, J. B.

    2012-01-01

    Kinetic models for quantum systems are quite popular due to their simplicity, although they are difficult to justify. We show that the transformation from quantum to kinetic description can be done exactly for the hyperfine interaction of one nuclei with arbitrary spin; more spins are described w...

  12. Modeling the kinetics of essential oil hydrodistillation from plant materials

    Directory of Open Access Journals (Sweden)

    Milojević Svetomir Ž.

    2013-01-01

    Full Text Available The present work deals with modeling the kinetics of essential oils extraction from plant materials by water and steam distillation. The experimental data were obtained by studying the hydrodistillation kinetics of essential oil from juniper berries. The literature data on the kinetics of essential oils hydrodistillation from different plant materials were also included into the modeling. A physical model based on simultaneous washing and diffusion of essential oil from plant materials were developed to describe the kinetics of essential oils hydrodistillation, and two other simpler models were derived from this physical model assuming either instantaneous washing followed by diffusion or diffusion with no washing (i.e. the first-order kinetics. The main goal was to compare these models and suggest the optimum ones for water and steam distillation and for different plant materials. All three models described well the experimental kinetic data on water distillation irrespective of the type of distillation equipment and its scale, the type of plant materials and the operational conditions. The most applicable one is the model involving simultaneous washing and diffusion of the essential oil. However, this model was generally inapplicable for steam distillation of essential oils, except for juniper berries. For this hydrodistillation technique, the pseudo first-order model was shown to be the best one. In a few cases, a variation of the essential oil yield with time was observed to be sigmoidal and was modeled by the Boltzmann sigmoid function.

  13. Aromatization of light naphtha fractions on zeolites 1: Kinetic model

    Directory of Open Access Journals (Sweden)

    Rovenskaja Svetlana A.

    2003-01-01

    Full Text Available On the basis of analyzing kinetic experimental data performed in laboratory integral reactors a lumping kinetic model of the "Zeoforming" process was developed. A reaction scheme of the lumped components was proposed, that was adapted to the technological requirements. The reaction rate constants and activation energies were estimated, that are valid for certain feed compositions. The model is intended for further modeling and optimization of the process.

  14. Kinetic derivation of a Hamilton-Jacobi traffic flow model

    CERN Document Server

    Borsche, Raul; Kimathi, Mark

    2012-01-01

    Kinetic models for vehicular traffic are reviewed and considered from the point of view of deriving macroscopic equations. A derivation of the associated macroscopic traffic flow equations leads to different types of equations: in certain situations modified Aw-Rascle equations are obtained. On the other hand, for several choices of kinetic parameters new Hamilton-Jacobi type traffic equations are found. Associated microscopic models are discussed and numerical experiments are presented discussing several situations for highway traffic and comparing the different models.

  15. An experimentally-supported genome-scale metabolic network reconstruction for Yersinia pestis CO92

    Directory of Open Access Journals (Sweden)

    Motin Vladimir L

    2011-10-01

    Full Text Available Abstract Background Yersinia pestis is a gram-negative bacterium that causes plague, a disease linked historically to the Black Death in Europe during the Middle Ages and to several outbreaks during the modern era. Metabolism in Y. pestis displays remarkable flexibility and robustness, allowing the bacterium to proliferate in both warm-blooded mammalian hosts and cold-blooded insect vectors such as fleas. Results Here we report a genome-scale reconstruction and mathematical model of metabolism for Y. pestis CO92 and supporting experimental growth and metabolite measurements. The model contains 815 genes, 678 proteins, 963 unique metabolites and 1678 reactions, accurately simulates growth on a range of carbon sources both qualitatively and quantitatively, and identifies gaps in several key biosynthetic pathways and suggests how those gaps might be filled. Furthermore, our model presents hypotheses to explain certain known nutritional requirements characteristic of this strain. Conclusions Y. pestis continues to be a dangerous threat to human health during modern times. The Y. pestis genome-scale metabolic reconstruction presented here, which has been benchmarked against experimental data and correctly reproduces known phenotypes, provides an in silico platform with which to investigate the metabolism of this important human pathogen.

  16. An Experimentally-Supported Genome-Scale Metabolic Network Reconstruction for Yersinia pestis CO92

    Energy Technology Data Exchange (ETDEWEB)

    Charusanti, Pep; Chauhan, Sadhana; Mcateer, Kathleen; Lerman, Joshua A.; Hyduke, Daniel R.; Motin, Vladimir L.; Ansong, Charles; Adkins, Joshua N.; Palsson, Bernhard O.

    2011-10-13

    Yersinia pestis is a gram-negative bacterium that causes plague, a disease linked historically to the Black Death in Europe during the Middle Ages and to several outbreaks during the modern era. Metabolism in Y. pestis displays remarkable flexibility and robustness, allowing the bacterium to proliferate in both warm-blooded mammalian hosts and cold-blooded insect vectors such as fleas. Here we report a genome-scale reconstruction and mathematical model of metabolism for Y. pestis CO92 and supporting experimental growth and metabolite measurements. The model contains 815 genes, 678 proteins, 963 unique metabolites and 1678 reactions, accurately simulates growth on a range of carbon sources both qualitatively and quantitatively, and identifies gaps in several key biosynthetic pathways and suggests how those gaps might be filled. Furthermore, our model presents hypotheses to explain certain known nutritional requirements characteristic of this strain. Y. pestis continues to be a dangerous threat to human health during modern times. The Y. pestis genome-scale metabolic reconstruction presented here, which has been benchmarked against experimental data and correctly reproduces known phenotypes, thus provides an in silico platform with which to investigate the metabolism of this important human pathogen.

  17. Lumping procedure for a kinetic model of catalytic naphtha reforming

    Directory of Open Access Journals (Sweden)

    H. M. Arani

    2009-12-01

    Full Text Available A lumping procedure is developed for obtaining kinetic and thermodynamic parameters of catalytic naphtha reforming. All kinetic and deactivation parameters are estimated from industrial data and thermodynamic parameters are calculated from derived mathematical expressions. The proposed model contains 17 lumps that include the C6 to C8+ hydrocarbon range and 15 reaction pathways. Hougen-Watson Langmuir-Hinshelwood type reaction rate expressions are used for kinetic simulation of catalytic reactions. The kinetic parameters are benchmarked with several sets of plant data and estimated by the SQP optimization method. After calculation of deactivation and kinetic parameters, plant data are compared with model predictions and only minor deviations between experimental and calculated data are generally observed.

  18. Genome-scale metabolic flux analysis of Streptomyces lividans growing on a complex medium.

    Science.gov (United States)

    D'Huys, Pieter-Jan; Lule, Ivan; Vercammen, Dominique; Anné, Jozef; Van Impe, Jan F; Bernaerts, Kristel

    2012-09-15

    Constraint-based metabolic modeling comprises various excellent tools to assess experimentally observed phenotypic behavior of micro-organisms in terms of intracellular metabolic fluxes. In combination with genome-scale metabolic networks, micro-organisms can be investigated in much more detail and under more complex environmental conditions. Although complex media are ubiquitously applied in industrial fermentations and are often a prerequisite for high protein secretion yields, such multi-component conditions are seldom investigated using genome-scale flux analysis. In this paper, a systematic and integrative approach is presented to determine metabolic fluxes in Streptomyces lividans TK24 grown on a nutritious and complex medium. Genome-scale flux balance analysis and randomized sampling of the solution space are combined to extract maximum information from exometabolome profiles. It is shown that biomass maximization cannot predict the observed metabolite production pattern as such. Although this cellular objective commonly applies to batch fermentation data, both input and output constraints are required to reproduce the measured biomass production rate. Rich media hence not necessarily lead to maximum biomass growth. To eventually identify a unique intracellular flux vector, a hierarchical optimization of cellular objectives is adopted. Out of various tested secondary objectives, maximization of the ATP yield per flux unit returns the closest agreement with the maximum frequency in flux histograms. This unique flux estimation is hence considered as a reasonable approximation for the biological fluxes. Flux maps for different growth phases show no active oxidative part of the pentose phosphate pathway, but NADPH generation in the TCA cycle and NADPH transdehydrogenase activity are most important in fulfilling the NADPH balance. Amino acids contribute to biomass growth by augmenting the pool of available amino acids and by boosting the TCA cycle, particularly

  19. Modelling atypical CYP3A4 kinetics: principles and pragmatism.

    Science.gov (United States)

    Houston, J Brian; Galetin, Aleksandra

    2005-01-15

    The Michaelis-Menten model, and the existence of a single active site for the interaction of substrate with drug metabolizing enzyme, adequately describes a substantial number of in vitro metabolite kinetic data sets for both clearance and inhibition determination. However, in an increasing number of cases (involving most notably, but not exclusively, CYP3A4), atypical kinetic features are observed, e.g., auto- and heteroactivation; partial, cooperative, and substrate inhibition; concentration-dependent effector responses (activation/inhibition); limited substrate substitution and inhibitory reciprocity necessitating sub-group classification. The phenomena listed above cannot be readily interpreted using single active site models and the literature indicates that three types of approaches have been adopted. First the 'nai ve' approach of using the Michaelis-Menten model regardless of the kinetic behaviour, second the 'empirical' approach (e.g., employing the Hill or uncompetitive inhibition equations to model homotropic phenomena of sigmoidicity and substrate inhibition, respectively) and finally, the 'mechanistic' approach. The later includes multisite kinetic models derived using the same rapid equilibrium/steady-state assumptions as the single-site model. These models indicate that 2 or 3 binding sites exist for a given CYP3A4 substrate and/or effector. Multisite kinetic models share common features, depending on the substrate kinetics and the nature of the effector response observed in vitro, which allow a generic model to be proposed. Thus although more complex than the other two approaches, they show more utility and can be comprehensively applied in relatively simple versions that can be readily generated from generic model. Multisite kinetic features, observed in isolated hepatocytes as well as in microsomes from hepatic tissue and heterologous expression systems, may be evident in substrate depletion-time profiles as well as in metabolite formation rates

  20. Modeling Biodegradation Kinetics on Benzene and Toluene and Their Mixture

    Directory of Open Access Journals (Sweden)

    Aparecido N. Módenes

    2007-10-01

    Full Text Available The objective of this work was to model the biodegradation kinetics of toxic compounds toluene and benzene as pure substrates and in a mixture. As a control, Monod and Andrews models were used. To predict substrates interactions, more sophisticated models of inhibition and competition, and SKIP (sum kinetics interactions parameters model were applied. The models evaluation was performed based on the experimental data from Pseudomonas putida F1 activities published in the literature. In parameter identification procedure, the global method of particle swarm optimization (PSO was applied. The simulation results show that the better description of the biodegradation process of pure toxic substrate can be achieved by Andrews' model. The biodegradation process of a mixture of toxic substrates is modeled the best when modified competitive inhibition and SKIP models are used. The developed software can be used as a toolbox of a kinetics model catalogue of industrial wastewater treatment for process design and optimization.

  1. Biomass torrefaction: modeling of volatile and solid product evolution kinetics.

    Science.gov (United States)

    Bates, Richard B; Ghoniem, Ahmed F

    2012-11-01

    The aim of this work is the development of a kinetics model for the evolution of the volatile and solid product composition during torrefaction conditions between 200 and 300°C. Coupled to an existing two step solid mass loss kinetics mechanism, this model describes the volatile release kinetics in terms of a set of identifiable chemical components, permitting the solid product composition to be estimated by mass conservation. Results show that most of the volatiles released during the first stage include highly oxygenated species such as water, acetic acid, and carbon dioxide, while volatiles released during the second step are composed primarily of lactic acid, methanol, and acetic acid. This kinetics model will be used in the development of a model to describe reaction energy balance and heat release dynamics.

  2. Kinetic, equilibrium and thermodynamic modelling of the sorption of ...

    African Journals Online (AJOL)

    Kinetic, equilibrium and thermodynamic modelling of the sorption of metals ... Batch sorption studies were conducted to assess the potential of a ... negative Ea values, indicating their preference to bind to low-energy sites. ... Article Metrics.

  3. Jellium-with-gap model applied to semilocal kinetic functionals

    Science.gov (United States)

    Constantin, Lucian A.; Fabiano, Eduardo; Śmiga, Szymon; Della Sala, Fabio

    2017-03-01

    We investigate a highly nonlocal generalization of the Lindhard function, given by the jellium-with-gap model. We find a band-gap-dependent gradient expansion of the kinetic energy, which performs noticeably well for large atoms. Using the static linear response theory and the simplest semilocal model for the local band gap, we derive a nonempirical generalized gradient approximation (GGA) of the kinetic energy. This GGA kinetic-energy functional is remarkably accurate for the description of weakly interacting molecular systems within the subsystem formulation of density functional theory.

  4. Kinetic models in industrial biotechnology - Improving cell factory performance.

    Science.gov (United States)

    Almquist, Joachim; Cvijovic, Marija; Hatzimanikatis, Vassily; Nielsen, Jens; Jirstrand, Mats

    2014-07-01

    An increasing number of industrial bioprocesses capitalize on living cells by using them as cell factories that convert sugars into chemicals. These processes range from the production of bulk chemicals in yeasts and bacteria to the synthesis of therapeutic proteins in mammalian cell lines. One of the tools in the continuous search for improved performance of such production systems is the development and application of mathematical models. To be of value for industrial biotechnology, mathematical models should be able to assist in the rational design of cell factory properties or in the production processes in which they are utilized. Kinetic models are particularly suitable towards this end because they are capable of representing the complex biochemistry of cells in a more complete way compared to most other types of models. They can, at least in principle, be used to in detail understand, predict, and evaluate the effects of adding, removing, or modifying molecular components of a cell factory and for supporting the design of the bioreactor or fermentation process. However, several challenges still remain before kinetic modeling will reach the degree of maturity required for routine application in industry. Here we review the current status of kinetic cell factory modeling. Emphasis is on modeling methodology concepts, including model network structure, kinetic rate expressions, parameter estimation, optimization methods, identifiability analysis, model reduction, and model validation, but several applications of kinetic models for the improvement of cell factories are also discussed.

  5. An integral representation of functions in gas-kinetic models

    Science.gov (United States)

    Perepelitsa, Misha

    2016-08-01

    Motivated by the theory of kinetic models in gas dynamics, we obtain an integral representation of lower semicontinuous functions on {{{R}}^d,} {d≥1}. We use the representation to study the problem of compactness of a family of the solutions of the discrete time BGK model for the compressible Euler equations. We determine sufficient conditions for strong compactness of moments of kinetic densities, in terms of the measures from their integral representations.

  6. Genome-scale engineering for systems and synthetic biology

    Science.gov (United States)

    Esvelt, Kevin M; Wang, Harris H

    2013-01-01

    Genome-modification technologies enable the rational engineering and perturbation of biological systems. Historically, these methods have been limited to gene insertions or mutations at random or at a few pre-defined locations across the genome. The handful of methods capable of targeted gene editing suffered from low efficiencies, significant labor costs, or both. Recent advances have dramatically expanded our ability to engineer cells in a directed and combinatorial manner. Here, we review current technologies and methodologies for genome-scale engineering, discuss the prospects for extending efficient genome modification to new hosts, and explore the implications of continued advances toward the development of flexibly programmable chasses, novel biochemistries, and safer organismal and ecological engineering. PMID:23340847

  7. Genome-scale engineering for systems and synthetic biology.

    Science.gov (United States)

    Esvelt, Kevin M; Wang, Harris H

    2013-01-01

    Genome-modification technologies enable the rational engineering and perturbation of biological systems. Historically, these methods have been limited to gene insertions or mutations at random or at a few pre-defined locations across the genome. The handful of methods capable of targeted gene editing suffered from low efficiencies, significant labor costs, or both. Recent advances have dramatically expanded our ability to engineer cells in a directed and combinatorial manner. Here, we review current technologies and methodologies for genome-scale engineering, discuss the prospects for extending efficient genome modification to new hosts, and explore the implications of continued advances toward the development of flexibly programmable chasses, novel biochemistries, and safer organismal and ecological engineering.

  8. Genome-scale validation of deep-sequencing libraries.

    Directory of Open Access Journals (Sweden)

    Dominic Schmidt

    Full Text Available Chromatin immunoprecipitation followed by high-throughput (HTP sequencing (ChIP-seq is a powerful tool to establish protein-DNA interactions genome-wide. The primary limitation of its broad application at present is the often-limited access to sequencers. Here we report a protocol, Mab-seq, that generates genome-scale quality evaluations for nucleic acid libraries intended for deep-sequencing. We show how commercially available genomic microarrays can be used to maximize the efficiency of library creation and quickly generate reliable preliminary data on a chromosomal scale in advance of deep sequencing. We also exploit this technique to compare enriched regions identified using microarrays with those identified by sequencing, demonstrating that they agree on a core set of clearly identified enriched regions, while characterizing the additional enriched regions identifiable using HTP sequencing.

  9. Kinetic Modelling of Pesticidal Degradation and Microbial Growth in Soil

    Institute of Scientific and Technical Information of China (English)

    LIUDUO-SEN; WANGZONG-SHENG; 等

    1994-01-01

    This paper discusses such models for the degradation kinetics of pesticides in soil as the model expressing the degradation rate as a function of two varables:the pesticide concentration and the number of pesticide degrading microorganisms,the model expressing the pesticide concentration as explicit or implicit function of time ,and the model exprssing the pesticide loss rate constants as functions of temperature,These models may interpret the degradation curves with an inflection point.A Kinetic model describing the growth processes of microbial populations in a closed system is reported as well.

  10. New mass loss kinetic model for thermal decomposition of biomass

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Based on non-isothermal experimental results for eight Chinese biomass species, a new kinetic model,named as the "pseudo bi-component separate-stage model (PBSM)", is developed in this note to describe the mass loss behavior of biomass thermal decomposition. This model gains an advantage over the commonly used "pseudo single-component overall model (PSOM)" and "pseudo multi-component overall model (PMOM)". By means of integral analysis it is indicated that the new model is suitable to describe the mass loss kinetics of wood and leaf samples under relatively low heating rates (e.g. 10°C/rin, used in this work).``

  11. Detailed Chemical Kinetic Modeling of Cyclohexane Oxidation

    Energy Technology Data Exchange (ETDEWEB)

    Silke, E J; Pitz, W J; Westbrook, C K; Ribaucour, M

    2006-11-10

    A detailed chemical kinetic mechanism has been developed and used to study the oxidation of cyclohexane at both low and high temperatures. Reaction rate constant rules are developed for the low temperature combustion of cyclohexane. These rules can be used for in chemical kinetic mechanisms for other cycloalkanes. Since cyclohexane produces only one type of cyclohexyl radical, much of the low temperature chemistry of cyclohexane is described in terms of one potential energy diagram showing the reaction of cyclohexyl radical + O{sub 2} through five, six and seven membered ring transition states. The direct elimination of cyclohexene and HO{sub 2} from RO{sub 2} is included in the treatment using a modified rate constant of Cavallotti et al. Published and unpublished data from the Lille rapid compression machine, as well as jet-stirred reactor data are used to validate the mechanism. The effect of heat loss is included in the simulations, an improvement on previous studies on cyclohexane. Calculations indicated that the production of 1,2-epoxycyclohexane observed in the experiments can not be simulated based on the current understanding of low temperature chemistry. Possible 'alternative' H-atom isomerizations leading to different products from the parent O{sub 2}QOOH radical were included in the low temperature chemical kinetic mechanism and were found to play a significant role.

  12. A mixed-integer linear programming approach to the reduction of genome-scale metabolic networks.

    Science.gov (United States)

    Röhl, Annika; Bockmayr, Alexander

    2017-01-03

    Constraint-based analysis has become a widely used method to study metabolic networks. While some of the associated algorithms can be applied to genome-scale network reconstructions with several thousands of reactions, others are limited to small or medium-sized models. In 2015, Erdrich et al. introduced a method called NetworkReducer, which reduces large metabolic networks to smaller subnetworks, while preserving a set of biological requirements that can be specified by the user. Already in 2001, Burgard et al. developed a mixed-integer linear programming (MILP) approach for computing minimal reaction sets under a given growth requirement. Here we present an MILP approach for computing minimum subnetworks with the given properties. The minimality (with respect to the number of active reactions) is not guaranteed by NetworkReducer, while the method by Burgard et al. does not allow specifying the different biological requirements. Our procedure is about 5-10 times faster than NetworkReducer and can enumerate all minimum subnetworks in case there exist several ones. This allows identifying common reactions that are present in all subnetworks, and reactions appearing in alternative pathways. Applying complex analysis methods to genome-scale metabolic networks is often not possible in practice. Thus it may become necessary to reduce the size of the network while keeping important functionalities. We propose a MILP solution to this problem. Compared to previous work, our approach is more efficient and allows computing not only one, but even all minimum subnetworks satisfying the required properties.

  13. Kinetic modelling of the Fischer-Tropsch synthesis

    Energy Technology Data Exchange (ETDEWEB)

    Gambaro, C.; Pollesel, P.; Zennaro, R. [Eni S.p.A., San Donato Milanese (Italy); Lietti, L.; Tronconi, E. [Politecnico di Milano (Italy)

    2006-07-01

    In this work the development of a CO conversion kinetic model of the Fischer-Tropsch process will be presented. Kinetic data were produced testing a Co-based catalyst on two lab units, equipped with a slurry autoclave and a fixed bed reactor respectively. Accordingly, information on the catalytic performances of the same catalyst in two reactor configurations were also obtained. The experimental results were then analyzed with different kinetic models, available in the literature: two mechanistic models, derived by Sarup-Wojciechowski and Yates-Satterfield, and a simple power law rate expression were compared. The parameters of the different rate expressions were estimated by non-linear regression of the kinetic data collected on the two lab units. (orig.)

  14. Modelling of the Kinetics of Sulfure Compounds in Desulfurisation Processes Based on Industry Data of Plant

    Directory of Open Access Journals (Sweden)

    Krivtcova Nadezhda

    2016-01-01

    Full Text Available Modelling of sulfur compounds kinetics was performed, including kinetics of benzothiophene and dibenzothiophene homologues. Modelling is based on experimental data obtained from monitoring of industrial hydrotreating set. Obtained results include kinetic parameters of reactions.

  15. Chemical Kinetic Models for HCCI and Diesel Combustion

    Energy Technology Data Exchange (ETDEWEB)

    Pitz, W J; Westbrook, C K; Mehl, M; Sarathy, S M

    2010-11-15

    Predictive engine simulation models are needed to make rapid progress towards DOE's goals of increasing combustion engine efficiency and reducing pollutant emissions. These engine simulation models require chemical kinetic submodels to allow the prediction of the effect of fuel composition on engine performance and emissions. Chemical kinetic models for conventional and next-generation transportation fuels need to be developed so that engine simulation tools can predict fuel effects. The objectives are to: (1) Develop detailed chemical kinetic models for fuel components used in surrogate fuels for diesel and HCCI engines; (2) Develop surrogate fuel models to represent real fuels and model low temperature combustion strategies in HCCI and diesel engines that lead to low emissions and high efficiency; and (3) Characterize the role of fuel composition on low temperature combustion modes of advanced combustion engines.

  16. Hybrid fluid/kinetic model for parallel heat conduction

    Energy Technology Data Exchange (ETDEWEB)

    Callen, J.D.; Hegna, C.C.; Held, E.D. [Univ. of Wisconsin, Madison, WI (United States)

    1998-12-31

    It is argued that in order to use fluid-like equations to model low frequency ({omega} < {nu}) phenomena such as neoclassical tearing modes in low collisionality ({nu} < {omega}{sub b}) tokamak plasmas, a Chapman-Enskog-like approach is most appropriate for developing an equation for the kinetic distortion (F) of the distribution function whose velocity-space moments lead to the needed fluid moment closure relations. Further, parallel heat conduction in a long collision mean free path regime can be described through a combination of a reduced phase space Chapman-Enskog-like approach for the kinetics and a multiple-time-scale analysis for the fluid and kinetic equations.

  17. Phase-field Model for Interstitial Loop Growth Kinetics and Thermodynamic and Kinetic Models of Irradiated Fe-Cr Alloys

    Energy Technology Data Exchange (ETDEWEB)

    Li, Yulan; Hu, Shenyang Y.; Sun, Xin; Khaleel, Mohammad A.

    2011-06-15

    Microstructure evolution kinetics in irradiated materials has strongly spatial correlation. For example, void and second phases prefer to nucleate and grow at pre-existing defects such as dislocations, grain boundaries, and cracks. Inhomogeneous microstructure evolution results in inhomogeneity of microstructure and thermo-mechanical properties. Therefore, the simulation capability for predicting three dimensional (3-D) microstructure evolution kinetics and its subsequent impact on material properties and performance is crucial for scientific design of advanced nuclear materials and optimal operation conditions in order to reduce uncertainty in operational and safety margins. Very recently the meso-scale phase-field (PF) method has been used to predict gas bubble evolution, void swelling, void lattice formation and void migration in irradiated materials,. Although most results of phase-field simulations are qualitative due to the lake of accurate thermodynamic and kinetic properties of defects, possible missing of important kinetic properties and processes, and the capability of current codes and computers for large time and length scale modeling, the simulations demonstrate that PF method is a promising simulation tool for predicting 3-D heterogeneous microstructure and property evolution, and providing microstructure evolution kinetics for higher scale level simulations of microstructure and property evolution such as mean field methods. This report consists of two parts. In part I, we will present a new phase-field model for predicting interstitial loop growth kinetics in irradiated materials. The effect of defect (vacancy/interstitial) generation, diffusion and recombination, sink strength, long-range elastic interaction, inhomogeneous and anisotropic mobility on microstructure evolution kinetics is taken into account in the model. The model is used to study the effect of elastic interaction on interstitial loop growth kinetics, the interstitial flux, and sink

  18. Hindered rotor models with variable kinetic functions for accurate thermodynamic and kinetic predictions

    Science.gov (United States)

    Reinisch, Guillaume; Leyssale, Jean-Marc; Vignoles, Gérard L.

    2010-10-01

    We present an extension of some popular hindered rotor (HR) models, namely, the one-dimensional HR (1DHR) and the degenerated two-dimensional HR (d2DHR) models, allowing for a simple and accurate treatment of internal rotations. This extension, based on the use of a variable kinetic function in the Hamiltonian instead of a constant reduced moment of inertia, is extremely suitable in the case of rocking/wagging motions involved in dissociation or atom transfer reactions. The variable kinetic function is first introduced in the framework of a classical 1DHR model. Then, an effective temperature and potential dependent constant is proposed in the cases of quantum 1DHR and classical d2DHR models. These methods are finally applied to the atom transfer reaction SiCl3+BCl3→SiCl4+BCl2. We show, for this particular case, that a proper accounting of internal rotations greatly improves the accuracy of thermodynamic and kinetic predictions. Moreover, our results confirm (i) that using a suitably defined kinetic function appears to be very adapted to such problems; (ii) that the separability assumption of independent rotations seems justified; and (iii) that a quantum mechanical treatment is not a substantial improvement with respect to a classical one.

  19. Genome-scale metabolic models: reconstruction and analysis

    NARCIS (Netherlands)

    Baart, G.J.; Martens, D.E.

    2012-01-01

    Metabolism can be defined as the complete set of chemical reactions that occur in living organisms in order to maintain life. Enzymes are the main players in this process as they are responsible for catalyzing the chemical reactions. The enzyme-reaction relationships can be used for the reconstructi

  20. Kinetic Modelling of Macroscopic Properties Changes during Crosslinked Polybutadiene Oxidation

    Science.gov (United States)

    Audouin, Ludmila; Coquillat, Marie; Colin, Xavier; Verdu, Jacques; Nevière, Robert

    2008-08-01

    The thermal oxidation of additive free hydroxyl-terminated polybutadiene (HTPB) isocyanate crosslinked rubber bulk samples has been studied at 80, 100 and 120 °C in air. The oxidation kinetics has been monitored by gravimetry and thickness distribution of oxidation products was determined by FTIR mapping. Changes of elastic shear modulus G' during oxidation were followed during oxidation at the same temperatures. The kinetic model established previously for HTPB has been adapted for bulk sample oxidation using previously determined set of kinetic parameters. Oxygen diffusion control of oxidation has been introduced into the model. The mass changes kinetic curves and oxidation products profiles were simulated and adequate fit was obtained. Using the rubber elasticity theory the elastic modulus changes were simulated taking into account the elastically active chains concentration changes due to chain scission and crosslinking reactions. The reasonable fit of G' as a function of oxidation time experimental curves was obtained.

  1. Breakdown parameter for kinetic modeling of multiscale gas flows.

    Science.gov (United States)

    Meng, Jianping; Dongari, Nishanth; Reese, Jason M; Zhang, Yonghao

    2014-06-01

    Multiscale methods built purely on the kinetic theory of gases provide information about the molecular velocity distribution function. It is therefore both important and feasible to establish new breakdown parameters for assessing the appropriateness of a fluid description at the continuum level by utilizing kinetic information rather than macroscopic flow quantities alone. We propose a new kinetic criterion to indirectly assess the errors introduced by a continuum-level description of the gas flow. The analysis, which includes numerical demonstrations, focuses on the validity of the Navier-Stokes-Fourier equations and corresponding kinetic models and reveals that the new criterion can consistently indicate the validity of continuum-level modeling in both low-speed and high-speed flows at different Knudsen numbers.

  2. A Kinetic Model of Chromium in a Flame

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Chromium has been identified as a carcinogenic metal.Incineration is the useful method for disposal of toxic chromium hazard waste and a chromium kinetic model in a flame is very important to study chromium oxidation.Chromium chemical kinetics over a range of temperatures of a hydrogen/air flame is proposed.Nine chromium compounds and fifty-eight reversible chemical reactions were considered The forward reaction rates are calculated based on the molecular collision approach for unknown ones and Arrhenius's Law for known ones.The backward reaction rates were calculated according to forward reaction rates, the equilibrium constants and chemical thermodynamics.It is verified by several equilibrium cases and is tested by a hydrogen/air diffusion flame.The results show that the kinetic model could be used in cases in which the chromium kinetics play an important role in a flame

  3. A multi-tissue type genome-scale metabolic network for analysis of whole-body systems physiology

    OpenAIRE

    Feist Adam M; Bordbar Aarash; Usaite-Black Renata; Woodcock Joseph; Palsson Bernhard O; Famili Iman

    2011-01-01

    Abstract Background Genome-scale metabolic reconstructions provide a biologically meaningful mechanistic basis for the genotype-phenotype relationship. The global human metabolic network, termed Recon 1, has recently been reconstructed allowing the systems analysis of human metabolic physiology and pathology. Utilizing high-throughput data, Recon 1 has recently been tailored to different cells and tissues, including the liver, kidney, brain, and alveolar macrophage. These models have shown ut...

  4. A Consensus Genome-scale Reconstruction of Chinese Hamster Ovary Cell Metabolism

    DEFF Research Database (Denmark)

    Hefzi, Hooman; Ang, Kok Siong; Hanscho, Michael

    2016-01-01

    in CHO and associated them with >1,700 genes in the Cricetulus griseus genome. The genome-scale metabolic model based on this reconstruction, iCHO1766, and cell-line-specific models for CHO-K1, CHO-S, and CHO-DG44 cells provide the biochemical basis of growth and recombinant protein production......Chinese hamster ovary (CHO) cells dominate biotherapeutic protein production and are widely used in mammalian cell line engineering research. To elucidate metabolic bottlenecks in protein production and to guide cell engineering and bioprocess optimization, we reconstructed the metabolic pathways...... simulations show that the metabolic resources in CHO are more than three times more efficiently utilized for growth or recombinant protein synthesis following targeted efforts to engineer the CHO secretory pathway. This model will further accelerate CHO cell engineering and help optimize bioprocesses....

  5. Kinetic exchange models: From molecular physics to social science

    Science.gov (United States)

    Patriarca, Marco; Chakraborti, Anirban

    2013-08-01

    We discuss several multi-agent models that have their origin in the kinetic exchange theory of statistical mechanics and have been recently applied to a variety of problems in the social sciences. This class of models can be easily adapted for simulations in areas other than physics, such as the modeling of income and wealth distributions in economics and opinion dynamics in sociology.

  6. Kinetic exchange models: From molecular physics to social science

    CERN Document Server

    Patriarca, Marco

    2013-01-01

    We discuss several multi-agent models that have their origin in the kinetic exchange theory of statistical mechanics and have been recently applied to a variety of problems in the social sciences. This class of models can be easily adapted for simulations in areas other than physics, such as the modeling of income and wealth distributions in economics and opinion dynamics in sociology.

  7. Physiologically based kinetic modeling of the bioactivation of myristicin

    NARCIS (Netherlands)

    Al-Malahmeh, Amer J.; Al-Ajlouni, Abdelmajeed; Wesseling, Sebastiaan; Soffers, Ans E.M.F.; Al-Subeihi, A.; Kiwamoto, Reiko; Vervoort, Jacques; Rietjens, Ivonne M.C.M.

    2016-01-01

    The present study describes physiologically based kinetic (PBK) models for the alkenylbenzene myristicin that were developed by extension of the PBK models for the structurally related alkenylbenzene safrole in rat and human. The newly developed myristicin models revealed that the formation of th

  8. Chemical kinetic modeling of H{sub 2} applications

    Energy Technology Data Exchange (ETDEWEB)

    Marinov, N.M.; Westbrook, C.K.; Cloutman, L.D. [Lawrence Livermore National Lab., CA (United States)] [and others

    1995-09-01

    Work being carried out at LLNL has concentrated on studies of the role of chemical kinetics in a variety of problems related to hydrogen combustion in practical combustion systems, with an emphasis on vehicle propulsion. Use of hydrogen offers significant advantages over fossil fuels, and computer modeling provides advantages when used in concert with experimental studies. Many numerical {open_quotes}experiments{close_quotes} can be carried out quickly and efficiently, reducing the cost and time of system development, and many new and speculative concepts can be screened to identify those with sufficient promise to pursue experimentally. This project uses chemical kinetic and fluid dynamic computational modeling to examine the combustion characteristics of systems burning hydrogen, either as the only fuel or mixed with natural gas. Oxidation kinetics are combined with pollutant formation kinetics, including formation of oxides of nitrogen but also including air toxics in natural gas combustion. We have refined many of the elementary kinetic reaction steps in the detailed reaction mechanism for hydrogen oxidation. To extend the model to pressures characteristic of internal combustion engines, it was necessary to apply theoretical pressure falloff formalisms for several key steps in the reaction mechanism. We have continued development of simplified reaction mechanisms for hydrogen oxidation, we have implemented those mechanisms into multidimensional computational fluid dynamics models, and we have used models of chemistry and fluid dynamics to address selected application problems. At the present time, we are using computed high pressure flame, and auto-ignition data to further refine the simplified kinetics models that are then to be used in multidimensional fluid mechanics models. Detailed kinetics studies have investigated hydrogen flames and ignition of hydrogen behind shock waves, intended to refine the detailed reactions mechanisms.

  9. A unifying kinetic framework for modeling oxidoreductase-catalyzed reactions

    OpenAIRE

    Chang, Ivan; Baldi, Pierre

    2013-01-01

    Motivation: Oxidoreductases are a fundamental class of enzymes responsible for the catalysis of oxidation–reduction reactions, crucial in most bioenergetic metabolic pathways. From their common root in the ancient prebiotic environment, oxidoreductases have evolved into diverse and elaborate protein structures with specific kinetic properties and mechanisms adapted to their individual functional roles and environmental conditions. While accurate kinetic modeling of oxidoreductases is thus imp...

  10. The Nonlinear Magnetosphere: Expressions in MHD and in Kinetic Models

    Science.gov (United States)

    Hesse, Michael; Birn, Joachim

    2011-01-01

    Like most plasma systems, the magnetosphere of the Earth is governed by nonlinear dynamic evolution equations. The impact of nonlinearities ranges from large scales, where overall dynamics features are exhibiting nonlinear behavior, to small scale, kinetic, processes, where nonlinear behavior governs, among others, energy conversion and dissipation. In this talk we present a select set of examples of such behavior, with a specific emphasis on how nonlinear effects manifest themselves in MHD and in kinetic models of magnetospheric plasma dynamics.

  11. Application of Detailed Chemical Kinetics to Combustion Instability Modeling

    Science.gov (United States)

    2016-01-04

    under two different conditions corresponding to marginally stable and unstable operation in order to evaluate the performance of the chemical kinetics...instability is a complex interaction between acoustics and the heat release due to combustion.In rocket engines, which are acoustically compact, there is...and amplitudes remains a challenge. The present article is an attempt towards addressing such discrepancies by enhancing the chemical kinetics model

  12. Kinetic model for hydroisomerization reaction of C8-aromatics

    Institute of Scientific and Technical Information of China (English)

    Ouguan XU; Hongye SU; Xiaoming JIN; Jian CHU

    2008-01-01

    Based on the reported reaction networks, a novel six-component hydroisomerization reaction net-work with a new lumped species including C8-naphthenes and Cs-paraffins is proposed and a kinetic model for a commercial unit is also developed. An empirical catalyst deactivation function is incorporated into the model accounting for the loss in activity because of coke forma-tion on the catalyst surface during the long-term opera-tion. The Runge-Kutta method is used to solve the ordinary differential equations of the model. The reaction kinetic parameters are benchmarked with several sets of balanced plant data and estimated by the differential vari-able metric optimization method (BFGS). The kinetic model is validated by an industrial unit with sets of plant data under different operating conditions and simulation results show a good agreement between the model predic-tions and the plant observations.

  13. A tool model for predicting atmospheric kinetics with sensitivity analysis

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    A package( a tool model) for program of predicting atmospheric chemical kinetics with sensitivity analysis is presented. The new direct method of calculating the first order sensitivity coefficients using sparse matrix technology to chemical kinetics is included in the tool model, it is only necessary to triangularize the matrix related to the Jacobian matrix of the model equation. The Gear type procedure is used to integrate amodel equation and its coupled auxiliary sensitivity coefficient equations. The FORTRAN subroutines of the model equation, the sensitivity coefficient equations, and their Jacobian analytical expressions are generated automatically from a chemical mechanism. The kinetic representation for the model equation and its sensitivity coefficient equations, and their Jacobian matrix is presented. Various FORTRAN subroutines in packages, such as SLODE, modified MA28, Gear package, with which the program runs in conjunction are recommended.The photo-oxidation of dimethyl disulfide is used for illustration.

  14. Kinetics of ethylcyclohexane pyrolysis and oxidation: An experimental and detailed kinetic modeling study

    KAUST Repository

    Wang, Zhandong

    2015-07-01

    Ethylcyclohexane (ECH) is a model compound for cycloalkanes with long alkyl side-chains. A preliminary investigation on ECH (Wang et al., Proc. Combust. Inst., 35, 2015, 367-375) revealed that an accurate ECH kinetic model with detailed fuel consumption mechanism and aromatic growth pathways, as well as additional ECH pyrolysis and oxidation data with detailed species concentration covering a wide pressure and temperature range are required to understand the ECH combustion kinetics. In this work, the flow reactor pyrolysis of ECH at various pressures (30, 150 and 760Torr) was studied using synchrotron vacuum ultraviolet (VUV) photoionization mass spectrometry (PIMS) and gas chromatography (GC). The mole fraction profiles of numerous major and minor species were evaluated, and good agreement was observed between the PIMS and GC data sets. Furthermore, a fuel-rich burner-stabilized laminar premixed ECH/O2/Ar flame at 30Torr was studied using synchrotron VUV PIMS. A detailed kinetic model for ECH high temperature pyrolysis and oxidation was developed and validated against the pyrolysis and flame data performed in this work. Further validation of the kinetic model is presented against literature data including species concentrations in jet-stirred reactor oxidation, ignition delay times in a shock tube, and laminar flame speeds at various pressures and equivalence ratios. The model well predicts the consumption of ECH, the growth of aromatics, and the global combustion properties. Reaction flux and sensitivity analysis were utilized to elucidate chemical kinetic features of ECH combustion under various reaction conditions. © 2015 The Combustion Institute.

  15. Characterizing acetogenic metabolism using a genome-scale metabolic reconstruction of Clostridium ljungdahlii

    Energy Technology Data Exchange (ETDEWEB)

    Nagarajan, H; Sahin, M; Nogales, J; Latif, H; Lovley, DR; Ebrahim, A; Zengler, K

    2013-11-25

    Background: The metabolic capabilities of acetogens to ferment a wide range of sugars, to grow autotrophically on H-2/CO2, and more importantly on synthesis gas (H-2/CO/CO2) make them very attractive candidates as production hosts for biofuels and biocommodities. Acetogenic metabolism is considered one of the earliest modes of bacterial metabolism. A thorough understanding of various factors governing the metabolism, in particular energy conservation mechanisms, is critical for metabolic engineering of acetogens for targeted production of desired chemicals. Results: Here, we present the genome-scale metabolic network of Clostridium ljungdahlii, the first such model for an acetogen. This genome-scale model (iHN637) consisting of 637 genes, 785 reactions, and 698 metabolites captures all the major central metabolic and biosynthetic pathways, in particular pathways involved in carbon fixation and energy conservation. A combination of metabolic modeling, with physiological and transcriptomic data provided insights into autotrophic metabolism as well as aided the characterization of a nitrate reduction pathway in C. ljungdahlii. Analysis of the iHN637 metabolic model revealed that flavin based electron bifurcation played a key role in energy conservation during autotrophic growth and helped identify genes for some of the critical steps in this mechanism. Conclusions: iHN637 represents a predictive model that recapitulates experimental data, and provides valuable insights into the metabolic response of C. ljungdahlii to genetic perturbations under various growth conditions. Thus, the model will be instrumental in guiding metabolic engineering of C. ljungdahlii for the industrial production of biocommodities and biofuels.

  16. Zea mays iRS1563: a comprehensive genome-scale metabolic reconstruction of maize metabolism.

    Science.gov (United States)

    Saha, Rajib; Suthers, Patrick F; Maranas, Costas D

    2011-01-01

    The scope and breadth of genome-scale metabolic reconstructions have continued to expand over the last decade. Herein, we introduce a genome-scale model for a plant with direct applications to food and bioenergy production (i.e., maize). Maize annotation is still underway, which introduces significant challenges in the association of metabolic functions to genes. The developed model is designed to meet rigorous standards on gene-protein-reaction (GPR) associations, elementally and charged balanced reactions and a biomass reaction abstracting the relative contribution of all biomass constituents. The metabolic network contains 1,563 genes and 1,825 metabolites involved in 1,985 reactions from primary and secondary maize metabolism. For approximately 42% of the reactions direct literature evidence for the participation of the reaction in maize was found. As many as 445 reactions and 369 metabolites are unique to the maize model compared to the AraGEM model for A. thaliana. 674 metabolites and 893 reactions are present in Zea mays iRS1563 that are not accounted for in maize C4GEM. All reactions are elementally and charged balanced and localized into six different compartments (i.e., cytoplasm, mitochondrion, plastid, peroxisome, vacuole and extracellular). GPR associations are also established based on the functional annotation information and homology prediction accounting for monofunctional, multifunctional and multimeric proteins, isozymes and protein complexes. We describe results from performing flux balance analysis under different physiological conditions, (i.e., photosynthesis, photorespiration and respiration) of a C4 plant and also explore model predictions against experimental observations for two naturally occurring mutants (i.e., bm1 and bm3). The developed model corresponds to the largest and more complete to-date effort at cataloguing metabolism for a plant species.

  17. Zea mays iRS1563: a comprehensive genome-scale metabolic reconstruction of maize metabolism.

    Directory of Open Access Journals (Sweden)

    Rajib Saha

    Full Text Available The scope and breadth of genome-scale metabolic reconstructions have continued to expand over the last decade. Herein, we introduce a genome-scale model for a plant with direct applications to food and bioenergy production (i.e., maize. Maize annotation is still underway, which introduces significant challenges in the association of metabolic functions to genes. The developed model is designed to meet rigorous standards on gene-protein-reaction (GPR associations, elementally and charged balanced reactions and a biomass reaction abstracting the relative contribution of all biomass constituents. The metabolic network contains 1,563 genes and 1,825 metabolites involved in 1,985 reactions from primary and secondary maize metabolism. For approximately 42% of the reactions direct literature evidence for the participation of the reaction in maize was found. As many as 445 reactions and 369 metabolites are unique to the maize model compared to the AraGEM model for A. thaliana. 674 metabolites and 893 reactions are present in Zea mays iRS1563 that are not accounted for in maize C4GEM. All reactions are elementally and charged balanced and localized into six different compartments (i.e., cytoplasm, mitochondrion, plastid, peroxisome, vacuole and extracellular. GPR associations are also established based on the functional annotation information and homology prediction accounting for monofunctional, multifunctional and multimeric proteins, isozymes and protein complexes. We describe results from performing flux balance analysis under different physiological conditions, (i.e., photosynthesis, photorespiration and respiration of a C4 plant and also explore model predictions against experimental observations for two naturally occurring mutants (i.e., bm1 and bm3. The developed model corresponds to the largest and more complete to-date effort at cataloguing metabolism for a plant species.

  18. A genomic scale map of genetic diversity in Trypanosoma cruzi

    Directory of Open Access Journals (Sweden)

    Ackermann Alejandro A

    2012-12-01

    Full Text Available Abstract Background Trypanosoma cruzi, the causal agent of Chagas Disease, affects more than 16 million people in Latin America. The clinical outcome of the disease results from a complex interplay between environmental factors and the genetic background of both the human host and the parasite. However, knowledge of the genetic diversity of the parasite, is currently limited to a number of highly studied loci. The availability of a number of genomes from different evolutionary lineages of T. cruzi provides an unprecedented opportunity to look at the genetic diversity of the parasite at a genomic scale. Results Using a bioinformatic strategy, we have clustered T. cruzi sequence data available in the public domain and obtained multiple sequence alignments in which one or two alleles from the reference CL-Brener were included. These data covers 4 major evolutionary lineages (DTUs: TcI, TcII, TcIII, and the hybrid TcVI. Using these set of alignments we have identified 288,957 high quality single nucleotide polymorphisms and 1,480 indels. In a reduced re-sequencing study we were able to validate ~ 97% of high-quality SNPs identified in 47 loci. Analysis of how these changes affect encoded protein products showed a 0.77 ratio of synonymous to non-synonymous changes in the T. cruzi genome. We observed 113 changes that introduce or remove a stop codon, some causing significant functional changes, and a number of tri-allelic and tetra-allelic SNPs that could be exploited in strain typing assays. Based on an analysis of the observed nucleotide diversity we show that the T. cruzi genome contains a core set of genes that are under apparent purifying selection. Interestingly, orthologs of known druggable targets show statistically significant lower nucleotide diversity values. Conclusions This study provides the first look at the genetic diversity of T. cruzi at a genomic scale. The analysis covers an estimated ~ 60% of the genetic diversity present in the

  19. Repopulation Kinetics and the Linear-Quadratic Model

    Science.gov (United States)

    O'Rourke, S. F. C.; McAneney, H.; Starrett, C.; O'Sullivan, J. M.

    2009-08-01

    The standard Linear-Quadratic (LQ) survival model for radiotherapy is used to investigate different schedules of radiation treatment planning for advanced head and neck cancer. We explore how these treament protocols may be affected by different tumour repopulation kinetics between treatments. The laws for tumour cell repopulation include the logistic and Gompertz models and this extends the work of Wheldon et al. [1], which was concerned with the case of exponential repopulation between treatments. Treatment schedules investigated include standarized and accelerated fractionation. Calculations based on the present work show, that even with growth laws scaled to ensure that the repopulation kinetics for advanced head and neck cancer are comparable, considerable variation in the survival fraction to orders of magnitude emerged. Calculations show that application of the Gompertz model results in a significantly poorer prognosis for tumour eradication. Gaps in treatment also highlight the differences in the LQ model with the effect of repopulation kinetics included.

  20. Kinetic modeling of the Townsend breakdown in argon

    Science.gov (United States)

    Macheret, S. O.; Shneider, M. N.

    2013-10-01

    Kinetic modeling of the Townsend breakdown in argon was performed in the "forward-back" approximation. The kinetic model was found to adequately describe the left branch of the Paschen curve, and the important role of ionization by fast ions and atoms near the cathode, as well as the increase in secondary emission coefficient in strong electric fields described in the literature, was confirmed. The modeling also showed that the electron energy distribution function develops a beam of high-energy electrons and that the runaway effect, i.e., the monotonic increase of the mean electron energy with the distance from the cathode, occurs at the left branch of the Paschen curve.

  1. Hard-sphere kinetic models for inert and reactive mixtures

    Science.gov (United States)

    Polewczak, Jacek

    2016-10-01

    I consider stochastic variants of a simple reacting sphere (SRS) kinetic model (Xystris and Dahler 1978 J. Chem. Phys. 68 387-401, Qin and Dahler 1995 J. Chem. Phys. 103 725-50, Dahler and Qin 2003 J. Chem. Phys. 118 8396-404) for dense reacting mixtures. In contrast to the line-of-center models of chemical reactive models, in the SRS kinetic model, the microscopic reversibility (detailed balance) can be easily shown to be satisfied, and thus all mathematical aspects of the model can be fully justified. In the SRS model, the molecules behave as if they were single mass points with two internal states. Collisions may alter the internal states of the molecules, and this occurs when the kinetic energy associated with the reactive motion exceeds the activation energy. Reactive and non-reactive collision events are considered to be hard sphere-like. I consider a four component mixture A, B, A *, B *, in which the chemical reactions are of the type A+B\\rightleftharpoons {{A}\\ast}+{{B}\\ast} , with A * and B * being distinct species from A and B. This work extends the joined works with George Stell to the kinetic models of dense inert and reactive mixtures. The idea of introducing smearing-type effect in the collisional process results in a new class of stochastic kinetic models for both inert and reactive mixtures. In this paper the important new mathematical properties of such systems of kinetic equations are proven. The new results for stochastic revised Enskog system for inert mixtures are also provided.

  2. Toward the automated generation of genome-scale metabolic networks in the SEED

    Directory of Open Access Journals (Sweden)

    Gould John

    2007-04-01

    Full Text Available Abstract Background Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. Results We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis. We have implemented our tools and database within the SEED, an open-source software environment for comparative

  3. Strain in the mesoscale kinetic Monte Carlo model for sintering

    DEFF Research Database (Denmark)

    Bjørk, Rasmus; Frandsen, Henrik Lund; Tikare, V.

    2014-01-01

    Shrinkage strains measured from microstructural simulations using the mesoscale kinetic Monte Carlo (kMC) model for solid state sintering are discussed. This model represents the microstructure using digitized discrete sites that are either grain or pore sites. The algorithm used to simulate...

  4. Some models for the adsorption kinetics of pesticides in soil

    NARCIS (Netherlands)

    Leistra, M.; Dekkers, W.A.

    1977-01-01

    Three models describing adsorption‐desorption kinetics of pesticides in soil, that could be incorporated into computer programs on pesticide movement in soil, were discussed, the first model involved single first‐order rate equations for adsorption and desorption. Results from an analytical and a

  5. Simplified kinetic models of methanol oxidation on silver

    DEFF Research Database (Denmark)

    Andreasen, Anders; Lynggaard, Hasse Harloff; Stegelmann, Carsten;

    2005-01-01

    Recently the authors developed a microkinetic model of methanol oxidation on silver [A. Andreasen, H. Lynggaard, C. Stegelmann, P. Stoltze, Surf. Sci. 544 (2003) 5–23]. The model successfully explains both surface science experiments and kinetic experiments at industrial conditions applying...

  6. Simplified kinetic models of methanol oxidation on silver

    DEFF Research Database (Denmark)

    Andreasen, A.; Lynggaard, H.; Stegelmann, C.;

    2005-01-01

    Recently the authors developed a microkinetic model of methanol oxidation on silver [A. Andreasen, H. Lynggaard, C. Stegelmann, P. Stoltze, Surf. Sci. 544 (2003) 5-23]. The model successfully explains both surface science experiments and kinetic experiments at industrial conditions applying...

  7. Computer-Aided Construction of Chemical Kinetic Models

    Energy Technology Data Exchange (ETDEWEB)

    Green, William H. [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)

    2014-12-31

    The combustion chemistry of even simple fuels can be extremely complex, involving hundreds or thousands of kinetically significant species. The most reasonable way to deal with this complexity is to use a computer not only to numerically solve the kinetic model, but also to construct the kinetic model in the first place. Because these large models contain so many numerical parameters (e.g. rate coefficients, thermochemistry) one never has sufficient data to uniquely determine them all experimentally. Instead one must work in “predictive” mode, using theoretical rather than experimental values for many of the numbers in the model, and as appropriate refining the most sensitive numbers through experiments. Predictive chemical kinetics is exactly what is needed for computer-aided design of combustion systems based on proposed alternative fuels, particularly for early assessment of the value and viability of proposed new fuels before those fuels are commercially available. This project was aimed at making accurate predictive chemical kinetics practical; this is a challenging goal which requires a range of science advances. The project spanned a wide range from quantum chemical calculations on individual molecules and elementary-step reactions, through the development of improved rate/thermo calculation procedures, the creation of algorithms and software for constructing and solving kinetic simulations, the invention of methods for model-reduction while maintaining error control, and finally comparisons with experiment. Many of the parameters in the models were derived from quantum chemistry calculations, and the models were compared with experimental data measured in our lab or in collaboration with others.

  8. Information cascade, Kirman's ant colony model, and kinetic Ising model

    CERN Document Server

    Hisakado, Masato

    2014-01-01

    In this paper, we discuss a voting model in which voters can obtain information from a finite number of previous voters. There exist three groups of voters: (i) digital herders and independent voters, (ii) analog herders and independent voters, and (iii) tanh-type herders. In our previous paper, we used the mean field approximation for case (i). In that study, if the reference number r is above three, phase transition occurs and the solution converges to one of the equilibria. In contrast, in the current study, the solution oscillates between the two equilibria, that is, good and bad equilibria. In this paper, we show that there is no phase transition when r is finite. If the annealing schedule is adequately slow from finite r to infinite r, the voting rate converges only to the good equilibrium. In case (ii), the state of reference votes is equivalent to that of Kirman's ant colony model, and it follows beta binomial distribution. In case (iii), we show that the model is equivalent to the finite-size kinetic...

  9. Comparison of linear modes in kinetic plasma models

    CERN Document Server

    Camporeale, Enrico

    2016-01-01

    We compare, in an extensive and systematic way, linear theory results obtained with the hybrid (ion-kinetic and electron-fluid), the gyrokinetic and the fully-kinetic plasma models. We present a test case with parameters that are relevant for solar wind turbulence at small scales, which is a topic now recognized to need a kinetic treatment, to a certain extent. We comment on the comparison of low-frequency single modes (Alfv\\'{e}n/ion-cyclotron, ion-acoustic, and fast modes) for a wide range of propagation angles, and on the overall spectral properties of the linear operators, for quasi-perpendicular propagation. The methodology and the results presented in this paper will be valuable when choosing which model should be used in regimes where the assumptions of each model are not trivially satisfied.

  10. Kinetic modelling for zinc (II) ions biosorption onto Luffa cylindrica

    Energy Technology Data Exchange (ETDEWEB)

    Oboh, I., E-mail: innocentoboh@uniuyo.edu.ng [Department of Chemical and Petroleum Engineering, University of Uyo, Uyo (Nigeria); Aluyor, E.; Audu, T. [Department of Chemical Engineering, University of Uyo, BeninCity, BeninCity (Nigeria)

    2015-03-30

    The biosorption of Zinc (II) ions onto a biomaterial - Luffa cylindrica has been studied. This biomaterial was characterized by elemental analysis, surface area, pore size distribution, scanning electron microscopy, and the biomaterial before and after sorption, was characterized by Fourier Transform Infra Red (FTIR) spectrometer. The kinetic nonlinear models fitted were Pseudo-first order, Pseudo-second order and Intra-particle diffusion. A comparison of non-linear regression method in selecting the kinetic model was made. Four error functions, namely coefficient of determination (R{sup 2}), hybrid fractional error function (HYBRID), average relative error (ARE), and sum of the errors squared (ERRSQ), were used to predict the parameters of the kinetic models. The strength of this study is that a biomaterial with wide distribution particularly in the tropical world and which occurs as waste material could be put into effective utilization as a biosorbent to address a crucial environmental problem.

  11. Genome-scale consequences of cofactor balancing in engineered pentose utilization pathways in Saccharomyces cerevisiae.

    Directory of Open Access Journals (Sweden)

    Amit Ghosh

    Full Text Available Biofuels derived from lignocellulosic biomass offer promising alternative renewable energy sources for transportation fuels. Significant effort has been made to engineer Saccharomyces cerevisiae to efficiently ferment pentose sugars such as D-xylose and L-arabinose into biofuels such as ethanol through heterologous expression of the fungal D-xylose and L-arabinose pathways. However, one of the major bottlenecks in these fungal pathways is that the cofactors are not balanced, which contributes to inefficient utilization of pentose sugars. We utilized a genome-scale model of S. cerevisiae to predict the maximal achievable growth rate for cofactor balanced and imbalanced D-xylose and L-arabinose utilization pathways. Dynamic flux balance analysis (DFBA was used to simulate batch fermentation of glucose, D-xylose, and L-arabinose. The dynamic models and experimental results are in good agreement for the wild type and for the engineered D-xylose utilization pathway. Cofactor balancing the engineered D-xylose and L-arabinose utilization pathways simulated an increase in ethanol batch production of 24.7% while simultaneously reducing the predicted substrate utilization time by 70%. Furthermore, the effects of cofactor balancing the engineered pentose utilization pathways were evaluated throughout the genome-scale metabolic network. This work not only provides new insights to the global network effects of cofactor balancing but also provides useful guidelines for engineering a recombinant yeast strain with cofactor balanced engineered pathways that efficiently co-utilizes pentose and hexose sugars for biofuels production. Experimental switching of cofactor usage in enzymes has been demonstrated, but is a time-consuming effort. Therefore, systems biology models that can predict the likely outcome of such strain engineering efforts are highly useful for motivating which efforts are likely to be worth the significant time investment.

  12. A Detailed Chemical Kinetic Model for TNT

    Energy Technology Data Exchange (ETDEWEB)

    Pitz, W J; Westbrook, C K

    2005-01-13

    A detailed chemical kinetic mechanism for 2,4,6-tri-nitrotoluene (TNT) has been developed to explore problems of explosive performance and soot formation during the destruction of munitions. The TNT mechanism treats only gas-phase reactions. Reactions for the decomposition of TNT and for the consumption of intermediate products formed from TNT are assembled based on information from the literature and on current understanding of aromatic chemistry. Thermodynamic properties of intermediate and radical species are estimated by group additivity. Reaction paths are developed based on similar paths for aromatic hydrocarbons. Reaction-rate constant expressions are estimated from the literature and from analogous reactions where the rate constants are available. The detailed reaction mechanism for TNT is added to existing reaction mechanisms for RDX and for hydrocarbons. Computed results show the effect of oxygen concentration on the amount of soot precursors that are formed in the combustion of RDX and TNT mixtures in N{sub 2}/O{sub 2} mixtures.

  13. Kinetic models for irreversible processes on a lattice

    Energy Technology Data Exchange (ETDEWEB)

    Wolf, N.O.

    1979-04-01

    The development and application of kinetic lattice models are considered. For the most part, the discussions are restricted to lattices in one-dimension. In Chapter 1, a brief overview of kinetic lattice model formalisms and an extensive literature survey are presented. A review of the kinetic models for non-cooperative lattice events is presented in Chapter 2. The development of cooperative lattice models and solution of the resulting kinetic equations for an infinite and a semi-infinite lattice are thoroughly discussed in Chapters 3 and 4. The cooperative models are then applied to the problem of theoretically dtermining the sticking coefficient for molecular chemisorption in Chapter 5. In Chapter 6, other possible applications of these models and several model generalizations are considered. Finally, in Chapter 7, an experimental study directed toward elucidating the mechanistic factors influencing the chemisorption of methane on single crystal tungsten is reported. In this it differs from the rest of the thesis which deals with the statistical distributions resulting from a given mechanism.

  14. Transperitoneal transport of creatinine. A comparison of kinetic models

    DEFF Research Database (Denmark)

    Fugleberg, S; Graff, J; Joffe, P;

    1994-01-01

    Six kinetic models of transperitoneal creatinine transport were formulated and validated on the basis of experimental results obtained from 23 non-diabetic patients undergoing peritoneal dialysis. The models were designed to elucidate the presence or absence of diffusive, non-lymphatic convective...... including all three forms of transport is superior to other models. We conclude that the best model of transperitoneal creatinine transport includes diffusion, non-lymphatic convective transport and lymphatic convective transport....

  15. A systems approach to predict oncometabolites via context-specific genome-scale metabolic networks.

    Directory of Open Access Journals (Sweden)

    Hojung Nam

    2014-09-01

    Full Text Available Altered metabolism in cancer cells has been viewed as a passive response required for a malignant transformation. However, this view has changed through the recently described metabolic oncogenic factors: mutated isocitrate dehydrogenases (IDH, succinate dehydrogenase (SDH, and fumarate hydratase (FH that produce oncometabolites that competitively inhibit epigenetic regulation. In this study, we demonstrate in silico predictions of oncometabolites that have the potential to dysregulate epigenetic controls in nine types of cancer by incorporating massive scale genetic mutation information (collected from more than 1,700 cancer genomes, expression profiling data, and deploying Recon 2 to reconstruct context-specific genome-scale metabolic models. Our analysis predicted 15 compounds and 24 substructures of potential oncometabolites that could result from the loss-of-function and gain-of-function mutations of metabolic enzymes, respectively. These results suggest a substantial potential for discovering unidentified oncometabolites in various forms of cancers.

  16. Plasma interfacial mixing layers: Comparisons of fluid and kinetic models

    Science.gov (United States)

    Vold, Erik; Yin, Lin; Taitano, William; Albright, B. J.; Chacon, Luis; Simakov, Andrei; Molvig, Kim

    2016-10-01

    We examine plasma transport across an initial discontinuity between two species by comparing fluid and kinetic models. The fluid model employs a kinetic theory approximation for plasma transport in the limit of small Knudsen number. The kinetic simulations include explicit particle-in-cell simulations (VPIC) and a new implicit Vlasov-Fokker-Planck code, iFP. The two kinetic methods are shown to be in close agreement for many aspects of the mixing dynamics at early times (to several hundred collision times). The fluid model captures some of the earliest time dynamic behavior seen in the kinetic results, and also generally agrees with iFP at late times when the total pressure gradient relaxes and the species transport is dominated by slow diffusive processes. The results show three distinct phases of the mixing: a pressure discontinuity forms across the initial interface (on times of a few collisions), the pressure perturbations propagate away from the interfacial mixing region (on time scales of an acoustic transit) and at late times the pressure relaxes in the mix region leaving a non-zero center of mass flow velocity. The center of mass velocity associated with the outward propagating pressure waves is required to conserve momentum in the rest frame. Work performed under the auspices of the U.S. DOE by the LANS, LLC, Los Alamos National Laboratory under Contract No. DE-AC52-06NA25396. Funding provided by the Advanced Simulation and Computing (ASC) Program.

  17. Thermodynamic and Kinetic Modeling of Transcriptional Pausing

    National Research Council Canada - National Science Library

    Vasisht R. Tadigotla; Dáibhid Ó. Maoiléidigh; Anirvan M. Sengupta; Vitaly Epshtein; Richard H. Ebright; Evgeny Nudler; Andrei E. Ruckenstein

    2006-01-01

    We present a statistical mechanics approach for the prediction of backtracked pauses in bacterial transcription elongation derived from structural models of the transcription elongation complex (EC...

  18. Bayesian inference of chemical kinetic models from proposed reactions

    KAUST Repository

    Galagali, Nikhil

    2015-02-01

    © 2014 Elsevier Ltd. Bayesian inference provides a natural framework for combining experimental data with prior knowledge to develop chemical kinetic models and quantify the associated uncertainties, not only in parameter values but also in model structure. Most existing applications of Bayesian model selection methods to chemical kinetics have been limited to comparisons among a small set of models, however. The significant computational cost of evaluating posterior model probabilities renders traditional Bayesian methods infeasible when the model space becomes large. We present a new framework for tractable Bayesian model inference and uncertainty quantification using a large number of systematically generated model hypotheses. The approach involves imposing point-mass mixture priors over rate constants and exploring the resulting posterior distribution using an adaptive Markov chain Monte Carlo method. The posterior samples are used to identify plausible models, to quantify rate constant uncertainties, and to extract key diagnostic information about model structure-such as the reactions and operating pathways most strongly supported by the data. We provide numerical demonstrations of the proposed framework by inferring kinetic models for catalytic steam and dry reforming of methane using available experimental data.

  19. 3D Building Model Fitting Using A New Kinetic Framework

    CERN Document Server

    Brédif, Mathieu; Pierrot-Deseilligny, Marc; Maître, Henri

    2008-01-01

    We describe a new approach to fit the polyhedron describing a 3D building model to the point cloud of a Digital Elevation Model (DEM). We introduce a new kinetic framework that hides to its user the combinatorial complexity of determining or maintaining the polyhedron topology, allowing the design of a simple variational optimization. This new kinetic framework allows the manipulation of a bounded polyhedron with simple faces by specifying the target plane equations of each of its faces. It proceeds by evolving continuously from the polyhedron defined by its initial topology and its initial plane equations to a polyhedron that is as topologically close as possible to the initial polyhedron but with the new plane equations. This kinetic framework handles internally the necessary topological changes that may be required to keep the faces simple and the polyhedron bounded. For each intermediate configurations where the polyhedron looses the simplicity of its faces or its boundedness, the simplest topological mod...

  20. A kinetic model of carbon burnout in pulverized coal combustion

    Energy Technology Data Exchange (ETDEWEB)

    Hurt, R.; Jian-Kuan Sun; Lunden, M. [Brown University, Providence, RI (United States). Division of Engineering

    1998-04-01

    The degree of carbon burnout is an important operating characteristic of full-scale suspension-fired coal combustion systems affecting boiler efficiency, electrostatic precipitator operation and the value of fly ash as a saleable product. Prediction of carbon loss requires special char combustion kinetics valid through the very high conversions targeted in industry (typically {gt} 99.5%), and valid for a wide-range of particle temperature histories occurring in full-scale furnaces. The paper presents high-temperature kinetic data for five coal chars in the form of time-resolved burning profiles that include the late stages of combustion. It then describes the development and validation of the Carbon Burnout Kinetic Model (CBK), a coal-general kinetics package that is specifically designed to predict the total extent of carbon burnout and ultimate fly ash carbon content for prescribed temperature/oxygen histories typical of pulverized coal combustion systems. The model combines the single-film treatment of cha oxidation with quantitative descriptions of thermal annealing, statistical kinetics, statistical densities, and ash inhibition in the late stages of combustion. In agreement with experimental observations, the CBK model predicts (1) low reactivities for unburned carbon residues extracted from commercial ash samples, (2) reactivity loss in the late stages of laboratory combustion, (3) the observed sensitivity of char reactivity to high-temperature heat treatment on second and subsecond time scales, and (4) the global reaction inhibition by mineral matter in the late stages of combustion observed in single-particle imaging studies. The model ascribes these various char deactivation phenomena to the combined effects of thermal annealing, ash inhibition, and the preferential consumption of more reactive particles (statistical kinetics), the relative contributions of which vary greatly with combustion conditions. 39 refs., 4 figs., 4 tabs., 1 app.

  1. Modeling uptake kinetics of cadmium by field-grown lettuce

    Energy Technology Data Exchange (ETDEWEB)

    Chen Weiping [Department of Environmental Sciences, University of California, 900 University Avenue, Riverside, CA 92521 (United States)], E-mail: chenweip@yahoo.com.cn; Li Lianqing [Institute of Resources, Ecosystem and Environment of Agriculture, Nanjing Agricultural University, Nanjing 210095 (China); Chang, Andrew C.; Wu Laosheng [Department of Environmental Sciences, University of California, 900 University Avenue, Riverside, CA 92521 (United States); Kwon, Soon-Ik [Agricultural Environmental and Ecology Division, National Institute of Agricultural Science and Technology, Suwon 441-707 (Korea, Republic of); Bottoms, Rick [Desert Research and Extension Center, 1004 East Holton Road, El Centro, CA 92243 (United States)

    2008-03-15

    Cadmium uptake by field grown Romaine lettuce treated with P-fertilizers of different Cd levels was investigated over an entire growing season. Results indicated that the rate of Cd uptake at a given time of the season can be satisfactorily described by the Michaelis-Menten kinetics, that is, plant uptake increases as the Cd concentration in soil solution increases, and it gradually approaches a saturation level. However, the rate constant of the Michaelis-Menten kinetics changes over the growing season. Under a given soil Cd level, the cadmium content in plant tissue decreases exponentially with time. To account for the dynamic nature of Cd uptake, a kinetic model integrating the time factor was developed to simulate Cd plant uptake over the growing season: C{sub Plant} = C{sub Solution} . PUF{sub max} . exp[-b . t], where C{sub Plant} and C{sub Solution} refer to the Cd content in plant tissue and soil solution, respectively, PUF{sub max} and b are kinetic constants. - A kinetic model was developed to evaluate the uptake of Cd under field conditions.

  2. A physical model of nicotinic ACh receptor kinetics

    OpenAIRE

    Nurowska, Ewa; Bratiichuk, Mykola; Dworakowska, Beata; Nowak, Roman J.

    2008-01-01

    We present a new approach to nicotinic receptor kinetics and a new model explaining random variabilities in the duration of open events. The model gives new interpretation on brief and long receptor openings and predicts (for two identical binding sites) the presence of three components in the open time distribution: two brief and a long. We also present the physical model of the receptor block. This picture naturally and universally explains receptor desensitization, the phenomenon of centra...

  3. A Discrete Velocity Traffic Kinetic Model Including Desired Speed

    Directory of Open Access Journals (Sweden)

    Shoufeng Lu

    2013-05-01

    Full Text Available We introduce the desired speed variable into the table of games and formulate a new table of games and the corresponding discrete traffic kinetic model. We use the hybrid programming technique of VB and MATLAB to develop the program. Lastly, we compared the proposed model result and the detector data. The results show that the proposed model can describe the traffic flow evolution.

  4. Exploring the chemical kinetics of partially oxidized intermediates by combining experiments, theory, and kinetic modeling.

    Science.gov (United States)

    Hoyermann, Karlheinz; Mauß, Fabian; Olzmann, Matthias; Welz, Oliver; Zeuch, Thomas

    2017-07-19

    Partially oxidized intermediates play a central role in combustion and atmospheric chemistry. In this perspective, we focus on the chemical kinetics of alkoxy radicals, peroxy radicals, and Criegee intermediates, which are key species in both combustion and atmospheric environments. These reactive intermediates feature a broad spectrum of chemical diversity. Their reactivity is central to our understanding of how volatile organic compounds are degraded in the atmosphere and converted into secondary organic aerosol. Moreover, they sensitively determine ignition timing in internal combustion engines. The intention of this perspective article is to provide the reader with information about the general mechanisms of reactions initiated by addition of atomic and molecular oxygen to alkyl radicals and ozone to alkenes. We will focus on critical branching points in the subsequent reaction mechanisms and discuss them from a consistent point of view. As a first example of our integrated approach, we will show how experiment, theory, and kinetic modeling have been successfully combined in the first infrared detection of Criegee intermediates during the gas phase ozonolysis. As a second example, we will examine the ignition timing of n-heptane/air mixtures at low and intermediate temperatures. Here, we present a reduced, fuel size independent kinetic model of the complex chemistry initiated by peroxy radicals that has been successfully applied to simulate standard n-heptane combustion experiments.

  5. A Kinetic Model for Vapor-liquid Flows

    Science.gov (United States)

    2005-07-13

    A Kinetic Model for Vapor-liquid Flows Aldo Frezzotti, Livio Gibelli and Silvia Lorenzani Dipartimento di Matematica del Politecnico di Milano Piazza...ES) Dipartimento di Matematica del Politecnico di Milano Piazza Leonardo da Vinci 32 - 20133 Milano - Italy 8. PERFORMING ORGANIZATION REPORT NUMBER

  6. Development of simple kinetic models and parameter estimation for ...

    African Journals Online (AJOL)

    PANCHIGA

    Key words: Exponential feed, growth modeling, Monod kinetic equation, Pichia pastoris, recombinant human ... Author(s) agree that this article remains permanently open access under the terms of the Creative Commons .... Methanol was the only energy and carbon source ..... A potential explanation for the decline in cell.

  7. Commute Maps: Separating Slowly Mixing Molecular Configurations for Kinetic Modeling.

    Science.gov (United States)

    Noé, Frank; Banisch, Ralf; Clementi, Cecilia

    2016-11-08

    Identification of the main reaction coordinates and building of kinetic models of macromolecular systems require a way to measure distances between molecular configurations that can distinguish slowly interconverting states. Here we define the commute distance that can be shown to be closely related to the expected commute time needed to go from one configuration to the other, and back. A practical merit of this quantity is that it can be easily approximated from molecular dynamics data sets when an approximation of the Markov operator eigenfunctions is available, which can be achieved by the variational approach to approximate eigenfunctions of Markov operators, also called variational approach of conformation dynamics (VAC) or the time-lagged independent component analysis (TICA). The VAC or TICA components can be scaled such that a so-called commute map is obtained in which Euclidean distance corresponds to the commute distance, and thus kinetic models such as Markov state models can be computed based on Euclidean operations, such as standard clustering. In addition, the distance metric gives rise to a quantity we call total kinetic content, which is an excellent score to rank input feature sets and kinetic model quality.

  8. Estimation of Kinetic Parameters in an Automotive SCR Catalyst Model

    DEFF Research Database (Denmark)

    Åberg, Andreas; Widd, Anders; Abildskov, Jens;

    2016-01-01

    A challenge during the development of models for simulation of the automotive Selective Catalytic Reduction catalyst is the parameter estimation of the kinetic parameters, which can be time consuming and problematic. The parameter estimation is often carried out on small-scale reactor tests, or p...

  9. Towards cleaner combustion engines through groundbreaking detailed chemical kinetic models.

    Science.gov (United States)

    Battin-Leclerc, Frédérique; Blurock, Edward; Bounaceur, Roda; Fournet, René; Glaude, Pierre-Alexandre; Herbinet, Olivier; Sirjean, Baptiste; Warth, V

    2011-09-01

    In the context of limiting the environmental impact of transportation, this critical review discusses new directions which are being followed in the development of more predictive and more accurate detailed chemical kinetic models for the combustion of fuels. In the first part, the performance of current models, especially in terms of the prediction of pollutant formation, is evaluated. In the next parts, recent methods and ways to improve these models are described. An emphasis is given on the development of detailed models based on elementary reactions, on the production of the related thermochemical and kinetic parameters, and on the experimental techniques available to produce the data necessary to evaluate model predictions under well defined conditions (212 references). This journal is © The Royal Society of Chemistry 2011

  10. Second order kinetic Kohn-Sham lattice model

    CERN Document Server

    Solorzano, Sergio; Herrmann, Hans

    2016-01-01

    In this work we introduce a new semi-implicit second order correction scheme to the kinetic Kohn-Sham lattice model. The new approach is validated by performing realistic exchange-correlation energy calculations of atoms and dimers of the first two rows of the periodic table finding good agreement with the expected values. Additionally we simulate the ethane molecule where we recover the bond lengths and compare the results with standard methods. Finally, we discuss the current applicability of pseudopotentials within the lattice kinetic Kohn-Sham approach.

  11. Chemical kinetics and combustion modelling with CFX 4

    Energy Technology Data Exchange (ETDEWEB)

    Stopford, P. [AEA Technology, Computational Fluid Dynamics Services Harwell, Oxfordshire (United Kingdom)

    1997-12-31

    The presentation describes some recent developments in combustion and kinetics models used in the CFX software of AEA Technology. Three topics are highlighted: the development of coupled solvers in a traditional `SIMPLE`-based CFD code, the use of detailed chemical kinetics mechanism via `look-up` tables and the application of CFD to large-scale multi-burner combustion plant. The aim is identify those physical approximations and numerical methods that are likely to be most useful in the future and those areas where further developments are required. (author) 6 refs.

  12. Kinetics and modeling of anaerobic digestion process

    DEFF Research Database (Denmark)

    2003-01-01

    Anaerobic digestion modeling started in the early 1970s when the need for design and efficient operation of anaerobic systems became evident. At that time not only was the knowledge about the complex process of anaerobic digestion inadequate but also there were computational limitations. Thus...

  13. Laplace transform in tracer kinetic modeling

    Energy Technology Data Exchange (ETDEWEB)

    Hauser, Eliete B., E-mail: eliete@pucrs.br [Instituto do Cerebro (InsCer/FAMAT/PUC-RS), Porto Alegre, RS, (Brazil). Faculdade de Matematica

    2013-07-01

    The main objective this paper is to quantify the pharmacokinetic processes: absorption, distribution and elimination of radiopharmaceutical(tracer), using Laplace transform method. When the drug is administered intravenously absorption is complete and is available in the bloodstream to be distributed throughout the whole body in all tissues and fluids, and to be eliminated. Mathematical modeling seeks to describe the processes of distribution and elimination through compartments, where distinct pools of tracer (spatial location or chemical state) are assigned to different compartments. A compartment model is described by a system of differential equations, where each equation represents the sum of all the transfer rates to and from a specific compartment. In this work a two-tissue irreversible compartment model is used for description of tracer, [{sup 18}F]2-fluor-2deoxy-D-glucose. In order to determine the parameters of the model, it is necessary to have information about the tracer delivery in the form of an input function representing the time-course of tracer concentration in arterial blood or plasma. We estimate the arterial input function in two stages and apply the Levenberg-Marquardt Method to solve nonlinear regressions. The transport of FDG across de arterial blood is very fast in the first ten minutes and then decreases slowly. We use de Heaviside function to represent this situation and this is the main contribution of this study. We apply the Laplace transform and the analytical solution for two-tissue irreversible compartment model is obtained. The only approach is to determinate de arterial input function. (author)

  14. Ensemble Kinetic Modeling of Metabolic Networks from Dynamic Metabolic Profiles

    Directory of Open Access Journals (Sweden)

    Gengjie Jia

    2012-11-01

    Full Text Available Kinetic modeling of metabolic pathways has important applications in metabolic engineering, but significant challenges still remain. The difficulties faced vary from finding best-fit parameters in a highly multidimensional search space to incomplete parameter identifiability. To meet some of these challenges, an ensemble modeling method is developed for characterizing a subset of kinetic parameters that give statistically equivalent goodness-of-fit to time series concentration data. The method is based on the incremental identification approach, where the parameter estimation is done in a step-wise manner. Numerical efficacy is achieved by reducing the dimensionality of parameter space and using efficient random parameter exploration algorithms. The shift toward using model ensembles, instead of the traditional “best-fit” models, is necessary to directly account for model uncertainty during the application of such models. The performance of the ensemble modeling approach has been demonstrated in the modeling of a generic branched pathway and the trehalose pathway in Saccharomyces cerevisiae using generalized mass action (GMA kinetics.

  15. Intrinsic Kinetic Modeling of Thermal Dimerization of C5 Fraction

    Institute of Scientific and Technical Information of China (English)

    Guo Liang; Wang Tiefeng; Li Dongfeng; Wang Jinfu

    2016-01-01

    This work aims to investigate the intrinsic kinetics of thermal dimerization of C5 fraction in the reactive distilla-tion process. Experiments are conducted in an 1000-mL stainless steel autoclave under some selected design conditions. By means of the weighted least squares method, the intrinsic kinetics of thermal dimerization of C5 fraction is established, and the corresponding pre-exponential factor as well as the activation energy are determined. For example, the pre-exponential factor A is equal to 4.39×105 and the activation energy Ea is equal to 6.58×104 J/mol for the cyclopentadiene dimerization re-action. The comparison between the experimental and calculated results shows that the kinetics model derived in this work is accurate and reliable, which can be used in the design of reactive distillation columns.

  16. Kinetics of Model Reactions for Interfacial Polymerization

    Directory of Open Access Journals (Sweden)

    Henry Hall

    2012-02-01

    Full Text Available To model the rates of interfacial polycondensations, the rates of reaction of benzoyl chloride and methyl chloroformate with various aliphatic monoamines in acetonitrile were determined at 25 °C. Buffering with picric acid slowed these extremely fast reactions so the rate constants could be determined from the rate of disappearance of picrate ion. The rates of the amine reactions correlated linearly with their Swain-Scott nucleophilicities.

  17. Thermodynamic and kinetic modeling of transcriptional pausing

    OpenAIRE

    Tadigotla, Vasisht R.; Maoiléidigh, Dáibhid Ó; Sengupta, Anirvan M.; Epshtein, Vitaly; Ebright, Richard H.; Nudler, Evgeny; Ruckenstein, Andrei E.

    2006-01-01

    We present a statistical mechanics approach for the prediction of backtracked pauses in bacterial transcription elongation derived from structural models of the transcription elongation complex (EC). Our algorithm is based on the thermodynamic stability of the EC along the DNA template calculated from the sequence-dependent free energy of DNA–DNA, DNA–RNA, and RNA–RNA base pairing associated with (i) the translocational and size fluctuations of the transcription bubble; (ii) changes in the as...

  18. Homogeneous gas phase models of relaxation kinetics in neon afterglow

    Directory of Open Access Journals (Sweden)

    Marković Vidosav Lj.

    2007-01-01

    Full Text Available The homogeneous gas phase models of relaxation kinetics (application of the gas phase effective coefficients to represent surface losses are applied for the study of charged and neutral active particles decay in neon afterglow. The experimental data obtained by the breakdown time delay measurements as a function of the relaxation time td (τ (memory curve is modeled in early, as well as in late afterglow. The number density decay of metastable states can explain neither the early, nor the late afterglow kinetics (memory effect, because their effective lifetimes are of the order of milliseconds and are determined by numerous collision quenching processes. The afterglow kinetics up to hundreds of milliseconds is dominated by the decay of molecular neon Ne2 + and nitrogen ions N2 + (present as impurities and the approximate value of N2 + ambipolar diffusion coefficient is determined. After the charged particle decay, the secondary emitted electrons from the surface catalyzed excitation of nitrogen atoms on the cathode determine the breakdown time delay down to the cosmic rays and natural radioactivity level. Due to the neglecting of number density spatial profiles, the homogeneous gas phase models give only the approximate values of the corresponding coefficients, but reproduce correctly other characteristics of afterglow kinetics from simple fits to the experimental data.

  19. Enzymatic hydrolysis of protein:mechanism and kinetic model

    Institute of Scientific and Technical Information of China (English)

    Qi Wei; He Zhimin

    2006-01-01

    The bioreaction mechanism and kinetic behavior of protein enzymatic hydrolysis for preparing active peptides were investigated to model and characterize the enzymatic hydrolysis curves.Taking into account single-substrate hydrolysis,enzyme inactivation and substrate or product inhibition,the reaction mechanism could be deduced from a series of experimental results carried out in a stirred tank reactor at different substrate concentrations,enzyme concentrations and temperatures based on M-M equation.An exponential equation dh/dt = aexp(-bh) was also established,where parameters a and b have different expressions according to different reaction mechanisms,and different values for different reaction systems.For BSA-trypsin model system,the regressive results agree with the experimental data,i.e.the average relative error was only 4.73%,and the reaction constants were determined as Km = 0.0748 g/L,Ks = 7.961 g/L,kd = 9.358/min,k2 =38.439/min,Ea= 64.826 kJ/mol,Ed= 80.031 kJ/mol in accordance with the proposed kinetic mode.The whole set of exponential kinetic equations can be used to model the bioreaction process of protein enzymatic hydrolysis,to calculate the thermodynamic and kinetic constants,and to optimize the operating parameters for bioreactor design.

  20. Vlasov models for kinetic Weibel-type instabilities

    Science.gov (United States)

    Ghizzo, A.; Sarrat, M.; Del Sarto, D.

    2017-02-01

    The Weibel instability, driven by a temperature anisotropy, is investigated within different kinetic descriptions based on the semi-Lagrangian full kinetic and relativistic Vlasov-Maxwell model, on the multi-stream approach, which is based on a Hamiltonian reduction technique, and finally, with the full pressure tensor fluid-type description. Dispersion relations of the Weibel instability are derived using the three different models. A qualitatively different regime is observed in Vlasov numerical experiments depending on the excitation of a longitudinal plasma electric field driven initially by the combined action of the stream symmetry breaking and weak relativistic effects, in contrast with the existing theories of the Weibel instability based on their purely transverse characters. The multi-stream model offers an alternate way to simulate easily the coupling with the longitudinal electric field and particularly the nonlinear regime of saturation, making numerical experiments more tractable, when only a few moments of the distribution are considered. Thus a numerical comparison between the reduced Hamiltonian model (the multi-stream model) and full kinetic (relativistic) Vlasov simulations has been investigated in that regime. Although nonlinear simulations of the fluid model, including the dynamics of the pressure tensor, have not been carried out here, the model is strongly relevant even in the three-dimensional case.

  1. Developments in kinetic modelling of chalcocite particle oxidation

    Energy Technology Data Exchange (ETDEWEB)

    Jaervi, J.; Ahokainen, T.; Jokilaakso, A. [Helsinki Univ. of Technology, Otaniemi (Finland). Lab. of Materials Processing and Powder Metallurgy

    1997-12-31

    A mathematical model for simulating chalcocite particle oxidation is presented. Combustion of pure chalcocite with oxygen is coded as a kinetic module which can be connected as a separate part of commercial CFD-package, PHOENICS. Heat transfer, fluid flow and combustion phenomena can be simulated using CFD-calculation together with the kinetic model. Interaction between gas phase and particles are taken into account by source terms. The aim of the kinetic model is to calculate the particle temperature, contents of species inside the particle, oxygen consumption and formation of sulphur dioxide. Four oxidation reactions are considered and the shrinking core model is used to describe the rate of the oxidation reactions. The model is verified by simulating the particle oxidation reactions in a laboratory scale laminar-flow furnace under different conditions and the model predicts the effects of charges correctly. In the future, the model validation will be done after experimental studies in the laminar flow-furnace. (author) 18 refs.

  2. Modeling Kinetics of Distortion in Porous Bi-layered Structures

    DEFF Research Database (Denmark)

    Tadesse Molla, Tesfaye; Frandsen, Henrik Lund; Bjørk, Rasmus;

    2013-01-01

    Shape distortions during constrained sintering experiment of bi-layer porous and dense cerium gadolinium oxide (CGO) structures have been modeled. Technologies like solid oxide fuel cells require co-firing thin layers with different green densities, which often exhibit differential shrinkage...... because of different sintering rates of the materials resulting in undesired distortions of the component. An analytical model based on the continuum theory of sintering has been developed to describe the kinetics of densification and distortion in the sintering processes. A new approach is used...... to extract the material parameters controlling shape distortion through optimizing the model to experimental data of free shrinkage strains. The significant influence of weight of the sample (gravity) on the kinetics of distortion is taken in to consideration. The modeling predictions indicate good agreement...

  3. Chemistry Resolved Kinetic Flow Modeling of TATB Based Explosives

    Energy Technology Data Exchange (ETDEWEB)

    Vitello, P A; Fried, L E; Howard, W M; Levesque, G; Souers, P C

    2011-07-21

    Detonation waves in insensitive, TATB based explosives are believed to have multi-time scale regimes. The initial burn rate of such explosives has a sub-microsecond time scale. However, significant late-time slow release in energy is believed to occur due to diffusion limited growth of carbon. In the intermediate time scale concentrations of product species likely change from being in equilibrium to being kinetic rate controlled. They use the thermo-chemical code CHEETAH linked to an ALE hydrodynamics code to model detonations. They term their model chemistry resolved kinetic flow as CHEETAH tracks the time dependent concentrations of individual species in the detonation wave and calculates EOS values based on the concentrations. A HE-validation suite of model simulations compared to experiments at ambient, hot, and cold temperatures has been developed. They present here a new rate model and comparison with experimental data.

  4. Ab initio and kinetic modeling studies of formic acid oxidation

    DEFF Research Database (Denmark)

    Marshall, Paul; Glarborg, Peter

    2015-01-01

    A detailed chemical kinetic model for oxidation of formic acid (HOCHO) in flames has been developed, based on theoretical work and data from literature. Ab initio calculations were used to obtain rate coefficients for reactions of HOCHO with H, O, and HO2. Modeling predictions with the mechanism...... as the fate of HOCO, determines the oxidation rate of formic acid. At lower temperatures HO2, formed from HOCO + O2, is an important chain carrier and modeling predictions become sensitive to the HOCHO + HO2 reaction. © 2014 The Combustion Institute....... on calculations with the kinetic model. Formic acid is consumed mainly by reaction with OH, yielding OCHO, which dissociates rapidly to CO2 + H, and HOCO, which may dissociate to CO + OH or CO2 + H, or react with H, OH, or O2 to form more stable products. The branching fraction of the HOCHO + OH reaction, as well...

  5. Kinetic model for the pathogenesis of radiation lung damage

    Energy Technology Data Exchange (ETDEWEB)

    Collis, C.H. (Institute of Cancer Research, Sutton (UK). Surrey Branch)

    1982-09-01

    The development of radiation-induced lung damage can be explained by a kinetic model, based on the assumption that this damage becomes manifest only when a critical proportion (K) of essential cells have ceased to function, and that the rate of loss of these cells following irradiation is linear and dose-dependent. The kinetic model relates the surviving fraction to the time to manifestation of radiation-induced lung damage and to constants, K and the cell cycle time, T. Predictions made from the model about the nature of the response to irradiation are, for the most part, fulfilled. The model can also be used to interpret the response to combined treatment with irradiation and cytotoxic drugs, including the much earlier manifestation of lung damage sometimes seen with such treatment.

  6. Study on Kinetics for Desulfurization of Model Diesel

    Institute of Scientific and Technical Information of China (English)

    Qian Jianhua; Zhou Yuenan; Liu Lin; Wang Yue; Xing Jinjuan; Lü Hong

    2009-01-01

    In this study, by means of the experiments for desulfurization of model diesel through oxi-dative extraction, the changes associated with the rate of desulfurization of diesel and the mechanism for oxidation of sulfides in diesel were explored. Through studying the mechanism for oxidation of sulfides and the principle of solvent extraction, the kinetic equation of desulfurization via oxidative extraction were determined. By means of the evaluation of model parameters and curve fitting, the reaction order between organic sulfide and sulfone, the intrinsic oxidation rate constant of organic sulfide and sulfone, and the equilibrium constant between suifone in model diesel and extractive sol-vent were determined. The experimental values of the desulfurization rate and the theoretical values of the corresponding model equation had closely demonstrated that the desulfurization reaction rate had high accuracy. And the reaction kinetics could provide an important basis for diesel desulfurization process in the future.

  7. Cleaner combustion developing detailed chemical kinetic models

    CERN Document Server

    Battin-Leclerc, Frédérique; Blurock, Edward

    2013-01-01

    This overview compiles the on-going research in Europe to enlarge and deepen the understanding of the reaction mechanisms and pathways associated with the combustion of an increased range of fuels. Focus is given to the formation of a large number of hazardous minor pollutants and the inability of current combustion models to predict the  formation of minor products such as alkenes, dienes, aromatics, aldehydes and soot nano-particles which have a deleterious impact on both the environment and on human health. Cleaner Combustion describes, at a fundamental level, the reactive chemistry of min

  8. Kinetic modelling of molecular hydrogen transport in microporous carbon materials.

    Science.gov (United States)

    Hankel, Marlies; Zhang, Hong; Nguyen, Thanh X; Bhatia, Suresh K; Gray, Stephen K; Smith, Sean C

    2011-05-07

    The proposal of kinetic molecular sieving of hydrogen isotopes is explored by employing statistical rate theory methods to describe the kinetics of molecular hydrogen transport in model microporous carbon structures. A Lennard-Jones atom-atom interaction potential is utilized for the description of the interactions between H(2)/D(2) and the carbon framework, while the requisite partition functions describing the thermal flux of molecules through the transition state are calculated quantum mechanically in view of the low temperatures involved in the proposed kinetic molecular sieving application. Predicted kinetic isotope effects for initial passage from the gas phase into the first pore mouth are consistent with expectations from previous modeling studies, namely, that at sufficiently low temperatures and for sufficiently narrow pore mouths D(2) transport is dramatically favored over H(2). However, in contrast to expectations from previous modeling, the absence of any potential barrier along the minimum energy pathway from the gas phase into the first pore mouth yields a negative temperature dependence in the predicted absolute rate coefficients-implying a negative activation energy. In pursuit of the effective activation barrier, we find that the minimum potential in the cavity is significantly higher than in the pore mouth for nanotube-shaped models, throwing into question the common assumption that passage through the pore mouths should be the rate-determining step. Our results suggest a new mechanism that, depending on the size and shape of the cavity, the thermal activation barrier may lie in the cavity rather than at the pore mouth. As a consequence, design strategies for achieving quantum-mediated kinetic molecular sieving of H(2)/D(2) in a microporous membrane will need, at the very least, to take careful account of cavity shape and size in addition to pore-mouth size in order to ensure that the selective step, namely passage through the pore mouth, is also

  9. Agent dynamics in kinetic models of wealth exchange

    CERN Document Server

    Chatterjee, Arnab

    2010-01-01

    We study the dynamics of individual agents in some kinetic models of wealth exchange, particularly, the models with savings. For the model with uniform savings, agents perform simple random walks in the `"wealth space". On the other hand, we observe ballistic diffusion in the model with distributed savings. There is an associated skewness in the gain-loss distribution which explains the steady state behavior in such models. We find that in general an agent gains while interacting with an agent with a larger saving propensity.

  10. Extraction of lycopene from tomato processing waste: kinetics and modelling.

    Science.gov (United States)

    Poojary, Mahesha M; Passamonti, Paolo

    2015-04-15

    Lycopene, a nutraceutical compound, was extracted from tomato processing waste, an abundantly available food industry by-product in Italy. The extraction kinetics was mathematically described using the first order kinetic model, the mass transfer model and Peleg's model to understand the physicochemical behaviour of the extraction. Samples were extracted using acetone/n-hexane mixtures at different ratios (1:3, 2:2 and 3:1, v/v) and at different temperatures (30, 40 and 50 °C) and simultaneously analysed using UV-VIS spectrophotometry. The lycopene yield was in the range 3.47-4.03 mg/100g, which corresponds to a percentage recovery of 65.22-75.75. All kinetic models gave a good fit to the experimental data, but the best one was Peleg's model, having the highest RAdj(2) and the lowest RMSE, MBE and χ(2) values. All the models confirmed that a temperature of 30 °C and solvent mixture of acetone/n-hexane 1:3 (v/v) provided optimal conditions for extraction of lycopene.

  11. Construction of reduced transport model by gyro-kinetic simulation with kinetic electrons in helical plasmas

    Science.gov (United States)

    Toda, S.; Nakata, M.; Nunami, M.; Ishizawa, A.; Watanabe, T.-H.; Sugama, H.

    2016-10-01

    A reduced model of the turbulent ion heat diffusivity is proposed by the gyrokinetic simulation code (GKV-X) with the adiabatic electrons for the high-Ti Large Helical Device discharge. The plasma parameter region of the short poloidal wavelength is studied, where the ion temperature gradient mode becomes unstable. The ion heat diffusivity by the nonlinear simulation with the kinetic electrons is found to be several times larger than the simulation results using the adiabatic electrons in the radial region 0.46 ion energy flux. The model of the turbulent diffusivity is derived as the function of the squared electrostatic potential fluctuation and the squared zonal flow potential. Next, the squared electrostatic potential fluctuation is approximated with the mixing length estimate. The squared zonal flow potential fluctuation is shown as the linear zonal flow response function. The reduced model of the turbulent diffusivity is derived as the function of the physical parameters by the linear GKV-X simulation with the kinetic electrons. This reduced model is applied to the transport code with the same procedure as.

  12. Kinetic Model of Biodiesel Processing Using Ultrasound

    Directory of Open Access Journals (Sweden)

    Bambang Susilo

    2009-04-01

    Full Text Available Ultrasound is predicted to be able to accelerate the chemical reaction, to increase the conversion of plant oil into biodiesel, and to decrease the need of catalyst and energy input. The application of ultrasound for processing of biodiesel and the mathematical model were conducted in this research. The result of the experiments showed that the ultrasound increased reaction rate and the conversion of palm oil into biodiesel up to 100%. It was better than the process with mechanical stirrer that the conversion was just 96%. The duration to complete the process using ultrasound was 1 minute. It was 30 to 120 times faster than that with mechanical stirrer. Ultrasound transforms mechanical energy into inner energy of the fluids and causes an increasing of temperature. Simultaneously, natural mixing process undergo because of acoustic circulation. Simulation with experiment data showed that the acceleration of transesterification with ultrasound was affected not only by natural mixing and increasing temperature. The cavitation, surface tension of micro bubble, and hot spot accelerate chemical reaction. In fact, transesterification of palm oil with ultrasound still needs catalyst. It needs only about 20% of catalyst compared to the process with mechanical stirrer.

  13. Kinetic model of induced codeposition of Ni-Mo alloys

    Institute of Scientific and Technical Information of China (English)

    ZENG, Yue; MA, Ming; XIAO, Xiao-Ming; LI, Ze-Lin; LIAN, Shi-Xun; ZHOU, Shao-Min

    2000-01-01

    The kinetic model of induced codeposition of nickel-molybdenum alloys from ammoniun citrate solution was studied on rotating disk electrodes to predict the behavior of the electrodeposition. Ihe molybdate (MoO42-) could be firstly electrochemically reduced to MoO2, and subsequently undergoes a chemical reduction with atomic hydrogen previously adsorbed on the inducing metal nickel to form molybdenum in alloys.The kinetic equations were derived, and the kinetic parameters were obtained from a comparison of experimental results and the kinetic equations. The electrochemical rate constants for discharge of nickel, molybdenum and water could been expressed as k1 ( E ) = 1. 23 × 10-9 CNexp( - 0. 198FE/ RT )mol/(dm2. s), k2 (E) = 3.28 × 10-10 CMoexp ( - 0.208FE/RT) mol/(dm2·s) and k3(E) = 1.27 × 10-6exp( - 0.062FE/RT) mol/(dm2 ·s), where CN and CMo are the concentrations of the nickel ion and molybdate, respectively, and E is the applied potential vs, saturated calornel electrode (SCE).The codeposition process could be well simulated by this model.

  14. Exploring the metabolic network of the epidemic pathogen Burkholderia cenocepacia J2315 via genome-scale reconstruction

    Directory of Open Access Journals (Sweden)

    Panda Gurudutta

    2011-05-01

    Full Text Available Abstract Background Burkholderia cenocepacia is a threatening nosocomial epidemic pathogen in patients with cystic fibrosis (CF or a compromised immune system. Its high level of antibiotic resistance is an increasing concern in treatments against its infection. Strain B. cenocepacia J2315 is the most infectious isolate from CF patients. There is a strong demand to reconstruct a genome-scale metabolic network of B. cenocepacia J2315 to systematically analyze its metabolic capabilities and its virulence traits, and to search for potential clinical therapy targets. Results We reconstructed the genome-scale metabolic network of B. cenocepacia J2315. An iterative reconstruction process led to the establishment of a robust model, iKF1028, which accounts for 1,028 genes, 859 internal reactions, and 834 metabolites. The model iKF1028 captures important metabolic capabilities of B. cenocepacia J2315 with a particular focus on the biosyntheses of key metabolic virulence factors to assist in understanding the mechanism of disease infection and identifying potential drug targets. The model was tested through BIOLOG assays. Based on the model, the genome annotation of B. cenocepacia J2315 was refined and 24 genes were properly re-annotated. Gene and enzyme essentiality were analyzed to provide further insights into the genome function and architecture. A total of 45 essential enzymes were identified as potential therapeutic targets. Conclusions As the first genome-scale metabolic network of B. cenocepacia J2315, iKF1028 allows a systematic study of the metabolic properties of B. cenocepacia and its key metabolic virulence factors affecting the CF community. The model can be used as a discovery tool to design novel drugs against diseases caused by this notorious pathogen.

  15. Kinetic model of the Buyers’ market

    Science.gov (United States)

    Zhykharsky, Alexander V.

    2013-09-01

    In this work the following results are received. The closed mathematical apparatus describing the process of interaction of the Buyers’ market with retail Shop is created. The “statistical analogy” between the vacuum electrostatic diode and the Buyers’ market co-operating with retail Shop is considered. On the basis of the spent analysis the closed mathematical apparatus describing process of interaction of the Buyers’ market with retail Shop is created. The analytical expressions connecting a stream of Buyers, come to Shop, and a stream of the gain of Shop, with parameters of the Buyers’ market are received. For check of adequacy of the received model it is solved of some real “market” problems. On the basis of the spent researches principles of construction of Information-analytical Systems of new type which provide direct measurements of parameters of the Buyers’ market are developed. Actually these Systems are devices for measurement of parameters of this market. In this work it is shown that by means of the device developed for measurement of parameters of the Buyers’ market, creation of a new science-“demandodynamics” the Buyers’ market, is possible. Here the term “demandodynamics the Buyers’ market” is accepted by analogy to the term “thermodynamics” in physics. (In this work it is shown that for the Buyers’ market concept “demand” is similar to concept “temperature” in physics.) The construction methodology “demandodynamics” the Buyers’ market is defined and is shown that within the limits of this science working out of a technique of a direct control by a condition of the Buyers’ market is possible.

  16. Kinetic models for historical processes of fast invasion and aggression

    Science.gov (United States)

    Aristov, Vladimir V.; Ilyin, Oleg V.

    2015-04-01

    In the last few decades many investigations have been devoted to theoretical models in new areas concerning description of different biological, sociological, and historical processes. In the present paper we suggest a model of the Nazi Germany invasion of Poland, France, and the USSR based on kinetic theory. We simulate this process with the Cauchy boundary problem for two-element kinetic equations. The solution of the problem is given in the form of a traveling wave. The propagation velocity of a front line depends on the quotient between initial forces concentrations. Moreover it is obtained that the general solution of the model can be expressed in terms of quadratures and elementary functions. Finally it is shown that the front-line velocities agree with the historical data.

  17. Kinetic Modeling of Paraffin Aromatization over Zeolites: A Design Perspective

    Science.gov (United States)

    Bhan, Aditya; Katare, Santhoji; Caruthers, James; Lauterbach, Jochen; Venkatasubramanian, Venkat; Delgass, Nicholas

    2002-03-01

    A generic framework for catalyst design involving the solution of a forward predictive problem using hybrid models and the inverse problem using evolutionary algorithms has been proposed. In that context, we investigate the aromatization of light paraffins over HZSM-5 to obtain the catalyst descriptors and associated kinetic parameters that predict performance. A detailed kinetic model that can fundamentally quantify the catalytic properties of acid sites in terms of intrinsic parameters such as rate constants and activation energies of elementary steps is developed on the basis of the following types of reactions: adsorption/desorption, oligomerization/ beta-scission, hydride transfer, protolysis and aromatization. The reaction network so generated has been grouped under various reaction families taking into account the different stabilities and reactivities of the adsorbed carbenium/carbonium ions. The detailed parameterization of each reaction type, optimizing fits to data, linking catalyst descriptors to performance, and means of improving the robustness of the model will be presented.

  18. 5-Lump kinetic model for gas oil catalytic cracking

    Energy Technology Data Exchange (ETDEWEB)

    Ancheyta-Juarez, Jorge; Aguilar-Rodriguez, Enrique [Instituto Mexicano del Petroleo, Eje Central Lazaro Cardenas 152, Mexico 07730 DF (Mexico); Lopez-Isunza, Felipe [Universidad Autonoma Metropolitana-Iztapalapa, Mexico 09340 DF (Mexico)

    1999-02-22

    A new 5-lump kinetic model is proposed to describe the gas oil catalytic cracking (FCC) process. The model contains eight kinetic constants, including one for catalyst deactivation, taking into account LPG (combined C{sub 3}-C{sub 4}), dry gas (C{sub 2} and lighter) and coke yields separately from other lumps (unconverted gas oil and gasoline). Apparent activation energies were determined from experiments obtained in a microactivity reactor (MAT) at temperatures: 480C, 500C and 520C; for a catalyst-to-oil ratio of 5 using vacuum gas oil and equilibrium catalyst, both recovered from an industrial FCC unit. Product yields predicted by this model show good agreement with experimental data

  19. Pre-reheating magnetogenesis in the kinetic coupling model

    Science.gov (United States)

    Fujita, Tomohiro; Namba, Ryo

    2016-08-01

    Recent blazar observations provide growing evidence for the presence of magnetic fields in the extragalactic regions. While natural speculation is to associate the production with inflationary physics, it is known that magnetogenesis solely from inflation is quite challenging. We therefore study a model in which a noninflaton field χ coupled to the electromagnetic field through its kinetic term, -I2(χ )F2/4 , continues to move after inflation until the completion of reheating. This leads to a postinflationary amplification of the electromagnetic field. We compute all the relevant contributions to the curvature perturbation, including gravitational interactions, and impose the constraints from the CMB scalar fluctuations on the strength of magnetic fields. We, for the first time, explicitly verify both the backreaction and CMB constraints in a simple yet successful magnetogenesis scenario without invoking a dedicated low-scale inflationary model in the weak-coupling regime of the kinetic coupling model.

  20. Modelling of an ASR countercurrent pyrolysis reactor with nonlinear kinetics

    Energy Technology Data Exchange (ETDEWEB)

    Chiarioni, A.; Reverberi, A.P.; Dovi, V.G. [Universita degli Studi di Genova (Italy). Dipartimento di Ingegneria Chimica e di Processo ' G.B. Bonino' ; El-Shaarawi, A.H. [National Water Research Institute, Burlington, Ont. (Canada)

    2003-10-01

    The main objective of this work is focused on the modelling of a steady-state reactor where an automotive shredder residue (ASR) is subject to pyrolysis. The gas and solid temperature inside the reactor and the relevant density profiles of both phases are simulated for fixed values of the geometry of the apparatus and a lumped kinetic model is adopted to take into account the high heterogeneity of the ASR material. The key elements for the simulation are the inlet solid temperature and the outlet gas temperature. The problem is modelled by a system of first-order boundary-value ordinary differential equations and it is solved by means of a relaxation technique owing to the nonlinearities contained in the chemical kinetic expression. (author)

  1. Reproducing Phenomenology of Peroxidation Kinetics via Model Optimization

    Science.gov (United States)

    Ruslanov, Anatole D.; Bashylau, Anton V.

    2010-06-01

    We studied mathematical modeling of lipid peroxidation using a biochemical model system of iron (II)-ascorbate-dependent lipid peroxidation of rat hepatocyte mitochondrial fractions. We found that antioxidants extracted from plants demonstrate a high intensity of peroxidation inhibition. We simplified the system of differential equations that describes the kinetics of the mathematical model to a first order equation, which can be solved analytically. Moreover, we endeavor to algorithmically and heuristically recreate the processes and construct an environment that closely resembles the corresponding natural system. Our results demonstrate that it is possible to theoretically predict both the kinetics of oxidation and the intensity of inhibition without resorting to analytical and biochemical research, which is important for cost-effective discovery and development of medical agents with antioxidant action from the medicinal plants.

  2. Kinetic modeling of the Townsend breakdown in argon

    Energy Technology Data Exchange (ETDEWEB)

    Macheret, S. O.; Shneider, M. N. [Department of Mechanical and Aerospace Engineering, Princeton University, D-414 Engineering Quadrangle, Princeton, New Jersey 08544 (United States)

    2013-10-15

    Kinetic modeling of the Townsend breakdown in argon was performed in the “forward-back” approximation. The kinetic model was found to adequately describe the left branch of the Paschen curve, and the important role of ionization by fast ions and atoms near the cathode, as well as the increase in secondary emission coefficient in strong electric fields described in the literature, was confirmed. The modeling also showed that the electron energy distribution function develops a beam of high-energy electrons and that the runaway effect, i.e., the monotonic increase of the mean electron energy with the distance from the cathode, occurs at the left branch of the Paschen curve.

  3. Stochastic effects in a discretized kinetic model of economic exchange

    Science.gov (United States)

    Bertotti, M. L.; Chattopadhyay, A. K.; Modanese, G.

    2017-04-01

    Linear stochastic models and discretized kinetic theory are two complementary analytical techniques used for the investigation of complex systems of economic interactions. The former employ Langevin equations, with an emphasis on stock trade; the latter is based on systems of ordinary differential equations and is better suited for the description of binary interactions, taxation and welfare redistribution. We propose a new framework which establishes a connection between the two approaches by introducing random fluctuations into the kinetic model based on Langevin and Fokker-Planck formalisms. Numerical simulations of the resulting model indicate positive correlations between the Gini index and the total wealth, that suggest a growing inequality with increasing income. Further analysis shows, in the presence of a conserved total wealth, a simultaneous decrease in inequality as social mobility increases, in conformity with economic data.

  4. Kinetic modelling of enzyme inactivation Kinetics of heat inactivation of the extracellular proteinase from Pseudomonas fluorescens 22F.

    NARCIS (Netherlands)

    Schokker, E.P.

    1997-01-01

    The kinetics of heat inactivation of the extracellular proteinase from Pseudomonas fluorescens 22F was studied. It was established, by making use of kinetic modelling, that heat inactivation in the temperature range 35 - 70 °C was most likely caused by intermolecular autoproteolysis, where unfolded

  5. Ordering kinetics in model systems with inhibited interfacial adsorption

    DEFF Research Database (Denmark)

    Willart, J.-F.; Mouritsen, Ole G.; Naudts, J.

    1992-01-01

    The ordering kinetics in two-dimensional Ising-like spin moels with inhibited interfacial adsorption are studied by computer-simulation calculations. The inhibited interfacial adsorption is modeled by a particular interfacial adsorption condition on the structure of the domain wall between...... neighboring domains. This condition can be either hard, as modeled by a singularity in the domain-boundary potential, or soft, as modeled by a version of the Blume-Capel model. The results show that the effect of the steric hindrance, be it hard or soft, is only manifested in the amplitude, A...

  6. An autocatalytic kinetic model for describing microbial growth during fermentation.

    Science.gov (United States)

    Ibarz, Albert; Augusto, Pedro E D

    2015-01-01

    The mathematical modelling of the behaviour of microbial growth is widely desired in order to control, predict and design food and bioproduct processing, stability and safety. This work develops and proposes a new semi-empirical mathematical model, based on an autocatalytic kinetic, to describe the microbial growth through its biomass concentration. The proposed model was successfully validated using 15 microbial growth patterns, covering the three most important types of microorganisms in food and biotechnological processing (bacteria, yeasts and moulds). Its main advantages and limitations are discussed, as well as the interpretation of its parameters. It is shown that the new model can be used to describe the behaviour of microbial growth.

  7. Modelling on corrosion inhibitor kinetics in carbon steel pipe used in oil industry

    Science.gov (United States)

    Hasmi, A. N.; Nuraini, N.; Wahyuningrum, D.; Sumarti, N.; Bunjali, B.

    2014-02-01

    A model to explain the kinetics of corrosion inhibitor is proposed here. The model is based on Transition State Theory. Our model has many similarities with Michelis-Menten Kinetics. The kinetics difference between uninhibited corrosion and inhibited corrosion is presented. Our model showed the inhibitor could suppress the corrosion rate.

  8. Stepwise kinetic equilibrium models of quantitative polymerase chain reaction

    Directory of Open Access Journals (Sweden)

    Cobbs Gary

    2012-08-01

    Full Text Available Abstract Background Numerous models for use in interpreting quantitative PCR (qPCR data are present in recent literature. The most commonly used models assume the amplification in qPCR is exponential and fit an exponential model with a constant rate of increase to a select part of the curve. Kinetic theory may be used to model the annealing phase and does not assume constant efficiency of amplification. Mechanistic models describing the annealing phase with kinetic theory offer the most potential for accurate interpretation of qPCR data. Even so, they have not been thoroughly investigated and are rarely used for interpretation of qPCR data. New results for kinetic modeling of qPCR are presented. Results Two models are presented in which the efficiency of amplification is based on equilibrium solutions for the annealing phase of the qPCR process. Model 1 assumes annealing of complementary targets strands and annealing of target and primers are both reversible reactions and reach a dynamic equilibrium. Model 2 assumes all annealing reactions are nonreversible and equilibrium is static. Both models include the effect of primer concentration during the annealing phase. Analytic formulae are given for the equilibrium values of all single and double stranded molecules at the end of the annealing step. The equilibrium values are then used in a stepwise method to describe the whole qPCR process. Rate constants of kinetic models are the same for solutions that are identical except for possibly having different initial target concentrations. Analysis of qPCR curves from such solutions are thus analyzed by simultaneous non-linear curve fitting with the same rate constant values applying to all curves and each curve having a unique value for initial target concentration. The models were fit to two data sets for which the true initial target concentrations are known. Both models give better fit to observed qPCR data than other kinetic models present in the

  9. A Consensus Genome-scale Reconstruction of Chinese Hamster Ovary Cell Metabolism

    KAUST Repository

    Hefzi, Hooman

    2016-11-23

    Chinese hamster ovary (CHO) cells dominate biotherapeutic protein production and are widely used in mammalian cell line engineering research. To elucidate metabolic bottlenecks in protein production and to guide cell engineering and bioprocess optimization, we reconstructed the metabolic pathways in CHO and associated them with >1,700 genes in the Cricetulus griseus genome. The genome-scale metabolic model based on this reconstruction, iCHO1766, and cell-line-specific models for CHO-K1, CHO-S, and CHO-DG44 cells provide the biochemical basis of growth and recombinant protein production. The models accurately predict growth phenotypes and known auxotrophies in CHO cells. With the models, we quantify the protein synthesis capacity of CHO cells and demonstrate that common bioprocess treatments, such as histone deacetylase inhibitors, inefficiently increase product yield. However, our simulations show that the metabolic resources in CHO are more than three times more efficiently utilized for growth or recombinant protein synthesis following targeted efforts to engineer the CHO secretory pathway. This model will further accelerate CHO cell engineering and help optimize bioprocesses.

  10. Kinetic models of gene expression including non-coding RNAs

    Science.gov (United States)

    Zhdanov, Vladimir P.

    2011-03-01

    In cells, genes are transcribed into mRNAs, and the latter are translated into proteins. Due to the feedbacks between these processes, the kinetics of gene expression may be complex even in the simplest genetic networks. The corresponding models have already been reviewed in the literature. A new avenue in this field is related to the recognition that the conventional scenario of gene expression is fully applicable only to prokaryotes whose genomes consist of tightly packed protein-coding sequences. In eukaryotic cells, in contrast, such sequences are relatively rare, and the rest of the genome includes numerous transcript units representing non-coding RNAs (ncRNAs). During the past decade, it has become clear that such RNAs play a crucial role in gene expression and accordingly influence a multitude of cellular processes both in the normal state and during diseases. The numerous biological functions of ncRNAs are based primarily on their abilities to silence genes via pairing with a target mRNA and subsequently preventing its translation or facilitating degradation of the mRNA-ncRNA complex. Many other abilities of ncRNAs have been discovered as well. Our review is focused on the available kinetic models describing the mRNA, ncRNA and protein interplay. In particular, we systematically present the simplest models without kinetic feedbacks, models containing feedbacks and predicting bistability and oscillations in simple genetic networks, and models describing the effect of ncRNAs on complex genetic networks. Mathematically, the presentation is based primarily on temporal mean-field kinetic equations. The stochastic and spatio-temporal effects are also briefly discussed.

  11. Modeling organic micro pollutant degradation kinetics during sewage sludge composting.

    Science.gov (United States)

    Sadef, Yumna; Poulsen, Tjalfe Gorm; Bester, Kai

    2014-11-01

    Degradation of 13 different organic micro-pollutants in sewage sludge during aerobic composting at 5 different temperatures over a 52 day period was investigated. Adequacy of two kinetic models: a single first order, and a dual first order expression (using an early (first 7 days) and a late-time (last 45 days) degradation coefficient), for describing micro-pollutant degradation, and kinetic constant dependency on composting temperature were evaluated. The results showed that both models provide relatively good descriptions of the degradation process, with the dual first order model being most accurate. The single first order degradation coefficient was 0.025 d(-1) on average across all compounds and temperatures. At early times, degradation was about three times faster than at later times. Average values of the early and late time degradation coefficients for the dual first order model were 0.066 d(-1) and 0.022 d(-1), respectively. On average 30% of the initial micro-pollutant mass present in the compost was degraded rapidly during the early stages of the composting process. Single first order and late time dual first order kinetic constants were strongly dependent on composting temperature with maximum values at temperatures of 35-65°C. In contrast the early time degradation coefficients were relatively independent of composting temperature.

  12. A robust methodology for kinetic model parameter estimation for biocatalytic reactions

    DEFF Research Database (Denmark)

    Al-Haque, Naweed; Andrade Santacoloma, Paloma de Gracia; Lima Afonso Neto, Watson;

    2012-01-01

    Effective estimation of parameters in biocatalytic reaction kinetic expressions are very important when building process models to enable evaluation of process technology options and alternative biocatalysts. The kinetic models used to describe enzyme-catalyzed reactions generally include several...

  13. A kinetic model for the first stage of pygas upgrading

    Directory of Open Access Journals (Sweden)

    J. L. de Medeiros

    2007-03-01

    Full Text Available Pyrolysis gasoline - PYGAS - is an intermediate boiling product of naphtha steam cracking with a high octane number and high aromatic/unsaturated contents. Due to stabilization concerns, PYGAS must be hydrotreated in two stages. The first stage uses a mild trickle-bed conversion for removing extremely reactive species (styrene, dienes and olefins prior to the more severe second stage where sulfured and remaining olefins are hydrogenated in gas phase. This work addresses the reaction network and two-phase kinetic model for the first stage of PYGAS upgrading. Nonlinear estimation was used for model tuning with kinetic data obtained in bench-scale trickle-bed hydrogenation with a commercial Pd/Al2O3 catalyst. On-line sampling experiments were designed to study the influence of variables - temperature and spatial velocity - on the conversion of styrene, dienes and olefins.

  14. Stochastic kinetic models: Dynamic independence, modularity and graphs

    CERN Document Server

    Bowsher, Clive G

    2010-01-01

    The dynamic properties and independence structure of stochastic kinetic models (SKMs) are analyzed. An SKM is a highly multivariate jump process used to model chemical reaction networks, particularly those in biochemical and cellular systems. We identify SKM subprocesses with the corresponding counting processes and propose a directed, cyclic graph (the kinetic independence graph or KIG) that encodes the local independence structure of their conditional intensities. Given a partition $[A,D,B]$ of the vertices, the graphical separation $A\\perp B|D$ in the undirected KIG has an intuitive chemical interpretation and implies that $A$ is locally independent of $B$ given $A\\cup D$. It is proved that this separation also results in global independence of the internal histories of $A$ and $B$ conditional on a history of the jumps in $D$ which, under conditions we derive, corresponds to the internal history of $D$. The results enable mathematical definition of a modularization of an SKM using its implied dynamics. Gra...

  15. Kinetics approach to modeling of polymer additive degradation in lubricants

    Institute of Scientific and Technical Information of China (English)

    llyaI.KUDISH; RubenG.AIRAPETYAN; Michael; J.; COVITCH

    2001-01-01

    A kinetics problem for a degrading polymer additive dissolved in a base stock is studied.The polymer degradation may be caused by the combination of such lubricant flow parameters aspressure, elongational strain rate, and temperature as well as lubricant viscosity and the polymercharacteristics (dissociation energy, bead radius, bond length, etc.). A fundamental approach tothe problem of modeling mechanically induced polymer degradation is proposed. The polymerdegradation is modeled on the basis of a kinetic equation for the density of the statistical distribu-tion of polymer molecules as a function of their molecular weight. The integrodifferential kineticequation for polymer degradation is solved numerically. The effects of pressure, elongational strainrate, temperature, and lubricant viscosity on the process of lubricant degradation are considered.The increase of pressure promotes fast degradation while the increase of temperature delaysdegradation. A comparison of a numerically calculated molecular weight distribution with an ex-perimental one obtained in bench tests showed that they are in excellent agreement with eachother.

  16. Kinetic model of metabolic network for xiamenmycin biosynthetic optimisation.

    Science.gov (United States)

    Xu, Min-juan; Chen, Yong-cong; Xu, Jun; Ao, Ping; Zhu, Xiao-mei

    2016-02-01

    Xiamenmycins, a series of prenylated benzopyran compounds with anti-fibrotic bioactivities, were isolated from a mangrove-derived Streptomyces xiamenensis. To fulfil the requirements of pharmaceutical investigations, a high production of xiamenmycin is needed. In this study, the authors present a kinetic metabolic model to evaluate fluxes in an engineered Streptomyces lividans with xiamenmycin-oriented genetic modification based on generic enzymatic rate equations and stability constraints. Lyapunov function was used for a viability optimisation. From their kinetic model, the flux distributions for the engineered S. lividans fed on glucose and glycerol as carbon sources were calculated. They found that if the bacterium can utilise glucose simultaneously with glycerol, xiamenmycin production can be enhanced by 40% theoretically, while maintaining the same growth rate. Glycerol may increase the flux for phosphoenolpyruvate synthesis without interfering citric acid cycle. They therefore believe this study demonstrates a possible new direction for bioengineering of S. lividans.

  17. Kinetic modeling and exploratory numerical simulation of chloroplastic starch degradation

    Directory of Open Access Journals (Sweden)

    Nag Ambarish

    2011-06-01

    Full Text Available Abstract Background Higher plants and algae are able to fix atmospheric carbon dioxide through photosynthesis and store this fixed carbon in large quantities as starch, which can be hydrolyzed into sugars serving as feedstock for fermentation to biofuels and precursors. Rational engineering of carbon flow in plant cells requires a greater understanding of how starch breakdown fluxes respond to variations in enzyme concentrations, kinetic parameters, and metabolite concentrations. We have therefore developed and simulated a detailed kinetic ordinary differential equation model of the degradation pathways for starch synthesized in plants and green algae, which to our knowledge is the most complete such model reported to date. Results Simulation with 9 internal metabolites and 8 external metabolites, the concentrations of the latter fixed at reasonable biochemical values, leads to a single reference solution showing β-amylase activity to be the rate-limiting step in carbon flow from starch degradation. Additionally, the response coefficients for stromal glucose to the glucose transporter kcat and KM are substantial, whereas those for cytosolic glucose are not, consistent with a kinetic bottleneck due to transport. Response coefficient norms show stromal maltopentaose and cytosolic glucosylated arabinogalactan to be the most and least globally sensitive metabolites, respectively, and β-amylase kcat and KM for starch to be the kinetic parameters with the largest aggregate effect on metabolite concentrations as a whole. The latter kinetic parameters, together with those for glucose transport, have the greatest effect on stromal glucose, which is a precursor for biofuel synthetic pathways. Exploration of the steady-state solution space with respect to concentrations of 6 external metabolites and 8 dynamic metabolite concentrations show that stromal metabolism is strongly coupled to starch levels, and that transport between compartments serves to

  18. Controllability in hybrid kinetic equations modeling nonequilibrium multicellular systems.

    Science.gov (United States)

    Bianca, Carlo

    2013-01-01

    This paper is concerned with the derivation of hybrid kinetic partial integrodifferential equations that can be proposed for the mathematical modeling of multicellular systems subjected to external force fields and characterized by nonconservative interactions. In order to prevent an uncontrolled time evolution of the moments of the solution, a control operator is introduced which is based on the Gaussian thermostat. Specifically, the analysis shows that the moments are solution of a Riccati-type differential equation.

  19. A genome-scale metabolic reconstruction of Mycoplasma genitalium, iPS189.

    Directory of Open Access Journals (Sweden)

    Patrick F Suthers

    2009-02-01

    Full Text Available With a genome size of approximately 580 kb and approximately 480 protein coding regions, Mycoplasma genitalium is one of the smallest known self-replicating organisms and, additionally, has extremely fastidious nutrient requirements. The reduced genomic content of M. genitalium has led researchers to suggest that the molecular assembly contained in this organism may be a close approximation to the minimal set of genes required for bacterial growth. Here, we introduce a systematic approach for the construction and curation of a genome-scale in silico metabolic model for M. genitalium. Key challenges included estimation of biomass composition, handling of enzymes with broad specificities, and the lack of a defined medium. Computational tools were subsequently employed to identify and resolve connectivity gaps in the model as well as growth prediction inconsistencies with gene essentiality experimental data. The curated model, M. genitalium iPS189 (262 reactions, 274 metabolites, is 87% accurate in recapitulating in vivo gene essentiality results for M. genitalium. Approaches and tools described herein provide a roadmap for the automated construction of in silico metabolic models of other organisms.

  20. A model for recovery kinetics of aluminum after large strain

    DEFF Research Database (Denmark)

    Yu, Tianbo; Hansen, Niels

    2012-01-01

    A model is suggested to analyze recovery kinetics of heavily deformed aluminum. The model is based on the hardness of isothermal annealed samples before recrystallization takes place, and it can be extrapolated to longer annealing times to factor out the recrystallization component of the hardness...... for conditions where recovery and recrystallization overlap. The model is applied to the isothermal recovery at temperatures between 140 and 220°C of commercial purity aluminum deformed to true strain 5.5. EBSD measurements have been carried out to detect the onset of discontinuous recrystallization. Furthermore...

  1. Computation Molecular Kinetics Model of HZE Induced Cell Cycle Arrest

    Science.gov (United States)

    Cucinotta, Francis A.; Ren, Lei

    2004-01-01

    Cell culture models play an important role in understanding the biological effectiveness of space radiation. High energy and charge (HZE) ions produce prolonged cell cycle arrests at the G1/S and G2/M transition points in the cell cycle. A detailed description of these phenomena is needed to integrate knowledge of the expression of DNA damage in surviving cells, including the determination of relative effectiveness factors between different types of radiation that produce differential types of DNA damage and arrest durations. We have developed a hierarchical kinetics model that tracks the distribution of cells in various cell phase compartments (early G1, late G1, S, G2, and M), however with transition rates that are controlled by rate-limiting steps in the kinetics of cyclin-cdk's interactions with their families of transcription factors and inhibitor molecules. The coupling of damaged DNA molecules to the downstream cyclin-cdk inhibitors is achieved through a description of the DNA-PK and ATM signaling pathways. For HZE irradiations we describe preliminary results, which introduce simulation of the stochastic nature of the number of direct particle traversals per cell in the modulation of cyclin-cdk and cell cycle population kinetics. Comparison of the model to data for fibroblast cells irradiated photons or HZE ions are described.

  2. Kinetics and specificity of nickel hypersensitivity in the murine model.

    Science.gov (United States)

    Siller, G M; Seymour, G J

    1994-01-01

    Nickel contact dermatitis appears to be almost exclusively a disease of females despite the increasing exposure of males to nickel. Successful murine models of nickel allergic contact dermatitis have been described. The purpose of this study is to investigate the kinetics and specificity of the response in this model and to examine if any differences exist between male and female. Mice were sensitised epicutaneously with nickel sulphate in aqueous solution of varying concentration, volume and duration of application. Following intradermal challenge, dose dependent response kinetics which approximated linearity were demonstrated upto the point of toxicity. Sensitised mice were challenged with Cobaltous chloride, Chromic chloride and Cupric sulphate and demonstrated no evidence of cross sensitivity to cobalt or chrome. Copper produced an irritant response making interpretation difficult. Earlier and stronger responses were observed in female mice, however these differences fell short of statistical significance. The results of the present study therefore establishes a reliable model for nickel hypersensitivity, that demonstrates both specificity and dose dependent kinetics without significant sex differences.

  3. Kinetic model on coke oven gas with steam reforming

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jia-yuan; ZHOU Jie-min; YAN Hong-jie

    2008-01-01

    The effects of factors such as the molar ratio of H2O to CH4 (n(H2O)/n(CH4)), methane conversion temperature and time on methane conversion rate were investigated to build kinetic model for reforming of coke-oven gas with steam. The results of experiments show that the optimal conditions for methane conversion are that the molar ratio of H2O to CH4 varies from 1.1 to 1.3and the conversion temperature varies from 1 223 to 1 273 K. The methane conversion rate is more than 95% when the molar ratio ofH2O to CH4 is 1.2, the conversion temperature is above 1 223 K and the conversion time is longer than 0.75 s. Kinetic model of methane conversion was proposed. All results demonstrate that the calculated values by the kinetic model accord with the experimental data well, and the error is less than 1.5%.

  4. Simulation of DME synthesis from coal syngas by kinetics model

    Energy Technology Data Exchange (ETDEWEB)

    Shim, H.M.; Lee, S.J.; Yoo, Y.D.; Yun, Y.S.; Kim, H.T. [Ajou University, Suwon (Republic of Korea)

    2009-05-15

    DME (Dimethyl Ether) has emerged as a clean alternative fuel for diesel. In this study it is developed a simulation model through a kinetics model of the ASPEN plus simulator, performed to detect operating characteristics of DME direct synthesis. An overall DME synthesis process is referenced by experimental data of 3 ton/day (TPD) coal gasification pilot plant located at IAE in Korea. Supplying condition of DME synthesis model is equivalently set to 80 N/m{sup 3} of syngas which is derived from a coal gasification plant. In the simulation it is assumed that the overall DME synthesis process proceeds with steady state, vapor-solid reaction with DME catalyst. The physical properties of reactants are governed by Soave-Redlich-Kwong (SRK) EOS in this model. A reaction model of DME synthesis is considered that is applied with the LHHW (Langmuir-Hinshelwood Hougen Watson) equation as an adsorption-desorption model on the surface of the DME catalyst. After adjusting the kinetics of the DME synthesis reaction among reactants with experimental data, the kinetics of the governing reactions inner DME reactor are modified and coupled with the entire DME synthesis reaction. For validating simulation results of the DME synthesis model, the obtained simulation results are compared with experimental results: conversion ratio, DME yield and DME production rate. Then, a sensitivity analysis is performed by effects of operating variables such as pressure, temperature of the reactor, void fraction of catalyst and H{sub 2}/CO ratio of supplied syngas with modified model. According to simulation results, optimum operating conditions of DME reactor are obtained in the range of 265-275{sup o}C and 60 kg/cm{sup 2}. And DME production rate has a maximum value in the range of 1-1.5 of H{sub 2}/CO ratio in the syngas composition.

  5. Kinetic Modeling of Sunflower Grain Filling and Fatty Acid Biosynthesis

    Science.gov (United States)

    Durruty, Ignacio; Aguirrezábal, Luis A. N.; Echarte, María M.

    2016-01-01

    Grain growth and oil biosynthesis are complex processes that involve various enzymes placed in different sub-cellular compartments of the grain. In order to understand the mechanisms controlling grain weight and composition, we need mathematical models capable of simulating the dynamic behavior of the main components of the grain during the grain filling stage. In this paper, we present a non-structured mechanistic kinetic model developed for sunflower grains. The model was first calibrated for sunflower hybrid ACA855. The calibrated model was able to predict the theoretical amount of carbohydrate equivalents allocated to the grain, grain growth and the dynamics of the oil and non-oil fraction, while considering maintenance requirements and leaf senescence. Incorporating into the model the serial-parallel nature of fatty acid biosynthesis permitted a good representation of the kinetics of palmitic, stearic, oleic, and linoleic acids production. A sensitivity analysis showed that the relative influence of input parameters changed along grain development. Grain growth was mostly affected by the specific growth parameter (μ′) while fatty acid composition strongly depended on their own maximum specific rate parameters. The model was successfully applied to two additional hybrids (MG2 and DK3820). The proposed model can be the first building block toward the development of a more sophisticated model, capable of predicting the effects of environmental conditions on grain weight and composition, in a comprehensive and quantitative way. PMID:27242809

  6. Kinetic models for fermentative hydrogen production: A review

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Jianlong; Wan, Wei [Laboratory of Environmental Technology, INET, Tsinghua University, Beijing 100084 (China)

    2009-05-15

    The kinetic models were developed and applied for fermentative hydrogen production. They were used to describe the progress of a batch fermentative hydrogen production process, to investigate the effects of substrate concentration, inhibitor concentration, temperatures, pH, and dilution rates on the process of fermentative hydrogen production, and to establish the relationship among the substrate degradation rate, the hydrogen-producing bacteria growth rate and the product formation rate. This review showed that the modified Gompertz model was widely used to describe the progress of a batch fermentative hydrogen production process, while the Monod model was widely used to describe the effects of substrate concentration on the rates of substrate degradation, hydrogen-producing bacteria growth and hydrogen production. Arrhenius model was used a lot to describe the effects of temperature on fermentative hydrogen production, while modified Han-Levenspiel model was used to describe the effects of inhibitor concentration on fermentative hydrogen production. The Andrew model was used to describe the effects of H{sup +} concentration on the specific hydrogen production rate, while the Luedeking-Piret model and its modified form were widely used to describe the relationship between the hydrogen-producing bacteria growth rate and the product formation rate. Finally, some suggestions for future work with these kinetic models were proposed. (author)

  7. Recovering kinetics from a simplified protein folding model using replica exchange simulations: a kinetic network and effective stochastic dynamics.

    Science.gov (United States)

    Zheng, Weihua; Andrec, Michael; Gallicchio, Emilio; Levy, Ronald M

    2009-08-27

    We present an approach to recover kinetics from a simplified protein folding model at different temperatures using the combined power of replica exchange (RE), a kinetic network, and effective stochastic dynamics. While RE simulations generate a large set of discrete states with the correct thermodynamics, kinetic information is lost due to the random exchange of temperatures. We show how we can recover the kinetics of a 2D continuous potential with an entropic barrier by using RE-generated discrete states as nodes of a kinetic network. By choosing the neighbors and the microscopic rates between the neighbors appropriately, the correct kinetics of the system can be recovered by running a kinetic simulation on the network. We fine-tune the parameters of the network by comparison with the effective drift velocities and diffusion coefficients of the system determined from short-time stochastic trajectories. One of the advantages of the kinetic network model is that the network can be built on a high-dimensional discretized state space, which can consist of multiple paths not consistent with a single reaction coordinate.

  8. Genome-scale reconstruction of metabolic network for a halophilic extremophile, Chromohalobacter salexigens DSM 3043

    Directory of Open Access Journals (Sweden)

    Oner Ebru

    2011-01-01

    Full Text Available Abstract Background Chromohalobacter salexigens (formerly Halomonas elongata DSM 3043 is a halophilic extremophile with a very broad salinity range and is used as a model organism to elucidate prokaryotic osmoadaptation due to its strong euryhaline phenotype. Results C. salexigens DSM 3043's metabolism was reconstructed based on genomic, biochemical and physiological information via a non-automated but iterative process. This manually-curated reconstruction accounts for 584 genes, 1386 reactions, and 1411 metabolites. By using flux balance analysis, the model was extensively validated against literature data on the C. salexigens phenotypic features, the transport and use of different substrates for growth as well as against experimental observations on the uptake and accumulation of industrially important organic osmolytes, ectoine, betaine, and its precursor choline, which play important roles in the adaptive response to osmotic stress. Conclusions This work presents the first comprehensive genome-scale metabolic model of a halophilic bacterium. Being a useful guide for identification and filling of knowledge gaps, the reconstructed metabolic network iOA584 will accelerate the research on halophilic bacteria towards application of systems biology approaches and design of metabolic engineering strategies.

  9. Multiensemble Markov models of molecular thermodynamics and kinetics.

    Science.gov (United States)

    Wu, Hao; Paul, Fabian; Wehmeyer, Christoph; Noé, Frank

    2016-06-07

    We introduce the general transition-based reweighting analysis method (TRAM), a statistically optimal approach to integrate both unbiased and biased molecular dynamics simulations, such as umbrella sampling or replica exchange. TRAM estimates a multiensemble Markov model (MEMM) with full thermodynamic and kinetic information at all ensembles. The approach combines the benefits of Markov state models-clustering of high-dimensional spaces and modeling of complex many-state systems-with those of the multistate Bennett acceptance ratio of exploiting biased or high-temperature ensembles to accelerate rare-event sampling. TRAM does not depend on any rate model in addition to the widely used Markov state model approximation, but uses only fundamental relations such as detailed balance and binless reweighting of configurations between ensembles. Previous methods, including the multistate Bennett acceptance ratio, discrete TRAM, and Markov state models are special cases and can be derived from the TRAM equations. TRAM is demonstrated by efficiently computing MEMMs in cases where other estimators break down, including the full thermodynamics and rare-event kinetics from high-dimensional simulation data of an all-atom protein-ligand binding model.

  10. Kinetic models for nucleocytoplasmic transport of messenger RNA.

    Science.gov (United States)

    Schröder, H C; Müller, W E; Agutter, P S

    1995-05-21

    Much is known about the mechanism by which mRNAs cross the nuclear envelope (the translocation stage of nucleocytoplasmic transport), but far less is known about the preceding (intranuclear migration/release) and succeeding (cytoplasmic binding) stages. Therefore, existing information suffices for articulating detailed kinetic models of translocation, but not models for the overall mRNA transport process. In this paper, we show that simple kinetic models of translocation can (i) accommodate data about nucleocytoplasmic distributions of endogenous transcripts; (ii) predict the overall effects on these distributions of effectors such as insulin and epidermal growth factor; (iii) throw some light on the mechanism(s) of action of the HIV-1 protein Rev and produce experimentally testable predictions about this mechanism; and (iv) account for the action of influenza virus NS1 protein. However, the simplest forms of translocation models apparently fail to account for some properties of viral regulators such as HIV Rev and adenovirus E1B-E4 complex. To elucidate these topics, less narrowly focused models of mRNA transport are required, describing intranuclear binding/release as well as translocation. On the basis of our examination of translocation models, we suggest some criteria that the requisite broadly based models must satisfy.

  11. Study on kinetic model of microwave thermocatalytic treatment of biomass tar model compound.

    Science.gov (United States)

    Anis, Samsudin; Zainal, Z A

    2014-01-01

    Kinetic model parameters for toluene conversion under microwave thermocatalytic treatment were evaluated. The kinetic rate constants were determined using integral method based on experimental data and coupled with Arrhenius equation for obtaining the activation energies and pre-exponential factors. The model provides a good agreement with the experimental data. The kinetic model was also validated with standard error of 3% on average. The extrapolation of the model showed a reasonable trend to predict toluene conversion and product yield both in thermal and catalytic treatments. Under microwave irradiation, activation energy of toluene conversion was lower in the range of 3-27 kJ mol(-1) compared to those of conventional heating reported in the literatures. The overall reaction rate was six times higher compared to conventional heating. As a whole, the kinetic model works better for tar model removal in the absence of gas reforming within a level of reliability demonstrated in this study.

  12. Alkaline Hydrolysis Kinetics Modeling of Bagasse Pentosan Dissolution

    Directory of Open Access Journals (Sweden)

    Yuxin Liu

    2013-11-01

    Full Text Available The main pentosan components of sugarcane bagasse, which can be subjected to alkaline hydrolysis, are xylose, arabinose, glucose, and galactose. The pentosan reaction mechanism was considered for alkali-treated bagasse with variation of temperature and time. The kinetics of pentosan degradation were studied concurrently at temperatures of 50 °C, 70 °C, and 90 °C, with a solid-liquid mass ratio of 1:15, a stirring speed of 500 revolutions/min, and different holding times for bagasse alkali pre-extraction. With respect to residual pentosan content and the losses of raw material, the hydrolysis rates of alkali pre-extraction and pentosan degradation reactions of bagasse all followed pseudo-first-order kinetic models. Finally, the main degradation activation energy was determined to be 20.86 KJ/mol, and the residual degradation activation energy was 28.75 KJ/mol according to the Arrhenius equation.

  13. Kinetic modeling of ethylbenzene dehydrogenation over hydrotalcite catalysts

    KAUST Repository

    Atanda, Luqman

    2011-07-01

    Kinetics of ethylbenzene dehydrogenation to styrene was investigated over a series of quaternary mixed oxides of Mg3Fe0.25Me0.25Al0.5 (Me=Co, Mn and Ni) catalysts prepared by calcination of hydrotalcite-like compounds and compared with commercial catalyst. The study was carried out in the absence of steam using a riser simulator at 400, 450, 500 and 550°C for reaction times of 5, 10, 15 and 20s. Mg3Fe0.25Mn0.25Al0.5 afforded the highest ethylbenzene conversion of 19.7% at 550°C. Kinetic parameters for the dehydrogenation process were determined using the catalyst deactivation function based on reactant conversion model. The apparent activation energies for styrene production were found to decrease as follows: E1-Ni>E1-Co>E1-Mn. © 2011 Elsevier B.V.

  14. Kinetic modelling and mechanism of dye adsorption on unburned carbon

    Energy Technology Data Exchange (ETDEWEB)

    Wang, S.B.; Li, H.T. [Curtin University of Technology, Perth, WA (Australia). Dept. of Chemical Engineering

    2007-07-01

    Textile dyeing processes are among the most environmentally unfriendly industrial processes by producing coloured wastewaters. The adsorption method using unburned carbon from coal combustion residue was studied for the decolourisation of typical acidic and basic dyes. It was discovered that the unburned carbon showed high adsorption capacity at 1.97 x 10{sup -4} and 5.27 x 10{sup -4} mol/g for Basic Violet 3 and Acid Black 1, respectively. The solution pH, particle size and temperature significantly influenced the adsorption capacity. Higher solution pH favoured the adsorption of basic dye while reduced the adsorption of acid dye. The adsorption of dye increased with increasing temperature but decreased with increasing particle size. Sorption kinetic data indicated that the adsorption kinetics followed the pseudo-second-order model. The adsorption mechanism consisted of two processes, external diffusion and intraparticle diffusion, and the external diffusion was the dominating process.

  15. An enhanced Brinson model with modified kinetics for martensite transformation

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Young-Jin; Lee, Jung Ju [Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of); Jeong, Ju-Won [Korea Aerospace Research Institute, Daejeon (Korea, Republic of); Lim, Jae Hyuk [Chonbuk National University, Jeonju (Korea, Republic of)

    2017-03-15

    We propose an enhanced Brinson model with modified kinetics for martensite transformation. Two additional material constants are considered to follow the stress-temperature diagram above austenite start temperature (As) along with treatment to keep the continuity of the martensite volume fraction and the path dependency of the phase transformation. To demonstrate the performance of the proposed model, we implement this algorithm into ABAQUS user subroutine, then conduct several numerical simulations and compare their results with SMA wire experiments as well as those of three-dimensional SMA constitutive models. From the results, it turns out that the proposed model is as accurate as the three-dimensional models and shows better accuracy over original Brinson model in terms of recovery stress.

  16. Modeling the turbulent kinetic energy equation for compressible, homogeneous turbulence

    Science.gov (United States)

    Aupoix, B.; Blaisdell, G. A.; Reynolds, William C.; Zeman, Otto

    1990-01-01

    The turbulent kinetic energy transport equation, which is the basis of turbulence models, is investigated for homogeneous, compressible turbulence using direct numerical simulations performed at CTR. It is shown that the partition between dilatational and solenoidal modes is very sensitive to initial conditions for isotropic decaying turbulence but not for sheared flows. The importance of the dilatational dissipation and of the pressure-dilatation term is evidenced from simulations and a transport equation is proposed to evaluate the pressure-dilatation term evolution. This transport equation seems to work well for sheared flows but does not account for initial condition sensitivity in isotropic decay. An improved model is proposed.

  17. Web-based kinetic modelling using JWS Online.

    Science.gov (United States)

    Olivier, Brett G; Snoep, Jacky L

    2004-09-01

    JWS Online is a repository of kinetic models, describing biological systems, which can be interactively run and interrogated over the Internet. It is implemented using a client-server strategy where the clients, in the form of web browser based Java applets, act as a graphical interface to the model servers, which perform the required numerical computations. The JWS Online website is publicly accessible at http://jjj.biochem.sun.ac.za/ with mirrors at http://www.jjj.bio.vu.nl/ and http://jjj.vbi.vt.edu/

  18. Kinetic model for microbial growth and desulphurisation with Enterobacter sp.

    Science.gov (United States)

    Liu, Long; Guo, Zhiguo; Lu, Jianjiang; Xu, Xiaolin

    2015-02-01

    Biodesulphurisation was investigated by using Enterobacter sp. D4, which can selectively desulphurise and convert dibenzothiophene into 2-hydroxybiphenyl (2-HBP). The experimental values of growth, substrate consumption and product generation were obtained at 95 % confidence level of the fitted values using three models: Hinshelwood equation, Luedeking-Piret and Luedeking-Piret-like equations. The average error values between experimental values and fitted values were less than 10 %. These kinetic models describe all the experimental data with good statistical parameters. The production of 2-HBP in Enterobacter sp. was by "coupled growth".

  19. Small velocity and finite temperature variations in kinetic relaxation models

    KAUST Repository

    Markowich, Peter

    2010-01-01

    A small Knuden number analysis of a kinetic equation in the diffusive scaling is performed. The collision kernel is of BGK type with a general local Gibbs state. Assuming that the flow velocity is of the order of the Knudsen number, a Hilbert expansion yields a macroscopic model with finite temperature variations, whose complexity lies in between the hydrodynamic and the energy-transport equations. Its mathematical structure is explored and macroscopic models for specific examples of the global Gibbs state are presented. © American Institute of Mathematical Sciences.

  20. Numerical Comparison of Solutions of Kinetic Model Equations

    Directory of Open Access Journals (Sweden)

    A. A. Frolova

    2015-01-01

    Full Text Available The collision integral approximation by different model equations has created a whole new trend in the theory of rarefied gas. One widely used model is the Shakhov model (S-model obtained by expansion of inverse collisions integral in a series of Hermite polynomials up to the third order. Using the same expansion with another value of free parameters leads to a linearized ellipsoidal statistical model (ESL.Both model equations (S and ESL have the same properties, as they give the correct relaxation of non-equilibrium stress tensor components and heat flux vector, the correct Prandtl number at the transition to the hydrodynamic regime and do not guarantee the positivity of the distribution function.The article presents numerical comparison of solutions of Shakhov equation, ESL- model and full Boltzmann equation in the four Riemann problems for molecules of hard spheres.We have considered the expansion of two gas flows, contact discontinuity, the problem of the gas counter-flows and the problem of the shock wave structure. For the numerical solution of the kinetic equations the method of discrete ordinates is used.The comparison shows that solution has a weak sensitivity to the form of collision operator in the problem of expansions of two gas flows and results obtained by the model and the kinetic Boltzmann equations coincide.In the problem of the contact discontinuity the solution of model equations differs from full kinetic solutions at the point of the initial discontinuity. The non-equilibrium stress tensor has the maximum errors, the error of the heat flux is much smaller, and the ESL - model gives the exact value of the extremum of heat flux.In the problems of gas counter-flows and shock wave structure the model equations give significant distortion profiles of heat flux and non-equilibrium stress tensor components in front of the shock waves. This behavior is due to fact that in the models under consideration there is no dependency of the

  1. A genome-scale metabolic reconstruction of Pseudomonas putida KT2440: iJN746 as a cell factory

    Directory of Open Access Journals (Sweden)

    Thiele Ines

    2008-09-01

    Full Text Available Abstract Background Pseudomonas putida is the best studied pollutant degradative bacteria and is harnessed by industrial biotechnology to synthesize fine chemicals. Since the publication of P. putida KT2440's genome, some in silico analyses of its metabolic and biotechnology capacities have been published. However, global understanding of the capabilities of P. putida KT2440 requires the construction of a metabolic model that enables the integration of classical experimental data along with genomic and high-throughput data. The constraint-based reconstruction and analysis (COBRA approach has been successfully used to build and analyze in silico genome-scale metabolic reconstructions. Results We present a genome-scale reconstruction of P. putida KT2440's metabolism, iJN746, which was constructed based on genomic, biochemical, and physiological information. This manually-curated reconstruction accounts for 746 genes, 950 reactions, and 911 metabolites. iJN746 captures biotechnologically relevant pathways, including polyhydroxyalkanoate synthesis and catabolic pathways of aromatic compounds (e.g., toluene, benzoate, phenylacetate, nicotinate, not described in other metabolic reconstructions or biochemical databases. The predictive potential of iJN746 was validated using experimental data including growth performance and gene deletion studies. Furthermore, in silico growth on toluene was found to be oxygen-limited, suggesting the existence of oxygen-efficient pathways not yet annotated in P. putida's genome. Moreover, we evaluated the production efficiency of polyhydroxyalkanoates from various carbon sources and found fatty acids as the most prominent candidates, as expected. Conclusion Here we presented the first genome-scale reconstruction of P. putida, a biotechnologically interesting all-surrounder. Taken together, this work illustrates the utility of iJN746 as i a knowledge-base, ii a discovery tool, and iii an engineering platform to explore P

  2. Modeling Heavy Metal Sorption Kinetics Using Fractional Calculus

    Directory of Open Access Journals (Sweden)

    V. C. Friesen

    2015-01-01

    Full Text Available Heavy metals are commonly regarded as environmentally aggressive and hazardous to human health. Among the different metals, lead plays an important economic role due to its large use in the automotive industry, being an essential component of batteries. Different approaches have been reported in the literature aimed at lead removal, and among them a very successful one considers the use of water hyacinths for sorption-based operation. The modeling of the metal sorption kinetics is a fundamental step towards in-depth studies and proper separation equipment design and optimization. Fractional calculus represents a novel approach and a growing research field for process modeling, which is based on the successful use of derivatives of arbitrary order. This paper reports the modeling of the kinetics of lead sorption by water hyacinths (Eichhornia crassipes using a fractional calculus. A general procedure on error analysis is also employed to prove the actual fractional nature of the proposed model by the use of parametric variance analysis, which was carried out using two different approaches (with the complete Hessian matrix and with a simplified Hessian matrix. The joint parameter confidence regions were generated, allowing to successfully show the fractional nature of the model and the sorption process.

  3. Kinetic model of ductile iron solidification with experimental verification

    Directory of Open Access Journals (Sweden)

    W. Kapturkiewicz

    2009-10-01

    Full Text Available A solidification model for ductile iron, including Weibull formula for nodule count has been presented. From this model, the following can be determined: cooling curves, kinetics of austenite and eutectic nucleation, austenite and eutectic growth velocity, volume fraction, distribution of Si and P both in austenite and eutectic grain with distribution in casting section.In the developed model of nodular graphite iron casting solidification, the correctness of the mathematical model has been experimentally verified in the range of the most significant factors, which include temperature field, the value of maximum undercooling, and the graphite nodule count interrelated with the casting cross-section. Literature offers practically no data on so confronted process model and simulation program.

  4. Langrangian model of nitrogen kinetics in the Chattahoochee river

    Science.gov (United States)

    Jobson, H.E.

    1987-01-01

    A Lagrangian reference frame is used to solve the convection-dispersion equation and interpret water-quality obtained from the Chattahoochee River. The model was calibrated using unsteady concentrations of organic nitrogen, ammonia, and nitrite plus nitrate obtained during June 1977 and verified using data obtained during August 1976. Reaction kinetics of the cascade type are shown to provide a reasonable description of the nitrogen-species processes in the Chattahoochee River. The conceptual model is easy to visualize in the physical sense and the output includes information that is not easily determined from an Eulerian approach, but which is very helpful in model calibration and data interpretation. For example, the model output allows one to determine which data are of most value in model calibration or verification.

  5. Simulation of styrene polymerization reactors: kinetic and thermodynamic modeling

    Directory of Open Access Journals (Sweden)

    A. S. Almeida

    2008-06-01

    Full Text Available A mathematical model for the free radical polymerization of styrene is developed to predict the steady-state and dynamic behavior of a continuous process. Special emphasis is given for the kinetic and thermodynamic models, where the most sensitive parameters were estimated using data from an industrial plant. The thermodynamic model is based on a cubic equation of state and a mixing rule applied to the low-pressure vapor-liquid equilibrium of polymeric solutions, suitable for modeling the auto-refrigerated polymerization reactors, which use the vaporization rate to remove the reaction heat from the exothermic reactions. The simulation results show the high predictive capability of the proposed model when compared with plant data for conversion, average molecular weights, polydispersity, melt flow index, and thermal properties for different polymer grades.

  6. Kinetic equations modelling wealth redistribution: a comparison of approaches.

    Science.gov (United States)

    Düring, Bertram; Matthes, Daniel; Toscani, Giuseppe

    2008-11-01

    Kinetic equations modelling the redistribution of wealth in simple market economies is one of the major topics in the field of econophysics. We present a unifying approach to the qualitative study for a large variety of such models, which is based on a moment analysis in the related homogeneous Boltzmann equation, and on the use of suitable metrics for probability measures. In consequence, we are able to classify the most important feature of the steady wealth distribution, namely the fatness of the Pareto tail, and the dynamical stability of the latter in terms of the model parameters. Our results apply, e.g., to the market model with risky investments [S. Cordier, L. Pareschi, and G. Toscani, J. Stat. Phys. 120, 253 (2005)], and to the model with quenched saving propensities [A. Chatterjee, B. K. Chakrabarti, and S. S. Manna, Physica A 335, 155 (2004)]. Also, we present results from numerical experiments that confirm the theoretical predictions.

  7. 7-lump kinetic model for residual oil catalytic cracking

    Institute of Scientific and Technical Information of China (English)

    XU Ou-guan; SU Hong-ye; MU Sheng-jing; CHU Jian

    2006-01-01

    In this paper a novel 7-lump kinetic model is proposed to describe residual oil catalytic cracking, in which coke is lumped separately for accurate prediction. The reactor block is modeled as a combination of an ideal pipe flow reactor (PFR)and a continuously stirred tank reactor (CSTR). Unit factors are designed to correct the deviation between model predictions and practical plant data and tuned by modified Levenberg-Marquardt algorithm. The parameters estimated are reliable and good agreement between the model predictions and plant observations is observed. The model helps us get good insight into the performance of an industrial riser reactor that would be useful for optimization of residual oil catalytic cracking.

  8. Microbially Mediated Kinetic Sulfur Isotope Fractionation: Reactive Transport Modeling Benchmark

    Science.gov (United States)

    Wanner, C.; Druhan, J. L.; Cheng, Y.; Amos, R. T.; Steefel, C. I.; Ajo Franklin, J. B.

    2014-12-01

    Microbially mediated sulfate reduction is a ubiquitous process in many subsurface systems. Isotopic fractionation is characteristic of this anaerobic process, since sulfate reducing bacteria (SRB) favor the reduction of the lighter sulfate isotopologue (S32O42-) over the heavier isotopologue (S34O42-). Detection of isotopic shifts have been utilized as a proxy for the onset of sulfate reduction in subsurface systems such as oil reservoirs and aquifers undergoing uranium bioremediation. Reactive transport modeling (RTM) of kinetic sulfur isotope fractionation has been applied to field and laboratory studies. These RTM approaches employ different mathematical formulations in the representation of kinetic sulfur isotope fractionation. In order to test the various formulations, we propose a benchmark problem set for the simulation of kinetic sulfur isotope fractionation during microbially mediated sulfate reduction. The benchmark problem set is comprised of four problem levels and is based on a recent laboratory column experimental study of sulfur isotope fractionation. Pertinent processes impacting sulfur isotopic composition such as microbial sulfate reduction and dispersion are included in the problem set. To date, participating RTM codes are: CRUNCHTOPE, TOUGHREACT, MIN3P and THE GEOCHEMIST'S WORKBENCH. Preliminary results from various codes show reasonable agreement for the problem levels simulating sulfur isotope fractionation in 1D.

  9. Kinetic modelling of cadmium and lead removal by aquatic mosses

    Directory of Open Access Journals (Sweden)

    R. J. E. Martins

    2014-03-01

    Full Text Available Because biosorption is a low cost and effective method for treating metal-bearing wastewaters, understanding the process kinetics is relevant for design purposes. In the present study, the performance of the aquatic moss Fontinalis antipyretica for removing cadmium and lead from simulated wastewaters has been evaluated. Five kinetic models (first-order, pseudo-first-order, Elovich, modified Ritchie second-order and pseudo-second-order were fitted to the experimental data and compared. Previously, the effect of parameters such as the initial solution pH, contact time, and initial metal ion concentration on biosorption was investigated. The initial pH of the solution was found to have an optimum value in the range of 4.0-6.0. The equilibrium sorption capacity of cadmium and lead by Fontinalis antipyretica increased with the initial metal concentration. For an initial metal concentration of 10 mg L-1, the uptake capacity of the moss, at equilibrium, is the same for both metals (4.8 mg g-1. Nevertheless, when the initial concentration increases up to 100 mg L-1, the uptake of Pb(II was higher than 78%. The pseudo-second order biosorption kinetics provided the better correlation with the experimental data (R² ≥ 0.999.

  10. Kinetic model for astaxanthin aggregation in water-methanol mixtures

    Science.gov (United States)

    Giovannetti, Rita; Alibabaei, Leila; Pucciarelli, Filippo

    2009-07-01

    The aggregation of astaxanthin in hydrated methanol was kinetically studied in the temperature range from 10 °C to 50 °C, at different astaxanthin concentrations and solvent composition. A kinetic model for the formation and transformation of astaxanthin aggregated has been proposed. Spectrophotometric studies showed that monomeric astaxanthin decayed to H-aggregates that after-wards formed J-aggregates when water content was 50% and the temperature lower than 20 °C; at higher temperatures, very stable J-aggregates were formed directly. Monomer formed very stable H-aggregates when the water content was greater than 60%; in these conditions H-aggregates decayed into J-aggregates only when the temperature was at least 50 °C. Through these findings it was possible to establish that the aggregation reactions took place through a two steps consecutive reaction with first order kinetic constants and that the values of these depended on the solvent composition and temperature.

  11. Assigning numbers to the arrows: Parameterizing a gene regulation network by using accurate expression kinetics

    Science.gov (United States)

    Ronen, Michal; Rosenberg, Revital; Shraiman, Boris I.; Alon, Uri

    2002-08-01

    A basic challenge in systems biology is to understand the dynamical behavior of gene regulation networks. Current approaches aim at determining the network structure based on genomic-scale data. However, the network connectivity alone is not sufficient to define its dynamics; one needs to also specify the kinetic parameters for the regulation reactions. Here, we ask whether effective kinetic parameters can be assigned to a transcriptional network based on expression data. We present a combined experimental and theoretical approach based on accurate high temporal-resolution measurement of promoter activities from living cells by using green fluorescent protein (GFP) reporter plasmids. We present algorithms that use these data to assign effective kinetic parameters within a mathematical model of the network. To demonstrate this, we employ a well defined network, the SOS DNA repair system of Escherichia coli. We find a strikingly detailed temporal program of expression that correlates with the functional role of the SOS genes and is driven by a hierarchy of effective kinetic parameter strengths for the various promoters. The calculated parameters can be used to determine the kinetics of all SOS genes given the expression profile of just one representative, allowing a significant reduction in complexity. The concentration profile of the master SOS transcriptional repressor can be calculated, demonstrating that relative protein levels may be determined from purely transcriptional data. This finding opens the possibility of assigning kinetic parameters to transcriptional networks on a genomic scale.

  12. Kinetic Model for 1D aggregation of yeast ``prions''

    Science.gov (United States)

    Kunes, Kay; Cox, Daniel; Singh, Rajiv

    2004-03-01

    Mammalian prion proteins (PrP) are of public health interest because of mad cow and chronic wasting diseases. Yeast have proteins which can undergo similar reconformation and aggregation processes to PrP; yeast forms are simpler to experimentally study and model. Recent in vitro studies of the SUP35 protein(1), showed long aggregates and pure exponential growth of the misfolded form. To explain this data, we have extended a previous model of aggregation kinetics(2). The model assumes reconformation only upon aggregation, and includes aggregate fissioning and an initial nucleation barrier. We find for sufficiently small nucleation rates or seeding by small dimer concentrations that we can achieve the requisite exponential growth and long aggregates. We will compare to a more realistic stochastic kinetics model and present prelimary attempts to describe recent experiments on SUP35 strains. *-Supported by U.S. Army Congressionally Mandated Research Fund. 1) P. Chien and J.S. Weissman, Nature 410, 223 (2001); http://online.kitp.ucsb.edu/online/bionet03/collins/. 2) J. Masel, V.A.> Jansen, M.A. Nowak, Biophys. Chem. 77, 139 (1999).

  13. Kinetic models for the VASIMR thruster helicon plasma source

    Science.gov (United States)

    Batishchev, Oleg; Molvig, Kim

    2001-10-01

    Helicon gas discharge [1] is widely used by industry because of its remarkable efficiency [2]. High energy and fuel efficiencies make it very attractive for space electrical propulsion applications. For example, helicon plasma source is used in the high specific impulse VASIMR [3] plasma thruster, including experimental prototypes VX-3 and upgraded VX-10 [4] configurations, which operate with hydrogen (deuterium) and helium plasmas. We have developed a set of models for the VASIMR helicon discharge. Firstly, we use zero-dimensional energy and mass balance equations to characterize partially ionized gas condition/composition. Next, we couple it to one-dimensional hybrid model [6] for gas flow in the quartz tube of the helicon. We compare hybrid model results to a purely kinetic simulation of propellant flow in gas feed + helicon source subsystem. Some of the experimental data [3-4] are explained. Lastly, we discuss full-scale kinetic modeling of coupled gas and plasmas [5-6] in the helicon discharge. [1] M.A.Lieberman, A.J.Lihtenberg, 'Principles of ..', Wiley, 1994; [2] F.F.Chen, Plas. Phys. Contr. Fus. 33, 339, 1991; [3] F.Chang-Diaz et al, Bull. APS 45 (7) 129, 2000; [4] J.Squire et al., Bull. APS 45 (7) 130, 2000; [5] O.Batishchev et al, J. Plasma Phys. 61, part II, 347, 1999; [6] O.Batishchev, K.Molvig, AIAA technical paper 2000-3754, -14p, 2001.

  14. Economic inequality and mobility in kinetic models for social sciences

    Science.gov (United States)

    Letizia Bertotti, Maria; Modanese, Giovanni

    2016-10-01

    Statistical evaluations of the economic mobility of a society are more difficult than measurements of the income distribution, because they require to follow the evolution of the individuals' income for at least one or two generations. In micro-to-macro theoretical models of economic exchanges based on kinetic equations, the income distribution depends only on the asymptotic equilibrium solutions, while mobility estimates also involve the detailed structure of the transition probabilities of the model, and are thus an important tool for assessing its validity. Empirical data show a remarkably general negative correlation between economic inequality and mobility, whose explanation is still unclear. It is therefore particularly interesting to study this correlation in analytical models. In previous work we investigated the behavior of the Gini inequality index in kinetic models in dependence on several parameters which define the binary interactions and the taxation and redistribution processes: saving propensity, taxation rates gap, tax evasion rate, welfare means-testing etc. Here, we check the correlation of mobility with inequality by analyzing the mobility dependence from the same parameters. According to several numerical solutions, the correlation is confirmed to be negative.

  15. Kinetic modelling of cytochrome c adsorption on SBA-15.

    Science.gov (United States)

    Yokogawa, Yoshiyuki; Yamauchi, Rie; Saito, Akira; Yamato, Yuta; Toma, Takeshi

    2017-01-01

    The adsorption capacity of mesoporous silicate (MPS) materials as an adsorbent for protein adsorption from the aqueous phase and the mechanism of the adsorption processes by comparative analyses of the applicability of five kinetic transfer models, pseudo-first-order model, pseudo-second-order model, Elovich kinetic model, Bangham's equation model, and intraparticle diffusion model, were investigated. A mixture of tetraethyl orthosilicate (TEOS) and triblock copolymer as a template was stirred, hydrothermally treated to form the mesoporous SBA-15 structure, and heat-treated at 550°C to form the MPS material, SBA-15. The synthesized SBA-15 was immersed in a phosphate buffered saline (PBS) solution containing cytochrome c for 2, 48, and 120 hours at 4°C. The TEM observations of proteins on/in mesoporous SBA-15 revealed the protein behaviors. The holes of the MPS materials were observed to overlap those of the stained proteins for the first 2 hours of immersion. The stained proteins were observed between primary particles and partly inside the mesoporous channels in the MPS material when it had been immersed for 48 hours. For MPS when it had been immersed for 120 hours, stained proteins were observed in almost all meso-scale channels of MPS. The time profiles for adsorption of proteins can be described well by Bangham's equation model and the intraparticle diffusion model. The Bangham's equation model is based on the assumption that pore diffusion was the only rate controlling step during adsorption, whose contribution to the overall mechanism of cytochrome c adsorption on SBA-15 should not be neglected. The kinetic curves obtained from the experiment for cytochrome c adsorption on SBA-15 could show the three steps: the initial rapid increase of the adsorbed amount of cytochrome c, the second gradual increase, and the final equilibrium stage. These three adsorption steps can be interpreted well by the multi-linearity of the intraparticle diffusion model

  16. Investigation of kinetics model of dc reactive sputtering

    Institute of Scientific and Technical Information of China (English)

    朱圣龙; 王福会; 吴维叓

    1996-01-01

    A novel physical sputtering kinetics model for reactive sputtering is presented.Reactive gas gettering effects and interactions among the characteristic parameters have been taken into account in the model.The data derived from the model accorded fairly well with experimental results.The relationship between the values of initial oxide coverage on the target and the ready states was depicted in the model.This relationship gives reasons for the difference of the threshold of reactive gas fluxes (Q) from the metal sputtering region to the oxide sputtering region and in reverse direction.The discontinuities in oxide coverage on the target surface (θ) versus reactive gas fluxes (Q) are referred to as the effects of reactive gas partial pressure (p) upon the forming rates of oxide on the surfaces of target (V0).The diversity of the oxygen flux threshold results from the variance of the initial values of oxide coverage on target.

  17. Genome-scale metabolic network validation of Shewanella oneidensis using transposon insertion frequency analysis.

    Directory of Open Access Journals (Sweden)

    Hong Yang

    2014-09-01

    Full Text Available Transposon mutagenesis, in combination with parallel sequencing, is becoming a powerful tool for en-masse mutant analysis. A probability generating function was used to explain observed miniHimar transposon insertion patterns, and gene essentiality calls were made by transposon insertion frequency analysis (TIFA. TIFA incorporated the observed genome and sequence motif bias of the miniHimar transposon. The gene essentiality calls were compared to: 1 previous genome-wide direct gene-essentiality assignments; and, 2 flux balance analysis (FBA predictions from an existing genome-scale metabolic model of Shewanella oneidensis MR-1. A three-way comparison between FBA, TIFA, and the direct essentiality calls was made to validate the TIFA approach. The refinement in the interpretation of observed transposon insertions demonstrated that genes without insertions are not necessarily essential, and that genes that contain insertions are not always nonessential. The TIFA calls were in reasonable agreement with direct essentiality calls for S. oneidensis, but agreed more closely with E. coli essentiality calls for orthologs. The TIFA gene essentiality calls were in good agreement with the MR-1 FBA essentiality predictions, and the agreement between TIFA and FBA predictions was substantially better than between the FBA and the direct gene essentiality predictions.

  18. Study on Lumped Kinetic Model for FDFCC II. Validation and Prediction of Model

    Institute of Scientific and Technical Information of China (English)

    Wu Feiyue; Weng Huixin; Luo Shixian

    2008-01-01

    On the basis of formulating the 9-lump kinetic model for gasoline catalytic upgrading and the 12-lump kinetic model for heavy oil FCC, this paper is aimed at development of a combined kinetic model for a typical FDFCC process after analyzing the coupled relationship and combination of these two models. The model is also verified by using commercial data, the results of which showed that the model can better predict the product yields and their quality, with the relative errors between the main products of the unit and commercial data being less than five percent. Furthermore, the combined model is used to predict and optimize the operating conditions for gasoline riser and heavy oil riser in FDFCC. So this paper can offer some guidance for the processing of FDFCC and is instructive to model research and development of such multi-reactor process and combined process.

  19. Adequacy indices for dialysis in acute renal failure: kinetic modeling.

    Science.gov (United States)

    Debowska, Malgorzata; Lindholm, Bengt; Waniewski, Jacek

    2010-05-01

    Many aspects of the management of renal replacement therapy in acute renal failure (ARF), including the appropriate assessment of dialysis adequacy, remain unresolved, because ARF patients often are not in a metabolic steady state. The aim of this study was to evaluate a system of adequacy indices for dialysis in ARF patients using urea and creatinine kinetic modeling. Kinetic modeling was performed for two different fictitious patients (A and B) with characteristics described by the average parameters for two patient groups and for two blood purification treatments: sustained low efficiency daily dialysis (SLEDD) in Patient A and continuous venovenous hemofiltration (CVVH) in Patient B, based on data from a clinical report. Urea and creatinine generation rates were estimated according to the clinical data on the solute concentrations in blood. Then, using estimated generation rates, two hypothetical treatments were simulated, CVVH in Patient A and SLEDD in Patient B. KT/V, fractional solute removal (FSR) and equivalent renal clearance (EKR) were calculated according to the definitions developed for metabolically unstable patients. CVVH appeared as being more effective than SLEDD because KT/V, FSR, and EKR were higher for CVVH than SLEDD in Patients A and B. Creatinine KT/V, FSR, and EKR were lower and well correlated to the respective indices for urea. Urea and creatinine generation rates were overestimated more than twice in Patient A and by 30-40% in Patient B if calculated assuming the metabolically stable state than if estimated by kinetic modeling. Adequacy indices and solute generation rates for ARF patients should be estimated using the definition for unsteady metabolic state. EKR and FSR were higher for urea and creatinine with CVVH than with SLEDD, because of higher K.T and minimized compartmental effects for CVVH.

  20. Kinetics of solid state phase transformations: Measurement and modelling of some basic issues

    Indian Academy of Sciences (India)

    S Raju; E Mohandas

    2010-01-01

    A brief review of the issues involved in modelling of the solid state transformation kinetics is presented. The fact that apart from the standard thermodynamic parameters, certain path variables like heating or cooling rate can also exert a crucial influence on the kinetic outcome is stressed. The kinetic specialties that are intrinsic to phase changes proceeding under varying thermal history are enumerated. A simple and general modelling methodology for understanding the kinetics of non-isothermal transformations is outlined.

  1. Tracer kinetic modelling in MRI: estimating perfusion and capillary permeability

    Science.gov (United States)

    Sourbron, S. P.; Buckley, D. L.

    2012-01-01

    The tracer-kinetic models developed in the early 1990s for dynamic contrast-enhanced MRI (DCE-MRI) have since become a standard in numerous applications. At the same time, the development of MRI hardware has led to increases in image quality and temporal resolution that reveal the limitations of the early models. This in turn has stimulated an interest in the development and application of a second generation of modelling approaches. They are designed to overcome these limitations and produce additional and more accurate information on tissue status. In particular, models of the second generation enable separate estimates of perfusion and capillary permeability rather than a single parameter Ktrans that represents a combination of the two. A variety of such models has been proposed in the literature, and development in the field has been constrained by a lack of transparency regarding terminology, notations and physiological assumptions. In this review, we provide an overview of these models in a manner that is both physically intuitive and mathematically rigourous. All are derived from common first principles, using concepts and notations from general tracer-kinetic theory. Explicit links to their historical origins are included to allow for a transfer of experience obtained in other fields (PET, SPECT, CT). A classification is presented that reveals the links between all models, and with the models of the first generation. Detailed formulae for all solutions are provided to facilitate implementation. Our aim is to encourage the application of these tools to DCE-MRI by offering researchers a clearer understanding of their assumptions and requirements.

  2. A Photochemical Kinetic Model for Solid Dosage Forms.

    Science.gov (United States)

    Carvalho, Thiago C; La Cruz, Thomas E; Tabora, Jose E

    2017-08-20

    Photochemical kinetics models for pharmaceutical compounds in solution have been extensively investigated, but not in solid phase upon exposure to different light sources. The objective of this study was to develop a mathematical model to describe the solid state photodegradation of pharmaceutical powder materials under different area/volumetric scales and light exposure conditions. The model considered the previous formalism presented for photodegradation kinetics in solution phase with important elements applied to static powder material being irradiated with a polychromatic light source. The model also included the influence of optical phenomena (i.e. reflectance, scattering factors, etc.) by applying Beer-Lambert law to light attenuation, including effects of powder density. Drug substance and drug product intermediates (blends and tablet cores) were exposed to different light sources and intensities. The model reasonably predicted the photodegradation levels of powder beds of drug substance and drug product intermediates under white and yellow lights with intensities around 5 to 11 kLux. Importantly, the model estimates demonstrated that the reciprocity law for photoreactions was held. Further model evaluation showed that, due to light attenuation, the powder bed is in virtual darkness at cake depths greater than 500 μm. At 100 μm, the photodegradation of the investigated compound is expected to be close to 100% in 10 days under white fluorescent halophosphate light at 9.5 kLux. For tablets, defining the volume over exposed surface area ratio is more challenging. Nevertheless, the model can consider a bracket between worst and best cases to provide a reasonable photodegradation estimate. This tool can be significantly leveraged to simulate different light exposure scenarios while assessing photostability risk in order to define appropriate Control Strategy in manufacturing. Copyright © 2017. Published by Elsevier B.V.

  3. Genome-scale metabolic analysis of Clostridium thermocellum for bioethanol production

    Directory of Open Access Journals (Sweden)

    Brooks J Paul

    2010-03-01

    Full Text Available Abstract Background Microorganisms possess diverse metabolic capabilities that can potentially be leveraged for efficient production of biofuels. Clostridium thermocellum (ATCC 27405 is a thermophilic anaerobe that is both cellulolytic and ethanologenic, meaning that it can directly use the plant sugar, cellulose, and biochemically convert it to ethanol. A major challenge in using microorganisms for chemical production is the need to modify the organism to increase production efficiency. The process of properly engineering an organism is typically arduous. Results Here we present a genome-scale model of C. thermocellum metabolism, iSR432, for the purpose of establishing a computational tool to study the metabolic network of C. thermocellum and facilitate efforts to engineer C. thermocellum for biofuel production. The model consists of 577 reactions involving 525 intracellular metabolites, 432 genes, and a proteomic-based representation of a cellulosome. The process of constructing this metabolic model led to suggested annotation refinements for 27 genes and identification of areas of metabolism requiring further study. The accuracy of the iSR432 model was tested using experimental growth and by-product secretion data for growth on cellobiose and fructose. Analysis using this model captures the relationship between the reduction-oxidation state of the cell and ethanol secretion and allowed for prediction of gene deletions and environmental conditions that would increase ethanol production. Conclusions By incorporating genomic sequence data, network topology, and experimental measurements of enzyme activities and metabolite fluxes, we have generated a model that is reasonably accurate at predicting the cellular phenotype of C. thermocellum and establish a strong foundation for rational strain design. In addition, we are able to draw some important conclusions regarding the underlying metabolic mechanisms for observed behaviors of C. thermocellum

  4. Model-free kinetics applied to sugarcane bagasse combustion

    Energy Technology Data Exchange (ETDEWEB)

    Ramajo-Escalera, B.; Espina, A.; Garcia, J.R. [Department of Organic and Inorganic Chemistry, University of Oviedo, 33006 Oviedo (Spain); Sosa-Arnao, J.H. [Mechanical Engineering Faculty, State University of Campinas (UNICAMP), P.O. Box 6122, 13083-970 Campinas, SP (Brazil); Nebra, S.A. [Interdisciplinary Center of Energy Planning, State University of Campinas (UNICAMP), R. Shigeo Mori 2013, 13083-770 Campinas, SP (Brazil)

    2006-09-15

    Vyazovkin's model-free kinetic algorithms were applied to determine conversion, isoconversion and apparent activation energy to both dehydration and combustion of sugarcane bagasse. Three different steps were detected with apparent activation energies of 76.1+/-1.7, 333.3+/-15.0 and 220.1+/-4.0kJ/mol in the conversion range of 2-5%, 15-60% and 70-90%, respectively. The first step is associated with the endothermic process of drying and release of water. The others correspond to the combustion (and carbonization) of organic matter (mainly cellulose, hemicellulose and lignin) and the combustion of the products of pyrolysis. (author)

  5. Fluctuation dissipation ratio in the one dimensional kinetic Ising model

    OpenAIRE

    Lippiello, E.; Zannetti, M.

    2000-01-01

    The exact relation between the response function $R(t,t^{\\prime})$ and the two time correlation function $C(t,t^{\\prime})$ is derived analytically in the one dimensional kinetic Ising model subjected to a temperature quench. The fluctuation dissipation ratio $X(t,t^{\\prime})$ is found to depend on time through $C(t,t^{\\prime})$ in the time region where scaling $C(t,t^{\\prime}) = f(t/t^{\\prime})$ holds. The crossover from the nontrivial form $X(C(t,t^{\\prime}))$ to $X(t,t^{\\prime}) \\equiv 1$ t...

  6. Large Scale Simulations of the Kinetic Ising Model

    Science.gov (United States)

    Münkel, Christian

    We present Monte Carlo simulation results for the dynamical critical exponent z of the two- and three-dimensional kinetic Ising model. The z-values were calculated from the magnetization relaxation from an ordered state into the equilibrium state at Tc for very large systems with up to (169984)2 and (3072)3 spins. To our knowledge, these are the largest Ising-systems simulated todate. We also report the successful simulation of very large lattices on a massively parallel MIMD computer with high speedups of approximately 1000 and an efficiency of about 0.93.

  7. Kinetic Relations for a Lattice Model of Phase Transitions

    Science.gov (United States)

    Schwetlick, Hartmut; Zimmer, Johannes

    2012-11-01

    The aim of this article is to analyse travelling waves for a lattice model of phase transitions, specifically the Fermi-Pasta-Ulam chain with piecewise quadratic interaction potential. First, for fixed, sufficiently large subsonic wave speeds, we rigorously prove the existence of a family of travelling wave solutions. Second, it is shown that this family of solutions gives rise to a kinetic relation which depends on the jump in the oscillatory energy in the solution tails. Third, our constructive approach provides a very good approximate travelling wave solution.

  8. A generic 3D kinetic model of gene expression

    Science.gov (United States)

    Zhdanov, Vladimir

    2012-04-01

    Recent experiments show that mRNAs and proteins can be localized both in prokaryotic and eukaryotic cells. To describe such situations, I present a 3D mean-field kinetic model aimed primarily at gene expression in prokaryotic cells, including the formation of mRNA, its translation into protein, and slow diffusion of these species. Under steady-state conditions, the mRNA and protein spatial distribution is described by simple exponential functions. The protein concentration near the gene transcribed into mRNA is shown to depend on the protein and mRNA diffusion coefficients and degradation rate constants.

  9. Kinetic mixing effect in the 3 -3 -1 -1 model

    Science.gov (United States)

    Dong, P. V.; Si, D. T.

    2016-06-01

    We show that the mixing effect of the neutral gauge bosons in the 3 -3 -1 -1 model comes from two sources. The first one is due to the 3 -3 -1 -1 gauge symmetry breaking as usual, whereas the second one results from the kinetic mixing between the gauge bosons of U (1 )X and U (1 )N groups, which are used to determine the electric charge and baryon minus lepton numbers, respectively. Such mixings modify the ρ -parameter and the known couplings of Z with fermions. The constraints that arise from flavor-changing neutral currents due to the gauge boson mixings and nonuniversal fermion generations are also given.

  10. Warped Higgsless Models with IR-Brane Kinetic Terms

    CERN Document Server

    Davoudiasl, H; Lillie, Benjamin Huntington; Rizzo, T G

    2004-01-01

    We examine a warped Higgsless $SU(2)_L\\times SU(2)_R\\times U(1)_{B-L}$ model in 5--$d$ with IR(TeV)--brane kinetic terms. It is shown that adding a brane term for the $U(1)_{B-L}$ gauge field does not affect the scale ($\\sim 2-3$ TeV) where perturbative unitarity in $W_L^+ W_L^- \\to W_L^+ W_L^-$ is violated. This term could, however, enhance the agreement of the model with the precision electroweak data. In contrast, the inclusion of a kinetic term corresponding to the $SU(2)_D$ custodial symmetry of the theory delays the unitarity violation in $W_L^\\pm$ scattering to energy scales of $\\sim 6-7$ TeV for a significant fraction of the parameter space. This is about a factor of 4 improvement compared to the corresponding scale of unitarity violation in the Standard Model without a Higgs. We also show that null searches for extra gauge bosons at the Tevatron and for contact interactions at LEP II place non-trivial bounds on the size of the IR-brane terms.

  11. Kinetic modeling of 3D equilibria in a tokamak

    Science.gov (United States)

    Albert, C. G.; Heyn, M. F.; Kasilov, S. V.; Kernbichler, W.; Martitsch, A. F.; Runov, A. M.

    2016-11-01

    External resonant magnetic perturbations (RMPs) can modify the magnetic topology in a tokamak. In this case the magnetic field cannot generally be described by ideal MHD equilibrium equations in the vicinity of resonant magnetic surfaces where parallel and perpendicular relaxation timescales are comparable. Usually, resistive MHD models are used to describe these regions. In the present work, a kinetic model is used for this purpose. Within this model, plasma response, current and charge density are computed with help of a Monte Carlo method, where guiding center orbit equations are solved using a semianalytical geometrical integrator. Besides its higher efficiency in comparison to usual integrators this method is not sensitive to noise in field quantities. The computed charges and currents are used to calculate the electromagnetic field with help of a finite element solver. A preconditioned iterative scheme is applied to search for a self-consistent solution. The discussed method is aimed at the nonlinear kinetic description of RMPs in experiments on Edge Localized Mode (ELM) mitigation by external perturbation coil systems without simplification of the device geometry.

  12. Kinetic modeling of ethane pyrolysis at high conversion.

    Science.gov (United States)

    Xu, Chen; Al Shoaibi, Ahmed Sultan; Wang, Chenguang; Carstensen, Hans-Heinrich; Dean, Anthony M

    2011-09-29

    The primary objective of this study is to develop an improved first-principle-based mechanism that describes the molecular weight growth kinetics observed during ethane pyrolysis. A proper characterization of the kinetics of ethane pyrolysis is a prerequisite for any analysis of hydrocarbon pyrolysis and oxidation. Flow reactor experiments were performed with ~50/50 ethane/nitrogen mixtures with temperatures ranging from 550 to 850 °C at an absolute pressure of ~0.8 atm and a residence time of ~5 s. These conditions result in ethane conversions ranging from virtually no reaction to ~90%. Comparisons of predictions using our original mechanism to these data yielded very satisfactory results in terms of the temperature dependence of ethane conversion and prediction of the major products ethylene and hydrogen. However, there were discrepancies in some of the minor species concentrations that are involved in the molecular weight growth kinetics. We performed a series of CBS-QB3 analyses for the C(3)H(7), C(4)H(7), and C(4)H(9) potential energy surfaces to better characterize the radical addition reactions that lead to molecular weight growth. We also extended a published C(6)H(9) PES to include addition of vinyl to butadiene. The results were then used to calculate pressure-dependent rate constants for the multiple reaction pathways of these addition reactions. Inclusion of the unadjusted rate constants resulting from these analyses in the mechanism significantly improved the description of several of the species involved in molecular weight growth kinetics. We compare the predictions of this improved model to those obtained with a consensus model recently published as well as to ethane steam cracking data. We find that a particularly important reaction is that of vinyl addition to butadiene. Another important observation is that several radical addition reactions are partially equilibrated. Not only does this mean that reliable thermodynamic parameters are essential

  13. Kinetic and Stochastic Models of 1D yeast ``prions"

    Science.gov (United States)

    Kunes, Kay

    2005-03-01

    Mammalian prion proteins (PrP) are of public health interest because of mad cow and chronic wasting diseases. Yeasts have proteins, which can undergo similar reconformation and aggregation processes to PrP; yeast ``prions" are simpler to experimentally study and model. Recent in vitro studies of the SUP35 protein (1), showed long aggregates and pure exponential growth of the misfolded form. To explain this data, we have extended a previous model of aggregation kinetics along with our own stochastic approach (2). Both models assume reconformation only upon aggregation, and include aggregate fissioning and an initial nucleation barrier. We find for sufficiently small nucleation rates or seeding by small dimer concentrations that we can achieve the requisite exponential growth and long aggregates.

  14. The Origin of the RNA World a Kinetic Model

    CERN Document Server

    Wattis, J A D; Wattis, Jonathan A. D.; Coveney, Peter V.

    1999-01-01

    The aims of this paper are to propose, construct and analyse microscopic kinetic models for the emergence of long chains of RNA from monomeric beta-D-ribonucleotide precursors in prebiotic circumstances. Our theory starts out from similar but more general chemical assumptions to those of Eigen, namely that catalytic replication can lead to a large population of long chains. In particular, our models incorporate the possibility of (i) direct chain growth, (ii) template-assisted synthesis and (iii) catalysis by RNA replicase ribozymes, all with varying degrees of efficiency. However, in our models the reaction mechanisms are kept `open'; we do not assume the existence of closed hypercycles which sustain a population of long chains. Rather it is the feasibility of the initial emergence of a self-sustaining set of RNA chains from monomeric nucleotides which is our prime concern. We confront directly the central nonlinear features of the problem, which have often been overlooked in previous studies. Our detailed m...

  15. Upper D region chemical kinetic modeling of LORE relaxation times

    Science.gov (United States)

    Gordillo-Vázquez, F. J.; Luque, A.; Haldoupis, C.

    2016-04-01

    The recovery times of upper D region electron density elevations, caused by lightning-induced electromagnetic pulses (EMP), are modeled. The work was motivated from the need to understand a recently identified narrowband VLF perturbation named LOREs, an acronym for LOng Recovery Early VLF events. LOREs associate with long-living electron density perturbations in the upper D region ionosphere; they are generated by strong EMP radiated from large peak current intensities of ±CG (cloud to ground) lightning discharges, known also to be capable of producing elves. Relaxation model scenarios are considered first for a weak enhancement in electron density and then for a much stronger one caused by an intense lightning EMP acting as an impulsive ionization source. The full nonequilibrium kinetic modeling of the perturbed mesosphere in the 76 to 92 km range during LORE-occurring conditions predicts that the electron density relaxation time is controlled by electron attachment at lower altitudes, whereas above 79 km attachment is balanced totally by associative electron detachment so that electron loss at these higher altitudes is controlled mainly by electron recombination with hydrated positive clusters H+(H2O)n and secondarily by dissociative recombination with NO+ ions, a process which gradually dominates at altitudes >88 km. The calculated recovery times agree fairly well with LORE observations. In addition, a simplified (quasi-analytic) model build for the key charged species and chemical reactions is applied, which arrives at similar results with those of the full kinetic model. Finally, the modeled recovery estimates for lower altitudes, that is <79 km, are in good agreement with the observed short recovery times of typical early VLF events, which are known to be associated with sprites.

  16. Kinetic model of sucrose accumulation in maturing sugarcane culm tissue.

    Science.gov (United States)

    Uys, Lafras; Botha, Frederik C; Hofmeyr, Jan-Hendrik S; Rohwer, Johann M

    2007-01-01

    Biochemically, it is not completely understood why or how commercial varieties of sugarcane (Saccharum officinarum) are able to accumulate sucrose in high concentrations. Such concentrations are obtained despite the presence of sucrose synthesis/breakdown cycles (futile cycling) in the culm of the storage parenchyma. Given the complexity of the process, kinetic modelling may help to elucidate the factors governing sucrose accumulation or direct the design of experimental optimisation strategies. This paper describes the extension of an existing model of sucrose accumulation (Rohwer, J.M., Botha, F.C., 2001. Analysis of sucrose accumulation in the sugar cane culm on the basis of in vitro kinetic data. Biochem. J. 358, 437-445) to account for isoforms of sucrose synthase and fructokinase, carbon partitioning towards fibre formation, and the glycolytic enzymes phosphofructokinase (PFK), pyrophosphate-dependent PFK and aldolase. Moreover, by including data on the maximal activity of the enzymes as measured in different internodes, a growth model was constructed that describes the metabolic behaviour as sugarcane parenchymal tissue matures from internodes 3-10. While there was some discrepancy between modelled and experimentally determined steady-state sucrose concentrations in the cytoplasm, steady-state fluxes showed a better fit. The model supports a hypothesis of vacuolar sucrose accumulation against a concentration gradient. A detailed metabolic control analysis of sucrose synthase showed that each isoform has a unique control profile. Fructose uptake by the cell and sucrose uptake by the vacuole had a negative control on the futile cycling of sucrose and a positive control on sucrose accumulation, while the control profile for neutral invertase was reversed. When the activities of these three enzymes were changed from their reference values, the effects on futile cycling and sucrose accumulation were amplified. The model can be run online at the JWS Online

  17. Reduced Models in Chemical Kinetics via Nonlinear Data-Mining

    Directory of Open Access Journals (Sweden)

    Eliodoro Chiavazzo

    2014-01-01

    Full Text Available The adoption of detailed mechanisms for chemical kinetics often poses two types of severe challenges: First, the number of degrees of freedom is large; and second, the dynamics is characterized by widely disparate time scales. As a result, reactive flow solvers with detailed chemistry often become intractable even for large clusters of CPUs, especially when dealing with direct numerical simulation (DNS of turbulent combustion problems. This has motivated the development of several techniques for reducing the complexity of such kinetics models, where, eventually, only a few variables are considered in the development of the simplified model. Unfortunately, no generally applicable a priori recipe for selecting suitable parameterizations of the reduced model is available, and the choice of slow variables often relies upon intuition and experience. We present an automated approach to this task, consisting of three main steps. First, the low dimensional manifold of slow motions is (approximately sampled by brief simulations of the detailed model, starting from a rich enough ensemble of admissible initial conditions. Second, a global parametrization of the manifold is obtained through the Diffusion Map (DMAP approach, which has recently emerged as a powerful tool in data analysis/machine learning. Finally, a simplified model is constructed and solved on the fly in terms of the above reduced (slow variables. Clearly, closing this latter model requires nontrivial interpolation calculations, enabling restriction (mapping from the full ambient space to the reduced one and lifting (mapping from the reduced space to the ambient one. This is a key step in our approach, and a variety of interpolation schemes are reported and compared. The scope of the proposed procedure is presented and discussed by means of an illustrative combustion example.

  18. Kinetic modeling can describe in vivo glycolysis in Entamoeba histolytica.

    Science.gov (United States)

    Saavedra, Emma; Marín-Hernández, Alvaro; Encalada, Rusely; Olivos, Alfonso; Mendoza-Hernández, Guillermo; Moreno-Sánchez, Rafael

    2007-09-01

    Glycolysis in the human parasite Entamoeba histolytica is characterized by the absence of cooperative modulation and the prevalence of pyrophosphate-dependent (over ATP-dependent) enzymes. To determine the flux-control distribution of glycolysis and understand its underlying control mechanisms, a kinetic model of the pathway was constructed by using the software gepasi. The model was based on the kinetic parameters determined in the purified recombinant enzymes, and the enzyme activities, and steady-state fluxes and metabolite concentrations determined in amoebal trophozoites. The model predicted, with a high degree of accuracy, the flux and metabolite concentrations found in trophozoites, but only when the pyrophosphate concentration was held constant; at variable pyrophosphate, the model was not able to completely account for the ATP production/consumption balance, indicating the importance of the pyrophosphate homeostasis for amoebal glycolysis. Control analysis by the model revealed that hexokinase exerted the highest flux control (73%), as a result of its low cellular activity and strong AMP inhibition. 3-Phosphoglycerate mutase also exhibited significant flux control (65%) whereas the other pathway enzymes showed little or no control. The control of the ATP concentration was also mainly exerted by ATP consuming processes and 3-phosphoglycerate mutase and hexokinase (in the producing block). The model also indicated that, in order to diminish the amoebal glycolytic flux by 50%, it was required to decrease hexokinase or 3-phosphoglycerate mutase by 24% and 55%, respectively, or by 18% for both enzymes. By contrast, to attain the same reduction in flux by inhibiting the pyrophosphate-dependent enzymes pyrophosphate-phosphofructokinase and pyruvate phosphate dikinase, they should be decreased > 70%. On the basis of metabolic control analysis, steps whose inhibition would have stronger negative effects on the energy metabolism of this parasite were identified

  19. Determining the control circuitry of redox metabolism at the genome-scale.

    Directory of Open Access Journals (Sweden)

    Stephen Federowicz

    2014-04-01

    Full Text Available Determining how facultative anaerobic organisms sense and direct cellular responses to electron acceptor availability has been a subject of intense study. However, even in the model organism Escherichia coli, established mechanisms only explain a small fraction of the hundreds of genes that are regulated during electron acceptor shifts. Here we propose a qualitative model that accounts for the full breadth of regulated genes by detailing how two global transcription factors (TFs, ArcA and Fnr of E. coli, sense key metabolic redox ratios and act on a genome-wide basis to regulate anabolic, catabolic, and energy generation pathways. We first fill gaps in our knowledge of this transcriptional regulatory network by carrying out ChIP-chip and gene expression experiments to identify 463 regulatory events. We then interfaced this reconstructed regulatory network with a highly curated genome-scale metabolic model to show that ArcA and Fnr regulate >80% of total metabolic flux and 96% of differential gene expression across fermentative and nitrate respiratory conditions. Based on the data, we propose a feedforward with feedback trim regulatory scheme, given the extensive repression of catabolic genes by ArcA and extensive activation of chemiosmotic genes by Fnr. We further corroborated this regulatory scheme by showing a 0.71 r(2 (p<1e-6 correlation between changes in metabolic flux and changes in regulatory activity across fermentative and nitrate respiratory conditions. Finally, we are able to relate the proposed model to a wealth of previously generated data by contextualizing the existing transcriptional regulatory network.

  20. Genome-scale reconstruction and analysis of the metabolic network in the hyperthermophilic archaeon Sulfolobus solfataricus.

    Directory of Open Access Journals (Sweden)

    Thomas Ulas

    Full Text Available We describe the reconstruction of a genome-scale metabolic model of the crenarchaeon Sulfolobus solfataricus, a hyperthermoacidophilic microorganism. It grows in terrestrial volcanic hot springs with growth occurring at pH 2-4 (optimum 3.5 and a temperature of 75-80°C (optimum 80°C. The genome of Sulfolobus solfataricus P2 contains 2,992,245 bp on a single circular chromosome and encodes 2,977 proteins and a number of RNAs. The network comprises 718 metabolic and 58 transport/exchange reactions and 705 unique metabolites, based on the annotated genome and available biochemical data. Using the model in conjunction with constraint-based methods, we simulated the metabolic fluxes induced by different environmental and genetic conditions. The predictions were compared to experimental measurements and phenotypes of S. solfataricus. Furthermore, the performance of the network for 35 different carbon sources known for S. solfataricus from the literature was simulated. Comparing the growth on different carbon sources revealed that glycerol is the carbon source with the highest biomass flux per imported carbon atom (75% higher than glucose. Experimental data was also used to fit the model to phenotypic observations. In addition to the commonly known heterotrophic growth of S. solfataricus, the crenarchaeon is also able to grow autotrophically using the hydroxypropionate-hydroxybutyrate cycle for bicarbonate fixation. We integrated this pathway into our model and compared bicarbonate fixation with growth on glucose as sole carbon source. Finally, we tested the robustness of the metabolism with respect to gene deletions using the method of Minimization of Metabolic Adjustment (MOMA, which predicted that 18% of all possible single gene deletions would be lethal for the organism.

  1. STOCHASTIC KINETIC MODELS: DYNAMIC INDEPENDENCE, MODULARITY AND GRAPHS.

    Science.gov (United States)

    Bowsher, Clive G

    2010-08-01

    The dynamic properties and independence structure of stochastic kinetic models (SKMs) are analyzed. An SKM is a highly multivariate jump process used to model chemical reaction networks, particularly those in biochemical and cellular systems. We identify SKM subprocesses with the corresponding counting processes and propose a directed, cyclic graph (the kinetic independence graph or KIG) that encodes the local independence structure of their conditional intensities. Given a partition [A, D, B] of the vertices, the graphical separation A ⊥ B|D in the undirected KIG has an intuitive chemical interpretation and implies that A is locally independent of B given A ∪ D. It is proved that this separation also results in global independence of the internal histories of A and B conditional on a history of the jumps in D which, under conditions we derive, corresponds to the internal history of D. The results enable mathematical definition of a modularization of an SKM using its implied dynamics. Graphical decomposition methods are developed for the identification and efficient computation of nested modularizations. Application to an SKM of the red blood cell advances understanding of this biochemical system.

  2. Modeling the kinetics of carbon coagulation in explosives detonation

    Science.gov (United States)

    Ree, F. H.; Viecelli, J. A.; Glosli, J. N.

    1998-05-01

    A typical insensitive high explosive such as LX-17 has a large carbon content. The detonation behavior of these explosives is affected by a slow coagulation of carbon atoms by diffusion and their possible transformation from one chemical bonding type to another. We have used the Brenner bond order potential to compute the melting line of diamond at high pressure and high temperature by molecular dynamics and Monte Carlo simulations, with the goal to refine the potential for the study of the kinetics of the graphite diamond transition. The slow diffusion-controlled kinetics of carbon clusters has been examined by including a time-dependent surface correction to the Gibbs free energy of these clusters in the nonequilibrium CHEQ code. We also propose a new explosive burn model which incorporates a partial release of the heat of detonation in a fast reaction zone, followed by a diffusion-limited release of the remaining energy. Hydrodynamic applications of the new burn model to LX-17 show that computed expansion and compression results both agree closely with experimental data.

  3. Rotational and divergent kinetic energy in the mesoscale model ALADIN

    Directory of Open Access Journals (Sweden)

    V. Blažica

    2013-03-01

    Full Text Available Kinetic energy spectra from the mesoscale numerical weather prediction (NWP model ALADIN with horizontal resolution 4.4 km are split into divergent and rotational components which are then compared at horizontal scales below 300 km and various vertical levels. It is shown that about 50% of kinetic energy in the free troposphere in ALADIN is divergent energy. The percentage increases towards 70% near the surface and in the upper troposphere towards 100 hPa. The maximal percentage of divergent energy is found at stratospheric levels around 100 hPa and at scales below 100 km which are not represented by the global models. At all levels, the divergent energy spectra are characterised by shallower slopes than the rotational energy spectra, and the difference increases as horizontal scales become larger. A very similar vertical distribution of divergent energy is obtained by using the standard ALADIN approach for the computation of spectra based on the extension zone and by applying detrending approach commonly used in mesoscale NWP community.

  4. Multiple-relaxation-time lattice Boltzmann kinetic model for combustion.

    Science.gov (United States)

    Xu, Aiguo; Lin, Chuandong; Zhang, Guangcai; Li, Yingjun

    2015-04-01

    To probe both the hydrodynamic nonequilibrium (HNE) and thermodynamic nonequilibrium (TNE) in the combustion process, a two-dimensional multiple-relaxation-time (MRT) version of lattice Boltzmann kinetic model (LBKM) for combustion phenomena is presented. The chemical energy released in the progress of combustion is dynamically coupled into the system by adding a chemical term to the LB kinetic equation. Aside from describing the evolutions of the conserved quantities, the density, momentum, and energy, which are what the Navier-Stokes model describes, the MRT-LBKM presents also a coarse-grained description on the evolutions of some nonconserved quantities. The current model works for both subsonic and supersonic flows with or without chemical reaction. In this model, both the specific-heat ratio and the Prandtl number are flexible, the TNE effects are naturally presented in each simulation step. The model is verified and validated via well-known benchmark tests. As an initial application, various nonequilibrium behaviors, including the complex interplays between various HNEs, between various TNEs, and between the HNE and TNE, around the detonation wave in the unsteady and steady one-dimensional detonation processes are preliminarily probed. It is found that the system viscosity (or heat conductivity) decreases the local TNE, but increases the global TNE around the detonation wave, that even locally, the system viscosity (or heat conductivity) results in two kinds of competing trends, to increase and to decrease the TNE effects. The physical reason is that the viscosity (or heat conductivity) takes part in both the thermodynamic and hydrodynamic responses.

  5. A study of the kinetic energy generation with general circulation models

    Science.gov (United States)

    Chen, T.-C.; Lee, Y.-H.

    1983-01-01

    The history data of winter simulation by the GLAS climate model and the NCAR community climate model are used to examine the generation of atmospheric kinetic energy. The contrast between the geographic distributions of the generation of kinetic energy and divergence of kinetic energy flux shows that kinetic energy is generated in the upstream side of jets, transported to the downstream side and destroyed there. The contributions from the time-mean and transient modes to the counterbalance between generation of kinetic energy and divergence of kinetic energy flux are also investigated. It is observed that the kinetic energy generated by the time-mean mode is essentially redistributed by the time-mean flow, while that generated by the transient flow is mainly responsible for the maintenance of the kinetic energy of the entire atmospheric flow.

  6. Study on Lumped Kinetic Model for FDFCC I. Establishment of Model

    Institute of Scientific and Technical Information of China (English)

    Wu Feiyue; Weng Huixin; Luo Shixian

    2008-01-01

    According to the process features and the reaction mechanism of FDFCC technology, its two reaction subsystems, one for heavy oil riser reactor, the other for gasoline riser reactor, were respectively studied. Correspondingly, a 12-lump kinetic model for heavy oil FCC and a 9-lump kinetic model for gasoline catalytic upgrading were presented. Based on this work, mathematical correlation of the lumps in the feeds and products involved in the reaction subsystems and those of the overall reaction system were analyzed in detail. Then, a combined kinetic model for FDFCC, which was based on the data recovered from a commercial unit, was put forward. The reaction performance embodied by the kinetic constants for the combined model of FDFCC was in accordance with catalytic cracking reaction mechanism. The model-calculated values were close to the data obtained in commercial scale. The model was easy to be applied in practice and could also provide some theoretical groundwork for further research on kinetic model for FDFCC.

  7. Quantum kinetics and thermalization in a particle bath model.

    Science.gov (United States)

    Alamoudi, S M; Boyanovsky, D; de Vega, H J

    1999-07-01

    We study the dynamics of relaxation and thermalization in an exactly solvable model of a particle interacting with a harmonic oscillator bath. Our goal is to understand the effects of non-Markovian processes on the relaxational dynamics and to compare the exact evolution of the distribution function with approximate Markovian and non-Markovian quantum kinetics. There are two different cases that are studied in detail: (i) a quasiparticle (resonance) when the renormalized frequency of the particle is above the frequency threshold of the bath and (ii) a stable renormalized "particle" state below this threshold. The time evolution of the occupation number for the particle is evaluated exactly using different approaches that yield to complementary insights. The exact solution allows us to investigate the concept of the formation time of a quasiparticle and to study the difference between the relaxation of the distribution of bare particles and that of quasiparticles. For the case of quasiparticles, the exact occupation number asymptotically tends to a statistical equilibrium distribution that differs from a simple Bose-Einstein form as a result of off-shell processes whereas in the stable particle case, the distribution of particles does not thermalize with the bath. We derive a non-Markovian quantum kinetic equation which resums the perturbative series and includes off-shell effects. A Markovian approximation that includes off-shell contributions and the usual Boltzmann equation (energy conserving) are obtained from the quantum kinetic equation in the limit of wide separation of time scales upon different coarse-graining assumptions. The relaxational dynamics predicted by the non-Markovian, Markovian, and Boltzmann approximations are compared to the exact result. The Boltzmann approach is seen to fail in the case of wide resonances and when threshold and renormalization effects are important.

  8. Genome-scale reconstruction of the metabolic network in Yersinia pestis, strain 91001

    Energy Technology Data Exchange (ETDEWEB)

    Navid, A; Almaas, E

    2009-01-13

    The gram-negative bacterium Yersinia pestis, the aetiological agent of bubonic plague, is one the deadliest pathogens known to man. Despite its historical reputation, plague is a modern disease which annually afflicts thousands of people. Public safety considerations greatly limit clinical experimentation on this organism and thus development of theoretical tools to analyze the capabilities of this pathogen is of utmost importance. Here, we report the first genome-scale metabolic model of Yersinia pestis biovar Mediaevalis based both on its recently annotated genome, and physiological and biochemical data from literature. Our model demonstrates excellent agreement with Y. pestis known metabolic needs and capabilities. Since Y. pestis is a meiotrophic organism, we have developed CryptFind, a systematic approach to identify all candidate cryptic genes responsible for known and theoretical meiotrophic phenomena. In addition to uncovering every known cryptic gene for Y. pestis, our analysis of the rhamnose fermentation pathway suggests that betB is the responsible cryptic gene. Despite all of our medical advances, we still do not have a vaccine for bubonic plague. Recent discoveries of antibiotic resistant strains of Yersinia pestis coupled with the threat of plague being used as a bioterrorism weapon compel us to develop new tools for studying the physiology of this deadly pathogen. Using our theoretical model, we can study the cell's phenotypic behavior under different circumstances and identify metabolic weaknesses which may be harnessed for the development of therapeutics. Additionally, the automatic identification of cryptic genes expands the usage of genomic data for pharmaceutical purposes.

  9. Developing a computational model of human hand kinetics using AVS

    Energy Technology Data Exchange (ETDEWEB)

    Abramowitz, Mark S. [State Univ. of New York, Binghamton, NY (United States)

    1996-05-01

    As part of an ongoing effort to develop a finite element model of the human hand at the Institute for Scientific Computing Research (ISCR), this project extended existing computational tools for analyzing and visualizing hand kinetics. These tools employ a commercial, scientific visualization package called AVS. FORTRAN and C code, originally written by David Giurintano of the Gillis W. Long Hansen`s Disease Center, was ported to a different computing platform, debugged, and documented. Usability features were added and the code was made more modular and readable. When the code is used to visualize bone movement and tendon paths for the thumb, graphical output is consistent with expected results. However, numerical values for forces and moments at the thumb joints do not yet appear to be accurate enough to be included in ISCR`s finite element model. Future work includes debugging the parts of the code that calculate forces and moments and verifying the correctness of these values.

  10. A Global Modeling Framework for Plasma Kinetics: Development and Applications

    Science.gov (United States)

    Parsey, Guy Morland

    The modern study of plasmas, and applications thereof, has developed synchronously with com- puter capabilities since the mid-1950s. Complexities inherent to these charged-particle, many- body, systems have resulted in the development of multiple simulation methods (particle-in-cell, fluid, global modeling, etc.) in order to both explain observed phenomena and predict outcomes of plasma applications. Recognizing that different algorithms are chosen to best address specific topics of interest, this thesis centers around the development of an open-source global model frame- work for the focused study of non-equilibrium plasma kinetics. After verification and validation of the framework, it was used to study two physical phenomena: plasma-assisted combustion and the recently proposed optically-pumped rare gas metastable laser. Global models permeate chemistry and plasma science, relying on spatial averaging to focus attention on the dynamics of reaction networks. Defined by a set of species continuity and energy conservation equations, the required data and constructed systems are conceptually similar across most applications, providing a light platform for exploratory and result-search parameter scan- ning. Unfortunately, it is common practice for custom code to be developed for each application-- an enormous duplication of effort which negatively affects the quality of the software produced. Presented herein, the Python-based Kinetic Global Modeling framework (KGMf) was designed to support all modeling phases: collection and analysis of reaction data, construction of an exportable system of model ODEs, and a platform for interactive evaluation and post-processing analysis. A symbolic ODE system is constructed for interactive manipulation and generation of a Jacobian, both of which are compiled as operation-optimized C-code. Plasma-assisted combustion and ignition (PAC/PAI) embody the modernization of burning fuel by opening up new avenues of control and optimization

  11. Ab initio determination of kinetics for atomic layer deposition modeling

    Science.gov (United States)

    Remmers, Elizabeth M.

    A first principles model is developed to describe the kinetics of atomic layer deposition (ALD) systems. This model requires no fitting parameters, as it is based on the reaction pathways, structures, and energetics obtained from quantum-chemical studies. Using transition state theory and partition functions from statistical mechanics, equilibrium constants and reaction rates can be calculated. Several tools were created in Python to aid in the calculation of these quantities, and this procedure was applied to two systems- zinc oxide deposition from diethyl zinc (DEZ) and water, and alumina deposition from trimethyl aluminum (TMA) and water. A Gauss-Jordan factorization is used to decompose the system dynamics, and the resulting systems of equations are solved numerically to obtain the temporal concentration profiles of these two deposition systems.

  12. Kinetic modelling of runaway electrons in dynamic scenarios

    CERN Document Server

    Stahl, A; Papp, G; Landreman, M; Fülöp, T

    2016-01-01

    Improved understanding of runaway-electron formation and decay processes are of prime interest for the safe operation of large tokamaks, and the dynamics of the runaway electrons during dynamical scenarios such as disruptions are of particular concern. In this paper, we present kinetic modelling of scenarios with time-dependent plasma parameters; in particular, we investigate hot-tail runaway generation during a rapid drop in plasma temperature. With the goal of studying runaway-electron generation with a self-consistent electric-field evolution, we also discuss the implementation of a conservative collision operator and demonstrate its properties. An operator for avalanche runaway-electron generation, which takes the energy dependence of the scattering cross section and the runaway distribution into account, is investigated. We show that the simpler avalanche model of Rosenbluth & Putvinskii [Nucl. Fusion 37, 1355 (1997)] can give very inaccurate results for the avalanche growth rate (either lower or hig...

  13. High Temperature Chemical Kinetic Combustion Modeling of Lightly Methylated Alkanes

    Energy Technology Data Exchange (ETDEWEB)

    Sarathy, S M; Westbrook, C K; Pitz, W J; Mehl, M

    2011-03-01

    Conventional petroleum jet and diesel fuels, as well as alternative Fischer-Tropsch (FT) fuels and hydrotreated renewable jet (HRJ) fuels, contain high molecular weight lightly branched alkanes (i.e., methylalkanes) and straight chain alkanes (n-alkanes). Improving the combustion of these fuels in practical applications requires a fundamental understanding of large hydrocarbon combustion chemistry. This research project presents a detailed high temperature chemical kinetic mechanism for n-octane and three lightly branched isomers octane (i.e., 2-methylheptane, 3-methylheptane, and 2,5-dimethylhexane). The model is validated against experimental data from a variety of fundamental combustion devices. This new model is used to show how the location and number of methyl branches affects fuel reactivity including laminar flame speed and species formation.

  14. Parameter estimation for models of ligninolytic and cellulolytic enzyme kinetics

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Gangsheng [ORNL; Post, Wilfred M [ORNL; Mayes, Melanie [ORNL; Frerichs, Joshua T [ORNL; Jagadamma, Sindhu [ORNL

    2012-01-01

    While soil enzymes have been explicitly included in the soil organic carbon (SOC) decomposition models, there is a serious lack of suitable data for model parameterization. This study provides well-documented enzymatic parameters for application in enzyme-driven SOC decomposition models from a compilation and analysis of published measurements. In particular, we developed appropriate kinetic parameters for five typical ligninolytic and cellulolytic enzymes ( -glucosidase, cellobiohydrolase, endo-glucanase, peroxidase, and phenol oxidase). The kinetic parameters included the maximum specific enzyme activity (Vmax) and half-saturation constant (Km) in the Michaelis-Menten equation. The activation energy (Ea) and the pH optimum and sensitivity (pHopt and pHsen) were also analyzed. pHsen was estimated by fitting an exponential-quadratic function. The Vmax values, often presented in different units under various measurement conditions, were converted into the same units at a reference temperature (20 C) and pHopt. Major conclusions are: (i) Both Vmax and Km were log-normal distributed, with no significant difference in Vmax exhibited between enzymes originating from bacteria or fungi. (ii) No significant difference in Vmax was found between cellulases and ligninases; however, there was significant difference in Km between them. (iii) Ligninases had higher Ea values and lower pHopt than cellulases; average ratio of pHsen to pHopt ranged 0.3 0.4 for the five enzymes, which means that an increase or decrease of 1.1 1.7 pH units from pHopt would reduce Vmax by 50%. (iv) Our analysis indicated that the Vmax values from lab measurements with purified enzymes were 1 2 orders of magnitude higher than those for use in SOC decomposition models under field conditions.

  15. Kinetic modelling of central carbon metabolism in Escherichia coli.

    Science.gov (United States)

    Peskov, Kirill; Mogilevskaya, Ekaterina; Demin, Oleg

    2012-09-01

    In the present study, we developed a detailed kinetic model of Escherichia coli central carbon metabolism. The main model assumptions were based on the results of metabolic and regulatory reconstruction of the system and thorough model verification with experimental data. The development and verification of the model included several stages, which allowed us to take into account both in vitro and in vivo experimental data and avoid the ambiguity that frequently occurs in detailed models of biochemical pathways. The choice of the level of detail for the mathematical description of enzymatic reaction rates and the evaluation of parameter values were based on available published data. Validation of the complete model of the metabolic pathway describing specific physiological states was based on fluxomics and metabolomics data. In particular, we developed a model that describes aerobic growth of E. coli in continuous culture with a limiting concentration of glucose. Such modification of the model was used to integrate experimental metabolomics data obtained in steady-state conditions for wild-type E. coli and genetically modified strains, e.g. knockout of the pyruvate kinase gene (pykA). Following analysis of the model behaviour, and comparison of the coincidence between predicted and experimental data, it was possible to investigate the functional and regulatory properties of E. coli central carbon metabolism. For example, a novel metabolic regulatory mechanism for 6-phosphogluconate dehydrogenase inhibition by phosphoenolpyruvate was hypothesized, and the flux ratios between the reactions catalysed by enzyme isoforms were predicted. The mathematical model described here has been submitted to the JWS Online Cellular Systems Modelling Database and can be accessed at http://jjj.biochem.sun.ac.za/database/peskov/index.html © 2012 The Authors Journal compilation © 2012 FEBS.

  16. Elementary Processes and Kinetic Modeling for Hydrogen and Helium Plasmas

    Directory of Open Access Journals (Sweden)

    Roberto Celiberto

    2017-05-01

    Full Text Available We report cross-sections and rate coefficients for excited states colliding with electrons, heavy particles and walls useful for the description of H 2 /He plasma kinetics under different conditions. In particular, the role of the rotational states in resonant vibrational excitations of the H 2 molecule by electron impact and the calculation of the related cross-sections are illustrated. The theoretical determination of the cross-section for the rovibrational energy exchange and dissociation of H 2 molecule, induced by He atom impact, by using the quasi-classical trajectory method is discussed. Recombination probabilities of H atoms on tungsten and graphite, relevant for the determination of the nascent vibrational distribution, are also presented. An example of a state-to-state plasma kinetic model for the description of shock waves operating in H 2 and He-H 2 mixtures is presented, emphasizing also the role of electronically-excited states in affecting the electron energy distribution function of free electrons. Finally, the thermodynamic properties and the electrical conductivity of non-ideal, high-density hydrogen plasma are finally discussed, in particular focusing on the pressure ionization phenomenon in high-pressure high-temperature plasmas.

  17. Pyrolysis Kinetic Modelling of Wheat Straw from the Pannonian Region

    Directory of Open Access Journals (Sweden)

    Ivan Pešenjanski

    2016-01-01

    Full Text Available The pyrolysis/devolatilization is a basic step of thermochemical processes and requires fundamental characterization. In this paper, the kinetic model of pyrolysis is specified as a one-step global reaction. This type of reaction is used to describe the thermal degradation of wheat straw samples by measuring rates of mass loss of solid matter at a linear increase in temperature. The mentioned experiments were carried out using a derivatograph in an open-air environment. The influence of different factors was investigated, such as particle size, humidity levels, and the heating rate in the kinetics of devolatilization. As the measured values of mass loss and temperature functions transform in Arrhenius coordinates, the results are shown in the form of saddle curves. Such characteristics cannot be approximated with one equation in the form of Arrhenius law. For use in numerical applications, transformed functions can be approximated by linear regression for three separate intervals. Analysis of measurement resulting in granulation and moisture content variations shows that these factors have no significant influence. Tests of heating rate variations confirm the significance of this impact, especially in warmer regions. The influence of this factor should be more precisely investigated as a general variable, which should be the topic of further experiments.

  18. Integration Strategies for Efficient Multizone Chemical Kinetics Models

    Energy Technology Data Exchange (ETDEWEB)

    McNenly, M J; Havstad, M A; Aceves, S M; Pitz, W J

    2009-10-15

    Three integration strategies are developed and tested for the stiff, ordinary differential equation (ODE) integrators used to solve the fully coupled multizone chemical kinetics model. Two of the strategies tested are found to provide more than an order of magnitude of improvement over the original, basic level of usage for the stiff ODE solver. One of the faster strategies uses a decoupled, or segregated, multizone model to generate an approximate Jacobian. This approach yields a 35-fold reduction in the computational cost for a 20 zone model. Using the same approximate Jacobian as a preconditioner for an iterative Krylov-type linear system solver, the second improved strategy achieves a 75-fold reduction in the computational cost for a 20 zone model. The faster strategies achieve their cost savings with no significant loss of accuracy. The pressure, temperature and major species mass fractions agree with the solution from the original integration approach to within six significant digits; and the radical mass fractions agree with the original solution to within four significant digits. The faster strategies effectively change the cost scaling of the multizone model from cubic to quadratic, with respect to the number of zones. As a consequence of the improved scaling, the 40 zone model offers more than a 250-fold cost savings over the basic calculation.

  19. Kinetic Model of Biogas Yield Production from Vinasse at Various Initial pH: Comparison between Modified Gompertz Model and First Order Kinetic Model

    Directory of Open Access Journals (Sweden)

    Budiyono

    2014-04-01

    Full Text Available Anaerobic treatment using anaerobic digestion can convert organic materials of vinasse into biogas. The purpose of this study was modeling kinetic of biogas production using modified Gompertz model and first order kinetic model at variation of initial pH. Substrates were consisted of two kinds of compositions, which were vinasse+rumen (VR and vinasse+rumen+urea (VRU. Initial pH in each substrate was 6, 7 and 8. Degradation process was done in 30 days using batch anaerobic digesters at room temperature. Both, at VR and VRU, initial pH of 7 generated the more total biogas than the others two (initial pH of 6 and 8. Biogas formed at substrate of VRU was more than that at substrate of VR. The best condition was substrate of VRU and initial pH of 7. At best condition, kinetic constants of biogas production model using modified Gompertz were ym (biogas production potential = 6.49 mL/g VS; U (maximum biogas production rate = 1.24 mL/g VS. day; &lambda (minimum time to produce biogas = 1.79 days. Whereas kinetic constants of biogas production model using first order kinetic were ym (biogas production potential = 6.78 mL/g VS; k (biogas production rate = 0.176 /day. The difference between the predicted and measured biogas yield (fitting error was higher with the first-order kinetic model (1.54-7.50% than with the modified Gompertz model (0.76-3.14%.

  20. Genome-scale metabolic representation of Amycolatopsis balhimycina

    DEFF Research Database (Denmark)

    Vongsangnak, Wanwipa; Figueiredo, L. F.; Förster, Jochen

    2012-01-01

    EC numbers, 647 metabolites and 1,363 metabolic reactions. During the analysis of the metabolic model, linear, quadratic and evolutionary programming algorithms using flux balance analysis (FBA), minimization of metabolic adjustment (MOMA), and OptGene, respectively were applied as well as phenotypic...... biosynthesis in Amycolatopsis balhimycina. The balhimycin yield obtained by A. balhimycina is, however, low and there is therefore a need to improve balhimycin production. In this study, we performed genome sequencing, assembly and annotation analysis of A. balhimycina and further used these annotated data...... to reconstruct a genome‐scale metabolic model for the organism. Here we generated an almost complete A. balhimycina genome sequence comprising 10,562,587 base pairs assembled into 2,153 contigs. The high GC‐genome (∼69%) includes 8,585 open reading frames (ORFs). We used our integrative toolbox called SEQTOR...

  1. SHARP: genome-scale identification of gene-protein-reaction associations in cyanobacteria.

    Science.gov (United States)

    Krishnakumar, S; Durai, Dilip A; Wangikar, Pramod P; Viswanathan, Ganesh A

    2013-11-01

    Genome scale metabolic model provides an overview of an organism's metabolic capability. These genome-specific metabolic reconstructions are based on identification of gene to protein to reaction (GPR) associations and, in turn, on homology with annotated genes from other organisms. Cyanobacteria are photosynthetic prokaryotes which have diverged appreciably from their nonphotosynthetic counterparts. They also show significant evolutionary divergence from plants, which are well studied for their photosynthetic apparatus. We argue that context-specific sequence and domain similarity can add to the repertoire of the GPR associations and significantly expand our view of the metabolic capability of cyanobacteria. We took an approach that combines the results of context-specific sequence-to-sequence similarity search with those of sequence-to-profile searches. We employ PSI-BLAST for the former, and CDD, Pfam, and COG for the latter. An optimization algorithm was devised to arrive at a weighting scheme to combine the different evidences with KEGG-annotated GPRs as training data. We present the algorithm in the form of software "Systematic, Homology-based Automated Re-annotation for Prokaryotes (SHARP)." We predicted 3,781 new GPR associations for the 10 prokaryotes considered of which eight are cyanobacteria species. These new GPR associations fall in several metabolic pathways and were used to annotate 7,718 gaps in the metabolic network. These new annotations led to discovery of several pathways that may be active and thereby providing new directions for metabolic engineering of these species for production of useful products. Metabolic model developed on such a reconstructed network is likely to give better phenotypic predictions.

  2. The architecture of ArgR-DNA complexes at the genome-scale in> Escherichia coli

    DEFF Research Database (Denmark)

    Cho, Suhyung; Cho, Yoo-Bok; Kang, Taek Jin;

    2015-01-01

    DNA-binding motifs that are recognized by transcription factors (TFs) have been well studied; however, challenges remain in determining the in vivo architecture of TF-DNA complexes on a genome-scale. Here, we determined the in vivo architecture of Escherichia coli arginine repressor (ArgR)-DNA co...

  3. A versatile genome-scale PCR-based pipeline for high-definition DNA FISH

    NARCIS (Netherlands)

    Bienko, M.; Crosetto, N.; Teytelman, L.; Klemm, S.; Itzkovitz, S.; van Oudenaarden, A.

    2013-01-01

    We developed a cost-effective genome-scale PCR-based method for high-definition DNA FISH (HD-FISH). We visualized gene loci with diffraction-limited resolution, chromosomes as spot clusters and single genes together with transcripts by combining HD-FISH with single-molecule RNA FISH. We provide a da

  4. Kinetic modeling and sensitivity analysis of plasma-assisted combustion

    Science.gov (United States)

    Togai, Kuninori

    Plasma-assisted combustion (PAC) is a promising combustion enhancement technique that shows great potential for applications to a number of different practical combustion systems. In this dissertation, the chemical kinetics associated with PAC are investigated numerically with a newly developed model that describes the chemical processes induced by plasma. To support the model development, experiments were performed using a plasma flow reactor in which the fuel oxidation proceeds with the aid of plasma discharges below and above the self-ignition thermal limit of the reactive mixtures. The mixtures used were heavily diluted with Ar in order to study the reactions with temperature-controlled environments by suppressing the temperature changes due to chemical reactions. The temperature of the reactor was varied from 420 K to 1250 K and the pressure was fixed at 1 atm. Simulations were performed for the conditions corresponding to the experiments and the results are compared against each other. Important reaction paths were identified through path flux and sensitivity analyses. Reaction systems studied in this work are oxidation of hydrogen, ethylene, and methane, as well as the kinetics of NOx in plasma. In the fuel oxidation studies, reaction schemes that control the fuel oxidation are analyzed and discussed. With all the fuels studied, the oxidation reactions were extended to lower temperatures with plasma discharges compared to the cases without plasma. The analyses showed that radicals produced by dissociation of the reactants in plasma plays an important role of initiating the reaction sequence. At low temperatures where the system exhibits a chain-terminating nature, reactions of HO2 were found to play important roles on overall fuel oxidation. The effectiveness of HO2 as a chain terminator was weakened in the ethylene oxidation system, because the reactions of C 2H4 + O that have low activation energies deflects the flux of O atoms away from HO2. For the

  5. Kinetic Modeling of Incremental Ambulatory Peritoneal Dialysis Exchanges.

    Science.gov (United States)

    Guest, Steven; Leypoldt, John K; Cassin, Michelle; Schreiber, Martin

    2017-01-01

    ♦ BACKGROUND: Incremental peritoneal dialysis (PD), the gradual introduction of dialysate exchanges at less than full-dose therapy, has been infrequently described in clinical reports. One concern with less than full-dose dialysis is whether urea clearance targets are achievable with an incremental regimen. In this report, we used a large database of PD patients, across all membrane transport types, and performed urea kinetic modeling determinations of possible incremental regimens for an individual membrane type. ♦ METHODS: Using a modified 3-pore model of peritoneal transport, various incremental manual continuous ambulatory PD (CAPD) exchanges employing glucose and/or icodextrin were evaluated. Peritoneal urea clearances from those simulations were added to residual kidney urea clearance for patients with various glomerular filtration rates (GFRs), and the total weekly urea clearance was then compared to the total weekly urea Kt/V target of 1.7. All 4 peritoneal membrane types were modeled. For each simulated prescription, net ultrafiltration and carbohydrate absorption were also calculated. ♦ RESULTS: Incremental CAPD regimens of 2 exchanges a day met adequacy targets if the GFR was 6 mL/min/1.73 m(2) in all membrane types. For regimens employing 3 exchanges a day, Kt/V targets were achieved at GFR levels of 4 to 5 mL/min/1.73 m(2) in high transporters to low transporters but higher tonicity 2.5% glucose solutions or icodextrin were required in some regimens. ♦ CONCLUSIONS: This work demonstrates that with incremental CAPD regimens, urea kinetic targets are achievable in most new starts to PD with residual kidney function. Incremental PD may be a less intrusive, better accepted initial treatment regime and a cost-effective way to initiate chronic dialysis in the incident patient. The key role of intrinsic kidney function in incremental regimens is highlighted in this analysis and would warrant conscientious monitoring. Copyright © 2017 International

  6. Analysis of Aspergillus nidulans metabolism at the genome-scale

    DEFF Research Database (Denmark)

    David, Helga; Ozcelik, İlknur Ş; Hofmann, Gerald

    2008-01-01

    Background: Aspergillus nidulans is a member of a diverse group of filamentous fungi, sharing many of the properties of its close relatives with significance in the fields of medicine, agriculture and industry. Furthermore, A. nidulans has been a classical model organism for studies of development...... biology and gene regulation, and thus it has become one of the best-characterized filamentous fungi. It was the first Aspergillus species to have its genome sequenced, and automated gene prediction tools predicted 9,451 open reading frames (ORFs) in the genome, of which less than 10% were assigned...

  7. Adaptation of the microdosimetric kinetic model to hypoxia

    Science.gov (United States)

    Bopp, C.; Hirayama, R.; Inaniwa, T.; Kitagawa, A.; Matsufuji, N.; Noda, K.

    2016-11-01

    Ion beams present a potential advantage in terms of treatment of lesions with hypoxic regions. In order to use this potential, it is important to accurately model the cell survival of oxic as well as hypoxic cells. In this work, an adaptation of the microdosimetric kinetic (MK) model making it possible to account for cell hypoxia is presented. The adaptation relies on the modification of damage quantity (double strand breaks and more complex lesions) due to the radiation. Model parameters such as domain size and nucleus size are then adapted through a fitting procedure. We applied this approach to two cell lines, HSG and V79 for helium, carbon and neon ions. A similar behaviour of the parameters was found for the two cell lines, namely a reduction of the domain size and an increase in the sensitive nuclear volume of hypoxic cells compared to those of oxic cells. In terms of oxygen enhancement ratio (OER), the experimental data behaviour can be reproduced, including dependence on particle type at the same linear energy transfer (LET). Errors on the cell survival prediction are of the same order of magnitude than for the original MK model. Our adaptation makes it possible to account for hypoxia without modelling the OER as a function of the LET of the particles, but directly accounting for hypoxic cell survival data.

  8. A genome-scale metabolic network reconstruction of tomato (Solanum lycopersicum L.) and its application to photorespiratory metabolism.

    Science.gov (United States)

    Yuan, Huili; Cheung, C Y Maurice; Poolman, Mark G; Hilbers, Peter A J; van Riel, Natal A W

    2016-01-01

    Tomato (Solanum lycopersicum L.) has been studied extensively due to its high economic value in the market, and high content in health-promoting antioxidant compounds. Tomato is also considered as an excellent model organism for studying the development and metabolism of fleshy fruits. However, the growth, yield and fruit quality of tomatoes can be affected by drought stress, a common abiotic stress for tomato. To investigate the potential metabolic response of tomato plants to drought, we reconstructed iHY3410, a genome-scale metabolic model of tomato leaf, and used this metabolic network to simulate tomato leaf metabolism. The resulting model includes 3410 genes and 2143 biochemical and transport reactions distributed across five intracellular organelles including cytosol, plastid, mitochondrion, peroxisome and vacuole. The model successfully described the known metabolic behaviour of tomato leaf under heterotrophic and phototrophic conditions. The in silico investigation of the metabolic characteristics for photorespiration and other relevant metabolic processes under drought stress suggested that: (i) the flux distributions through the mevalonate (MVA) pathway under drought were distinct from that under normal conditions; and (ii) the changes in fluxes through core metabolic pathways with varying flux ratio of RubisCO carboxylase to oxygenase may contribute to the adaptive stress response of plants. In addition, we improved on previous studies of reaction essentiality analysis for leaf metabolism by including potential alternative routes for compensating reaction knockouts. Altogether, the genome-scale model provides a sound framework for investigating tomato metabolism and gives valuable insights into the functional consequences of abiotic stresses. © 2015 The Authors.The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.

  9. Kinetic effects of adriamycin and bleomycin on two osteosarcoma models.

    Science.gov (United States)

    Bell, D F; Bell, R S; Mankin, H J; Gebhardt, M C; Weltie, F; O'Brien, T

    1988-01-01

    Although chemotherapeutic drugs are frequently administered to patients with osteosarcoma, there has been little research into the effect of cytotoxic drugs on osteosarcoma cell biology. The effect of two drugs (Adriamycin and bleomycin) on cell cycle kinetics was investigated in vitro in an established line of human osteosarcoma cells and in vivo using the Dunn osteosarcoma model. The cell cycle changes were consistent with G2 arrest for both drugs in vivo and in vitro. The alteration in cell cycle distribution was correlated with inhibition of 3H-thymidine incorporation in vitro. In vivo, the greater change in cell cycle distribution caused by Adriamycin was reflected in the increased inhibition of tumor growth found with this drug.

  10. Formulation and kinetic modeling of curcumin loaded intranasal mucoadhesive microemulsion

    Directory of Open Access Journals (Sweden)

    B Mikesh Patel

    2012-01-01

    Full Text Available It is a challenge to develop the optimum dosage form of poorly water-soluble drugs and to target them due to limited bioavailability, intra and inter subject variability. In this investigation, mucoadhesive microemulsion of curcumin was developed by water titration method taking biocompatible components for intranasal delivery and was characterized. Nasal ciliotoxicity studies were carried out using excised sheep nasal mucosa. in vitro release studies of formulations and PDS were performed. Labrafil M 1944 CS based microemulsion was transparent, stable and nasal non-ciliotoxic having particle size 12.32±0.81nm (PdI=0.223 and from kinetic modeling, the release was found to be Fickian diffusion for mucoadhesive microemulsion.

  11. An Experimental and Kinetic Modeling Study of Methyl Decanoate Combustion

    Energy Technology Data Exchange (ETDEWEB)

    Sarathy, S M; Thomson, M J; Pitz, W J; Lu, T

    2010-02-19

    Biodiesel is typically a mixture of long chain fatty acid methyl esters for use in compression ignition engines. Improving biofuel engine performance requires understanding its fundamental combustion properties and the pathways of combustion. This research study presents new combustion data for methyl decanoate in an opposed-flow diffusion flame. An improved detailed chemical kinetic model for methyl decanoate combustion is developed, which serves as the basis for deriving a skeletal mechanism via the direct relation graph method. The novel skeletal mechanism consists of 648 species and 2998 reactions. This mechanism well predicts the methyl decanoate opposed-flow diffusion flame data. The results from the flame simulations indicate that methyl decanoate is consumed via abstraction of hydrogen atoms to produce fuel radicals, which lead to the production of alkenes. The ester moiety in methyl decanoate leads to the formation of low molecular weight oxygenated compounds such as carbon monoxide, formaldehyde, and ketene.

  12. Testing a dissipative kinetic k-essence model

    CERN Document Server

    Cardenas, V H; Villanueva, J R

    2015-01-01

    In this work, we present a study of a purely kinetic k-essence model, characterized basically by a parameter $\\alpha$ in presence of a bulk dissipative term, whose relationship between viscous pressure $\\Pi$ and energy density $\\rho$ of the background follows a polytropic type law $\\Pi \\propto \\rho^{\\lambda+1/2}$, where $\\lambda$, in principle, is a parameter without restrictions. Analytical solutions for the energy density of the k-essence field are found in two specific cases: $\\lambda=1/2$ and $\\lambda=(1-\\alpha)/2\\alpha$, and then we show that these solutions posses the same functional form than the non-viscous counterpart. Finally, both approach are contrasted with observational data from type Ia supernova, and the most recent Hubble parameter measurements, and therefore, the best values for the parameters of the theory are founds.

  13. Testing a dissipative kinetic k-essence model

    Energy Technology Data Exchange (ETDEWEB)

    Cardenas, Victor H.; Villanueva, J.R. [Universidad de Valparaiso, Instituto de Fisica y Astronomia, Valparaiso (Chile); Centro de Astrofisica de Valparaiso, Valparaiso (Chile); Cruz, Norman [Universidad de Santiago de Chile, Departamento de Fisica, Santiago (Chile)

    2015-04-01

    In thiswork,we present a study of a purely kinetic k-essence model, characterized basically by a parameter α in presence of a bulk dissipative term, whose relationship between viscous pressure Π and energy density ρ of the background follows a polytropic type law, Π ∝ ρ{sup λ+1/2}, where λ, in principle, is a parameter without restrictions. Analytical solutions for the energy density of the k-essence field are found in two specific cases: λ = 1/2 and λ = (1 - α)/2α, and then we show that these solutions possess the same functional form as the non-viscous counterpart. Finally, both approaches are contrasted with observational data from type Ia supernova, and the most recent Hubble parameter measurements, and therefore, the best values for the parameters of the theory are found. (orig.)

  14. Phase transition in kinetic exchange opinion models with independence

    CERN Document Server

    Crokidakis, Nuno

    2014-01-01

    In this work we study the critical behavior of a three-state ($+1$, $-1$, $0$) opinion model with independence. Each agent has a probability $q$ to act as independent, i.e., he/she can choose his/her opinion independently of the opinions of the other agents. On the other hand, with the complementary probability $1-q$ the agent interacts with a randomly chosen individual through a kinetic exchange. Our analytical and numerical results show that the independence mechanism acts as a noise that induce an order-disorder transition at critical points $q_{c}$ that depend on the individuals' flexibility. For a special value of this flexibility the system undergoes a transition to an absorbing state with all opinions $0$.

  15. Thermal stability of n-dodecane : experiments and kinetic modelling

    CERN Document Server

    Herbinet, Olivier; Battin-Leclerc, Frédérique; Fournet, René

    2007-01-01

    The thermal decomposition of n-dodecane, a component of some jet fuels, has been studied in a jet-stirred reactor at temperatures from 793 to 1093 K, for residence times between 1 and 5 s and at atmospheric pressure. Thermal decomposition of hydrocarbon fuel prior the entrance in the combustion chamber is an envisaged way to cool the wall of hypersonic vehicles. The products of the reaction are mainly hydrogen, methane, ethane, 1,3-butadiene and 1-alkenes from ethylene to 1-undecene. For higher temperatures and residence times acetylene, allene, propyne, cyclopentene, 1,3-cyclopentadiene and aromatic compounds from benzene to pyrene through naphthalene have also been observed. A previous detailed kinetic model of the thermal decomposition of n-dodecane generated using EXGAS software has been improved and completed by a sub-mechanism explaining the formation and the consumption of aromatic compounds.

  16. Kinetic Model for a Spherical Rolling Robot with Soft Shell in a Beeline Motion

    Directory of Open Access Journals (Sweden)

    Sheng Zhang

    2014-02-01

    Full Text Available A simplified kinetic model called Spring Pendulum is developed for a spherical rolling robot with soft shell in order to meet the needs of attitude stabilization and controlling for the robot. The elasticity and plasticity of soft shell is represented by some uniform springs connected to the bracket in this model. The expression of the kinetic model is deduced from Newtonian mechanics principles. Testing data of the driving angle acquired from a prototype built by authors indicate that testing data curve accords to the theoretic kinetic characteristic curve, so the kinetic model is validated

  17. Critical Analysis of Underground Coal Gasification Models. Part II: Kinetic and Computational Fluid Dynamics Models

    Directory of Open Access Journals (Sweden)

    Alina Żogała

    2014-01-01

    Originality/value: This paper presents state of art in the field of coal gasification modeling using kinetic and computational fluid dynamics approach. The paper also presents own comparative analysis (concerned with mathematical formulation, input data and parameters, basic assumptions, obtained results etc. of the most important models of underground coal gasification.

  18. Exploring massive, genome scale datasets with the genometricorr package

    KAUST Repository

    Favorov, Alexander

    2012-05-31

    We have created a statistically grounded tool for determining the correlation of genomewide data with other datasets or known biological features, intended to guide biological exploration of high-dimensional datasets, rather than providing immediate answers. The software enables several biologically motivated approaches to these data and here we describe the rationale and implementation for each approach. Our models and statistics are implemented in an R package that efficiently calculates the spatial correlation between two sets of genomic intervals (data and/or annotated features), for use as a metric of functional interaction. The software handles any type of pointwise or interval data and instead of running analyses with predefined metrics, it computes the significance and direction of several types of spatial association; this is intended to suggest potentially relevant relationships between the datasets. Availability and implementation: The package, GenometriCorr, can be freely downloaded at http://genometricorr.sourceforge.net/. Installation guidelines and examples are available from the sourceforge repository. The package is pending submission to Bioconductor. © 2012 Favorov et al.

  19. Generic phase coexistence in the totally asymmetric kinetic Ising model

    Science.gov (United States)

    Godrèche, Claude; Luck, Jean-Marc

    2017-07-01

    The physical analysis of generic phase coexistence in the North-East-Center Toom model was originally given by Bennett and Grinstein. The gist of their argument relies on the dynamics of interfaces and droplets. We revisit the same question for a specific totally asymmetric kinetic Ising model on the square lattice. This nonequilibrium model possesses the remarkable property that its stationary-state measure in the absence of a magnetic field coincides with that of the usual ferromagnetic Ising model. We use both analytical arguments and numerical simulations in order to make progress in the quantitative understanding of the phenomenon of generic phase coexistence. At zero temperature a mapping onto the TASEP allows an exact determination of the time-dependent shape of the ballistic interface sweeping a large square minority droplet of up or down spins. At finite temperature, measuring the mean lifetime of such a droplet allows an accurate measurement of its shrinking velocity v, which depends on temperature T and magnetic field h. In the absence of a magnetic field, v vanishes with an exponent Δ_v≈2.5+/-0.2 as the critical temperature T c is approached. At fixed temperature in the ordered phase, v vanishes at the phase-boundary fields +/- h_b(T) which mark the limits of the coexistence region. The latter fields vanish with an exponent Δ_h≈3.2+/-0.3 as T c is approached.

  20. Detailed kinetic modeling study of n-pentanol oxidation

    KAUST Repository

    Heufer, Karl Alexander

    2012-10-18

    To help overcome the world\\'s dependence upon fossil fuels, suitable biofuels are promising alternatives that can be used in the transportation sector. Recent research on internal combustion engines shows that short alcoholic fuels (e.g., ethanol or n-butanol) have reduced pollutant emissions and increased knock resistance compared to fossil fuels. Although higher molecular weight alcohols (e.g., n-pentanol and n-hexanol) exhibit higher reactivity that lowers their knock resistance, they are suitable for diesel engines or advanced engine concepts, such as homogeneous charge compression ignition (HCCI), where higher reactivity at lower temperatures is necessary for engine operation. The present study presents a detailed kinetic model for n-pentanol based on modeling rules previously presented for n-butanol. This approach was initially validated using quantum chemistry calculations to verify the most stable n-pentanol conformation and to obtain C-H and C-C bond dissociation energies. The proposed model has been validated against ignition delay time data, speciation data from a jet-stirred reactor, and laminar flame velocity measurements. Overall, the model shows good agreement with the experiments and permits a detailed discussion of the differences between alcohols and alkanes. © 2012 American Chemical Society.

  1. Scale-up and kinetic modeling for bioethanol production.

    Science.gov (United States)

    Imamoglu, Esra; Sukan, Fazilet Vardar

    2013-09-01

    Bioethanol was produced from acidic hydrolysate of rice hulls using recombinant Escherichia coli KO11. Two different issues (scale-up and kinetic modeling) were evaluated simultaneously and concomitantly for bioethanol production. During the step-wise scale-up process from 100 mL shaken flask to 10 L stirred-tank bioreactor, the constant Reynolds number and the constant impeller tip speed were evaluated as scale-up methodologies under laboratory conditions. It was determined that the volumetric bioethanol productivity was 88% higher in 10 L bioreactor in comparison to the value of 0.21 g L(-1) h(-1) in shaken flask. The modified Monod and Luedeking-Piret models provided an accurate approach for the modeling of the experimental data. Ethanol concentration reached the maximum level of 29.03 g/L, which was 5% higher than the value of model prediction in 10 L bioreactor. The findings of this research could contribute to the industrial scale productions especially from lignocellulosic raw materials.

  2. Gompertz kinetics model of fast chemical neurotransmission currents.

    Science.gov (United States)

    Easton, Dexter M

    2005-10-01

    At a chemical synapse, transmitter molecules ejected from presynaptic terminal(s) bind reversibly with postsynaptic receptors and trigger an increase in channel conductance to specific ions. This paper describes a simple but accurate predictive model for the time course of the synaptic conductance transient, based on Gompertz kinetics. In the model, two simple exponential decay terms set the rates of development and decline of transmitter action. The first, r, triggering conductance activation, is surrogate for the decelerated rate of growth of conductance, G. The second, r', responsible for Y, deactivation of the conductance, is surrogate for the decelerated rate of decline of transmitter action. Therefore, the differential equation for the net conductance change, g, triggered by the transmitter is dg/dt=g(r-r'). The solution of that equation yields the product of G(t), representing activation, and Y(t), which defines the proportional decline (deactivation) of the current. The model fits, over their full-time course, published records of macroscopic ionic current associated with fast chemical transmission. The Gompertz model is a convenient and accurate method for routine analysis and comparison of records of synaptic current and putative transmitter time course. A Gompertz fit requiring only three independent rate constants plus initial current appears indistinguishable from a Markov fit using seven rate constants.

  3. Construction of the simplest model to explain complex receptor activation kinetics

    DEFF Research Database (Denmark)

    Bywater, RP; Sorensen, A; Røgen, Peter;

    2002-01-01

    We study the mathematical solutions to the kinetic equations arising from various simple ligand-reactor models. Focusing on the prediction of the various models for the activity vs. concentration curve, we find that solutions to the kinetic equations arising from the so-called dimer model exibit...

  4. Genome-scale reconstruction and in silico analysis of the Ralstonia eutropha H16 for polyhydroxyalkanoate synthesis, lithoautotrophic growth, and 2-methyl citric acid production

    Directory of Open Access Journals (Sweden)

    Kim Tae

    2011-06-01

    Full Text Available Abstract Background Ralstonia eutropha H16, found in both soil and water, is a Gram-negative lithoautotrophic bacterium that can utillize CO2 and H2 as its sources of carbon and energy in the absence of organic substrates. R. eutropha H16 can reach high cell densities either under lithoautotrophic or heterotrophic conditions, which makes it suitable for a number of biotechnological applications. It is the best known and most promising producer of polyhydroxyalkanoates (PHAs from various carbon substrates and is an environmentally important bacterium that can degrade aromatic compounds. In order to make R. eutropha H16 a more efficient and robust biofactory, system-wide metabolic engineering to improve its metabolic performance is essential. Thus, it is necessary to analyze its metabolic characteristics systematically and optimize the entire metabolic network at systems level. Results We present the lithoautotrophic genome-scale metabolic model of R. eutropha H16 based on the annotated genome with biochemical and physiological information. The stoichiometic model, RehMBEL1391, is composed of 1391 reactions including 229 transport reactions and 1171 metabolites. Constraints-based flux analyses were performed to refine and validate the genome-scale metabolic model under environmental and genetic perturbations. First, the lithoautotrophic growth characteristics of R. eutropha H16 were investigated under varying feeding ratios of gas mixture. Second, the genome-scale metabolic model was used to design the strategies for the production of poly[R-(--3hydroxybutyrate] (PHB under different pH values and carbon/nitrogen source uptake ratios. It was also used to analyze the metabolic characteristics of R. eutropha when the phosphofructokinase gene was expressed. Finally, in silico gene knockout simulations were performed to identify targets for metabolic engineering essential for the production of 2-methylcitric acid in R. eutropha H16. Conclusion The

  5. Understanding the Pulsar High Energy Emission: Macroscopic and Kinetic Models

    Science.gov (United States)

    Kalapotharakos, Constantinos; Brambilla, Gabriele; Timokhin, Andrey; Kust Harding, Alice; Kazanas, Demos

    2017-08-01

    Pulsars are extraordinary objects powered by the rotation of magnetic fields of order 10^8, 10^12G anchored onto neutron stars and rotating with periods 10^(-3)-10s. These fields mediate the conversion of their rotational energy into MHD winds and at the same time accelerate particles to energies sufficiently high to produce GeV photons. Fermi, since its launch in 2008, has established several trends among the observed gamma-ray pulsar properties playing a catalytic role in the current modeling of the high energy emission in pulsar magnetospheres. We judiciously use the guidance provided by the Fermi data to yield meaningful constraints on the macroscopic parameters of our global dissipative pulsar magnetosphere models. Our FIDO (Force-Free Inside, Dissipative Outside) models indicate that the dissipative regions lie outside the light cylinder near the equatorial current sheet. Our models reproduce the light-curve phenomenology while a detailed comparison of the model spectral properties with those observed by Fermi reveals the dependence of the macroscopic conductivity parameter on the spin-down rate providing a unique insight into the understanding of the physical mechanisms behind the high-energy emission in pulsar magnetospheres. Finally, we further exploit these important results by building self-consistent 3D global kinetic particle-in-cell (PIC) models which, eventually, provide the dependence of the macroscopic parameter behavior (e.g. conductivity) on the microphysical properties (e.g. particle multiplicities, particle injection rates). Our PIC models provide field structures and particle distributions that are not only consistent with each other but also able to reproduce a broad range of the observed gamma-ray phenomenology (light curves and spectral properties) of both young and millisecond pulsars.

  6. Genome-scale comparison and constraint-based metabolic reconstruction of the facultative anaerobic Fe(III-reducer Rhodoferax ferrireducens

    Directory of Open Access Journals (Sweden)

    Daugherty Sean

    2009-09-01

    Full Text Available Abstract Background Rhodoferax ferrireducens is a metabolically versatile, Fe(III-reducing, subsurface microorganism that is likely to play an important role in the carbon and metal cycles in the subsurface. It also has the unique ability to convert sugars to electricity, oxidizing the sugars to carbon dioxide with quantitative electron transfer to graphite electrodes in microbial fuel cells. In order to expand our limited knowledge about R. ferrireducens, the complete genome sequence of this organism was further annotated and then the physiology of R. ferrireducens was investigated with a constraint-based, genome-scale in silico metabolic model and laboratory studies. Results The iterative modeling and experimental approach unveiled exciting, previously unknown physiological features, including an expanded range of substrates that support growth, such as cellobiose and citrate, and provided additional insights into important features such as the stoichiometry of the electron transport chain and the ability to grow via fumarate dismutation. Further analysis explained why R. ferrireducens is unable to grow via photosynthesis or fermentation of sugars like other members of this genus and uncovered novel genes for benzoate metabolism. The genome also revealed that R. ferrireducens is well-adapted for growth in the subsurface because it appears to be capable of dealing with a number of environmental insults, including heavy metals, aromatic compounds, nutrient limitation and oxidative stress. Conclusion This study demonstrates that combining genome-scale modeling with the annotation of a new genome sequence can guide experimental studies and accelerate the understanding of the physiology of under-studied yet environmentally relevant microorganisms.

  7. Hopping electron model with geometrical frustration: kinetic Monte Carlo simulations

    Science.gov (United States)

    Terao, Takamichi

    2016-09-01

    The hopping electron model on the Kagome lattice was investigated by kinetic Monte Carlo simulations, and the non-equilibrium nature of the system was studied. We have numerically confirmed that aging phenomena are present in the autocorrelation function C ({t,tW )} of the electron system on the Kagome lattice, which is a geometrically frustrated lattice without any disorder. The waiting-time distributions p(τ ) of hopping electrons of the system on Kagome lattice has been also studied. It is confirmed that the profile of p (τ ) obtained at lower temperatures obeys the power-law behavior, which is a characteristic feature of continuous time random walk of electrons. These features were also compared with the characteristics of the Coulomb glass model, used as a model of disordered thin films and doped semiconductors. This work represents an advance in the understanding of the dynamics of geometrically frustrated systems and will serve as a basis for further studies of these physical systems.

  8. Kinetic modelling of runaway electrons in dynamic scenarios

    Science.gov (United States)

    Stahl, A.; Embréus, O.; Papp, G.; Landreman, M.; Fülöp, T.

    2016-11-01

    Improved understanding of runaway-electron formation and decay processes are of prime interest for the safe operation of large tokamaks, and the dynamics of the runaway electrons during dynamical scenarios such as disruptions are of particular concern. In this paper, we present kinetic modelling of scenarios with time-dependent plasma parameters; in particular, we investigate hot-tail runaway generation during a rapid drop in plasma temperature. With the goal of studying runaway-electron generation with a self-consistent electric-field evolution, we also discuss the implementation of a collision operator that conserves momentum and energy and demonstrate its properties. An operator for avalanche runaway-electron generation, which takes the energy dependence of the scattering cross section and the runaway distribution into account, is investigated. We show that the simplified avalanche model of Rosenbluth and Putvinskii (1997 Nucl. Fusion 37 1355) can give inaccurate results for the avalanche growth rate (either lower or higher) for many parameters, especially when the average runaway energy is modest, such as during the initial phase of the avalanche multiplication. The developments presented pave the way for improved modelling of runaway-electron dynamics during disruptions or other dynamic events.

  9. Kinetic Model of Hypophosphite Oxidation on a Nickel Electrode in D2O Solution

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Kinetic model of hypophosphite oxidation on a nickel electrode was studied in D2Osolution in order to reach a better understanding of the oxidation mechanism. In the model the electrooxidation of hypophosphite undergo a H abstraction of hypophosphite from the P-H bond to form the phosphorus-centered radical PHO2-, which subsequently is electrochemically reacted with water to form the final product, phosphite. The kinetic equations were derived, and the kinetic parameters were obtained from a comparison of experimental results and the kinetic equations. The process of hypophosphite electrooxidation could be well simulated by this model

  10. Applicaiton of a Kinetic Multireaction Model for Studying Metolachlor Adsorption in Soil

    Institute of Scientific and Technical Information of China (English)

    ZHUHONGXIA; MALIWANG; 等

    1997-01-01

    Metolachlor retention on a Sharkey clay soil was quantified using a kinetic batch method for different initial solution concentrations.Time-dependent adsorption was carried out by monitoring solution concentration at different reaction times.Adsorption was kinetic multireaction model which includes reverible and irreversible retention processes of the equilibrium and kinetic types,The predictive capability of the model for the dexcription of experimental results for metolachlor retention was examined and proved to be adequate。

  11. Genome-Scale Architecture of Small Molecule Regulatory Networks and the Fundamental Trade-Off between Regulation and Enzymatic Activity

    Directory of Open Access Journals (Sweden)

    Ed Reznik

    2017-09-01

    Full Text Available Metabolic flux is in part regulated by endogenous small molecules that modulate the catalytic activity of an enzyme, e.g., allosteric inhibition. In contrast to transcriptional regulation of enzymes, technical limitations have hindered the production of a genome-scale atlas of small molecule-enzyme regulatory interactions. Here, we develop a framework leveraging the vast, but fragmented, biochemical literature to reconstruct and analyze the small molecule regulatory network (SMRN of the model organism Escherichia coli, including the primary metabolite regulators and enzyme targets. Using metabolic control analysis, we prove a fundamental trade-off between regulation and enzymatic activity, and we combine it with metabolomic measurements and the SMRN to make inferences on the sensitivity of enzymes to their regulators. Generalizing the analysis to other organisms, we identify highly conserved regulatory interactions across evolutionarily divergent species, further emphasizing a critical role for small molecule interactions in the maintenance of metabolic homeostasis.

  12. Modeling turbulence structure. Chemical kinetics interaction in turbulent reactive flows

    Energy Technology Data Exchange (ETDEWEB)

    Magnussen, B.F. [The Norwegian Univ. of Science and Technology, Trondheim (Norway)

    1997-12-31

    The challenge of the mathematical modelling is to transfer basic physical knowledge into a mathematical formulation such that this knowledge can be utilized in computational simulation of practical problems. The combustion phenomena can be subdivided into a large set of interconnected phenomena like flow, turbulence, thermodynamics, chemical kinetics, radiation, extinction, ignition etc. Combustion in one application differs from combustion in another area by the relative importance of the various phenomena. The difference in fuel, geometry and operational conditions often causes the differences. The computer offers the opportunity to treat the individual phenomena and their interactions by models with wide operational domains. The relative magnitude of the various phenomena therefore becomes the consequence of operational conditions and geometry and need not to be specified on the basis of experience for the given problem. In mathematical modelling of turbulent combustion, one of the big challenges is how to treat the interaction between the chemical reactions and the fluid flow i.e. the turbulence. Different scientists adhere to different concepts like the laminar flamelet approach, the pdf approach of the Eddy Dissipation Concept. Each of these approaches offers different opportunities and problems. All these models are based on a sound physical basis, however none of these have general validity in taking into consideration all detail of the physical chemical interaction. The merits of the models can only be judged by their ability to reproduce physical reality and consequences of operational and geometric conditions in a combustion system. The presentation demonstrates and discusses the development of a coherent combustion technology for energy conversion and safety based on the Eddy Dissipation Concept by Magnussen. (author) 30 refs.

  13. Heterogeneous kinetic modeling of the catalytic conversion of cycloparaffins

    Science.gov (United States)

    Al-Sabawi, Mustafa N.

    catalytic conversions respectively, are reported. Using these data, heterogeneous kinetic models accounting for intracrystallite molecular transport, adsorption and thermal and catalytic cracking of both cycloparaffin reactants are established. Results show that undesirable hydrogen transfer reactions are more pronounced and selectively favoured against other reactions at lower reaction temperatures, while the desirable ring-opening and cracking reactions predominate at the higher reaction temperatures. Moreover, results of the present work show that while crystallite size may have an effect on the overall conversion in some situations, there is a definite effect on the selectivity of products obtained during the cracking of MCH and decalin and the cracking of MCH in a mixture with co-reactants such as 1,3,5-triisopropylbenzene. Keywords. cycloparaffins, naphthenes, fluid catalytic cracking, kinetic modeling, Y-zeolites, diffusion, adsorption, ring-opening, hydrogen transfer, catalyst selectivity.

  14. Micellization kinetics in block copolymer solutions : Scaling model

    NARCIS (Netherlands)

    Dormidontova, EE

    1999-01-01

    The kinetics of micelle evolution of diblock copolymers from unimers toward the equilibrium state is studied analytically on the basis of consideration of the kinetic equations. The association/dissociation rate constants for unimer insertion/expulsion and micelle fusion/fission are calculated by

  15. Micellization kinetics in block copolymer solutions : Scaling model

    NARCIS (Netherlands)

    Dormidontova, EE

    1999-01-01

    The kinetics of micelle evolution of diblock copolymers from unimers toward the equilibrium state is studied analytically on the basis of consideration of the kinetic equations. The association/dissociation rate constants for unimer insertion/expulsion and micelle fusion/fission are calculated by ap

  16. Kinetic modeling of water sorption by roasted and ground coffee

    Directory of Open Access Journals (Sweden)

    Fernanda Machado Baptestini

    2017-05-01

    Full Text Available The objective of this study was to model the kinetics of water sorption in roasted and ground coffee. Crude Arabica coffee beans with an initial moisture content of 0.1234 kgwkgdm-1 were used. These beans were roasted to a medium roast level (SCCA # 55 and ground at three particle sizes: coarse (1.19 mm, medium (0.84 mm and fine (0.59 mm. To obtain the water sorption isotherms and the isosteric heat, different conditions of temperature and relative humidity were analyzed using the dynamic method at 25ºC (0.50, 0.60, 0.70, and 0.80 of RH and 30°C (0.30, 0.40, 0.50, 0.60, 0.70, and 0.80 of RH and using the static method at 25ºC (0.332 and 0.438 of RH. The GAB model best represented the hygroscopic equilibrium of roasted coffee at every particle size. Isosteric heat of sorption for the fine particle size increased with increments of equilibrium moisture content, indicating a strong bond energy between water molecules and the product components. The Gibbs free energy decreased with the increase in equilibrium moisture content and with temperature.

  17. Fluctuation theorems for discrete kinetic models of molecular motors

    Science.gov (United States)

    Faggionato, Alessandra; Silvestri, Vittoria

    2017-04-01

    Motivated by discrete kinetic models for non-cooperative molecular motors on periodic tracks, we consider random walks (also not Markov) on quasi one dimensional (1d) lattices, obtained by gluing several copies of a fundamental graph in a linear fashion. We show that, for a suitable class of quasi-1d lattices, the large deviation rate function associated to the position of the walker satisfies a Gallavotti-Cohen symmetry for any choice of the dynamical parameters defining the stochastic walk. This class includes the linear model considered in Lacoste et al (2008 Phys. Rev. E 78 011915). We also derive fluctuation theorems for the time-integrated cycle currents and discuss how the matrix approach of Lacoste et al (2008 Phys. Rev. E 78 011915) can be extended to derive the above Gallavotti-Cohen symmetry for any Markov random walk on {Z} with periodic jump rates. Finally, we review in the present context some large deviation results of Faggionato and Silvestri (2017 Ann. Inst. Henri Poincaré 53 46-78) and give some specific examples with explicit computations.

  18. Python framework for kinetic modeling of electronically excited reaction pathways

    Science.gov (United States)

    Verboncoeur, John; Parsey, Guy; Guclu, Yaman; Christlieb, Andrew

    2012-10-01

    The use of plasma energy to enhance and control the chemical reactions during combustion, a technology referred to as ``plasma assisted combustion'' (PAC), can result in a variety of beneficial effects: e.g. stable lean operation, pollution reduction, and wider range of p-T operating conditions. While experimental evidence abounds, theoretical understanding of PAC is at best incomplete, and numerical tools still lack in reliable predictive capabilities. In the context of a joint experimental-numerical effort at Michigan State University, we present here an open-source modular Python framework dedicated to the dynamic optimization of non-equilibrium PAC systems. Multiple sources of experimental reaction data, e.g. reaction rates, cross-sections and oscillator strengths, are used in order to quantify the effect of data uncertainty and limiting assumptions. A collisional-radiative model (CRM) is implemented to organize reactions by importance and as a potential means of measuring a non-Maxwellian electron energy distribution function (EEDF), when coupled to optical emission spectroscopy data. Finally, we explore scaling laws in PAC parameter space using a kinetic global model (KGM) accelerated with CRM optimized reaction sequences and sparse stiff integrators.

  19. Modeling battery cells under discharge using kinetic and stochastic battery models

    OpenAIRE

    Kaj, Ingemar; Konane, Victorien

    2016-01-01

    In this paper we review several approaches to mathematical modeling of simple battery cells and develop these ideas further with emphasis on charge recovery and the response behavior of batteries to given external load. We focus on models which use few parameters and basic battery data, rather than detailed reaction and material characteristics of a specific battery cell chemistry, starting with the coupled ODE linear dynamics of the kinetic battery model. We show that a related system of PDE...

  20. Kinetic theories for spin models for cooperative relaxation dynamics

    Science.gov (United States)

    Pitts, Steven Jerome

    The facilitated kinetic Ising models with asymmetric spin flip constraints introduced by Jackle and co-workers [J. Jackle, S. Eisinger, Z. Phys. B 84, 115 (1991); J. Reiter, F. Mauch, J. Jackle, Physica A 184, 458 (1992)] exhibit complex relaxation behavior in their associated spin density time correlation functions. This includes the growth of relaxation times over many orders of magnitude when the thermodynamic control parameter is varied, and, in some cases, ergodic-nonergodic transitions. Relaxation equations for the time dependence of the spin density autocorrelation function for a set of these models are developed that relate this autocorrelation function to the irreducible memory function of Kawasaki [K. Kawasaki, Physica A 215, 61 (1995)] using a novel diagrammatic series approach. It is shown that the irreducible memory function in a theory of the relaxation of an autocorrelation function in a Markov model with detailed balance plays the same role as the part of the memory function approximated by a polynomial function of the autocorrelation function with positive coefficients in schematic simple mode coupling theories for supercooled liquids [W. Gotze, in Liquids, Freezing and the Glass Transition, D. Levesque, J. P. Hansen, J. Zinn-Justin eds., 287 (North Holland, New York, 1991)]. Sets of diagrams in the series for the irreducible memory function are summed which lead to approximations of this type. The behavior of these approximations is compared with known results from previous analytical calculations and from numerical simulations. For the simplest one dimensional model, relaxation equations that are closely related to schematic extended mode coupling theories [W. Gotze, ibid] are also derived using the diagrammatic series. Comparison of the results of these approximate theories with simulation data shows that these theories improve significantly on the results of the theories of the simple schematic mode coupling theory type. The potential

  1. Disposition of smoked cannabis with high [Delta]9-tetrahydrocannabinol content: A kinetic model.

    NARCIS (Netherlands)

    Hunault, C.C.; van Eijkeren, J.C.; Mensinga, T.T.; de Vries, I.; Leenders, M.E.C.; Meulenbelt, J.

    2010-01-01

    Introduction No model exists to describe the disposition and kinetics of inhaled cannabis containing a high THC dose. We aimed to develop a kinetic model providing estimates of the THC serum concentrations after smoking cannabis cigarettes containing high THC doses (up to 69 mg THC).Methods

  2. Disposition of smoked cannabis with high [Delta]9-tetrahydrocannabinol content: A kinetic model.

    NARCIS (Netherlands)

    Hunault, C.C.; van Eijkeren, J.C.; Mensinga, T.T.; de Vries, I.; Leenders, M.E.C.; Meulenbelt, J.

    2010-01-01

    Introduction No model exists to describe the disposition and kinetics of inhaled cannabis containing a high THC dose. We aimed to develop a kinetic model providing estimates of the THC serum concentrations after smoking cannabis cigarettes containing high THC doses (up to 69 mg THC).Methods Twenty-f

  3. A kinetic model for the glucose/glycine Maillard reaction pathways

    NARCIS (Netherlands)

    Martins, S.I.F.S.; Boekel, van M.A.J.S.

    2005-01-01

    A comprehensive kinetic model for the glucose/glycine Maillard reaction is proposed based on an approach called multiresponse kinetic modelling. Special attention was paid to reactants, intermediates and end products: -fructose, N-(1-deoxy--fructos-1-yl)-glycine (DFG), 1-deoxy-2,3-hexodiulose and

  4. Predicting individual responses to pravastatin using a physiologically based kinetic model for plasma cholesterol concentrations

    NARCIS (Netherlands)

    Pas, N.C.A. van de; Rullmann, J.A.C.; Woutersen, R.A.; Ommen, B. van; Rietjens, I.M.C.M.; Graaf, A.A. de

    2014-01-01

    We used a previously developed physiologically based kinetic (PBK) model to analyze the effect of individual variations in metabolism and transport of cholesterol on pravastatin response. The PBK model is based on kinetic expressions for 21 reactions that interconnect eight different body

  5. The genome-scale metabolic extreme pathway structure in Haemophilus influenzae shows significant network redundancy.

    Science.gov (United States)

    Papin, Jason A; Price, Nathan D; Edwards, Jeremy S; Palsson B, Bernhard Ø

    2002-03-07

    Genome-scale metabolic networks can be characterized by a set of systemically independent and unique extreme pathways. These extreme pathways span a convex, high-dimensional space that circumscribes all potential steady-state flux distributions achievable by the defined metabolic network. Genome-scale extreme pathways associated with the production of non-essential amino acids in Haemophilus influenzae were computed. They offer valuable insight into the functioning of its metabolic network. Three key results were obtained. First, there were multiple internal flux maps corresponding to externally indistinguishable states. It was shown that there was an average of 37 internal states per unique exchange flux vector in H. influenzae when the network was used to produce a single amino acid while allowing carbon dioxide and acetate as carbon sinks. With the inclusion of succinate as an additional output, this ratio increased to 52, a 40% increase. Second, an analysis of the carbon fates illustrated that the extreme pathways were non-uniformly distributed across the carbon fate spectrum. In the detailed case study, 45% of the distinct carbon fate values associated with lysine production represented 85% of the extreme pathways. Third, this distribution fell between distinct systemic constraints. For lysine production, the carbon fate values that represented 85% of the pathways described above corresponded to only 2 distinct ratios of 1:1 and 4:1 between carbon dioxide and acetate. The present study analysed single outputs from one organism, and provides a start to genome-scale extreme pathways studies. These emergent system-level characterizations show the significance of metabolic extreme pathway analysis at the genome-scale.

  6. A versatile genome-scale PCR-based pipeline for high-definition DNA FISH.

    Science.gov (United States)

    Bienko, Magda; Crosetto, Nicola; Teytelman, Leonid; Klemm, Sandy; Itzkovitz, Shalev; van Oudenaarden, Alexander

    2013-02-01

    We developed a cost-effective genome-scale PCR-based method for high-definition DNA FISH (HD-FISH). We visualized gene loci with diffraction-limited resolution, chromosomes as spot clusters and single genes together with transcripts by combining HD-FISH with single-molecule RNA FISH. We provide a database of over 4.3 million primer pairs targeting the human and mouse genomes that is readily usable for rapid and flexible generation of probes.

  7. A kinetic model for runaway electrons in the ionosphere

    Directory of Open Access Journals (Sweden)

    G. Garcia

    2006-09-01

    Full Text Available Electrodynamic models and measurements with satellites and incoherent scatter radars predict large field aligned current densities on one side of the auroral arcs. Different authors and different kinds of studies (experimental or modeling agree that the current density can reach up to hundreds of µA/m2. This large current density could be the cause of many phenomena such as tall red rays or triggering of unstable ion acoustic waves. In the present paper, we consider the issue of electrons moving through an ionospheric gas of positive ions and neutrals under the influence of a static electric field. We develop a kinetic model of collisions including electrons/electrons, electrons/ions and electrons/neutrals collisions. We use a Fokker-Planck approach to describe binary collisions between charged particles with a long-range interaction. We present the essential elements of this collision operator: the Langevin equation for electrons/ions and electrons/electrons collisions and the Monte-Carlo and null collision methods for electrons/neutrals collisions. A computational example is given illustrating the approach to equilibrium and the impact of the different terms (electrons/electrons and electrons/ions collisions on the one hand and electrons/neutrals collisions on the other hand. Then, a parallel electric field is applied in a new sample run. In this run, the electrons move in the z direction parallel to the electric field. The first results show that all the electron distribution functions are non-Maxwellian. Furthermore, runaway electrons can carry a significant part of the total current density, up to 20% of the total current density.

  8. A Mathematical Model for Suppression Subtractive Hybridization

    OpenAIRE

    2002-01-01

    Suppression subtractive hybridization (SSH) is frequently used to unearth differentially expressed genes on a whole-genome scale. Its versatility is based on combining cDNA library subtraction and normalization, which allows the isolation of sequences of varying degrees of abundance and differential expression. SSH is a complex process with many adjustable parameters that affect the outcome of gene isolation.We present a mathematical model of SSH based on DNA hybridization kinetics for assess...

  9. KINETIC MODELS STUDY OF HYDRODESULPHURIZATION VACUUM DISTILLATE REACTION

    Directory of Open Access Journals (Sweden)

    AbdulMunem A. Karim

    2013-05-01

    Full Text Available    This study deals with  kinetics of hydrodesulphurization (HDS reaction of vacuum gas oil (611-833 K which was distillated from Kirkuk crude oil and which was obtained by blending the fractions, light vacuum gas oil (611 - 650 K, medium vacuum gas oil (650-690 K, heavy vacuum gas oil (690-727 K and very heavy vacuum gas oil (727-833 K.   The vacuum gas oil was hydrotreated on a commercial cobalt-molybdenum alumina catalyst presulfied at specified conditions in a laboratory trickle bed reactor. The reaction temperature range (583-643 K,liquid hourly space velocity range (1.5-3.75 h-1 and hydrogen pressure was kept constant at 3.5 MPa with hydrogen to oil ratio about 250 lt/lt.           The conversion results for desulphurization reaction appeared to obey the second order reaction. According to this model, the rate constants for desulphurization reaction were determined. Finally, the apparent activation energy (Ea, enthalpy of activation ( H* and entropy ( S* were calculated based on the values of rate constant (k2 and were equal 80.3792 KJ/mole, 75.2974 KJ/mole and 197.493 J/mole, respectively.

  10. Freed by interaction kinetic states in the Harper model

    Science.gov (United States)

    Frahm, Klaus M.; Shepelyansky, Dima L.

    2015-12-01

    We study the problem of two interacting particles in a one-dimensional quasiperiodic lattice of the Harper model. We show that a short or long range interaction between particles leads to emergence of delocalized pairs in the non-interacting localized phase. The properties of these freed by interaction kinetic states (FIKS) are analyzed numerically including the advanced Arnoldi method. We find that the number of sites populated by FIKS pairs grows algebraically with the system size with the maximal exponent b = 1, up to a largest lattice size N = 10 946 reached in our numerical simulations, thus corresponding to a complete delocalization of pairs. For delocalized FIKS pairs the spectral properties of such quasiperiodic operators represent a deep mathematical problem. We argue that FIKS pairs can be detected in the framework of recent cold atom experiments [M. Schreiber et al., Science 349, 842 (2015)] by a simple setup modification. We also discuss possible implications of FIKS pairs for electron transport in the regime of charge-density wave and high T c superconductivity.

  11. Kinetic modeling for chemiluminescent radicals in acetylene combustion

    Directory of Open Access Journals (Sweden)

    Marques Carla S. T.

    2006-01-01

    Full Text Available Kinetic modeling to reproduce the experimental chemiluminescence of OH*, CHO*, CH* and C2* excited radicals formed in C2H2/O2 combustion in a closed chamber was evaluated. A reaction mechanism with 37 species and 106 elementary reactions for C2H2/O2 combustion at phi=1.00 and phi=1.62 was validated through chemiluminescence measurements, where formation and decay reactions of excited radicals are included. KINAL package was used for simulations. Ordinary differential equations were solved by the DIFF program and production rate analysis were acquired by the ROPA program. There was good agreement between experimental and simulated chemiluminescence profiles of all radicals for both combustions. The results showed CH has a meaningful role in the production of excited radicals. Reactions: H + O2 = OH* + O; CH + O = CHO*; C2H + O2 = CH* + CO2 and CH2 + C = C2* + H2 were the main reactions paths used to reproduce the experimental profiles.

  12. Oil cracking to gases: Kinetic modeling and geological significance

    Institute of Scientific and Technical Information of China (English)

    TIAN Hui; WANG Zhaoming; XIAO Zhongyao; LI Xianqing; XIAO Xianming

    2006-01-01

    ATriassic oil sample from LN14 of Tarim Basin was pyrolyzed using the sealed gold tubes at 200-620℃ under a constant pressure of 50 MPa.The gaseous and residual soluble hydrocarbons were analyzed. The results show that the cracking of oil to gas can be divided into two distinct stages: the primary generation of total C1-5 gases from liquid oil characterized by the dominance of C2-5 hydrocarbons and the secondary or further cracking of C2-5gases to methane and carbon-rich matters leading to the progressive dryness of gases. Based on the experimental data, the kinetic parameters were determined for the primary generation and secondary cracking of oil cracking gases and extrapolated to geological conditions to predict the thermal stability and cracking extent of crude oil. Finally, an evolution model for the thermal destruction of crude oil was proposed and its implications to the migration and accumulation of oil cracking gases were discussed.

  13. Kinetic model of the bichromatic dark trap for atoms

    Science.gov (United States)

    Krasnov, I. V.

    2017-08-01

    A kinetic model of atom confinement in a bichromatic dark trap (BDT) is developed with the goal of describing its dissipative properties. The operating principle of the deep BDT is based on using the combination of multiple bichromatic cosine-Gaussian optical beams (CGBs) for creating high-potential barriers, which is described in our previous work (Krasnov 2016 Laser Phys. 26 105501). In the indicated work, particle motion in the BDT is described in terms of classical trajectories. In the present study, particle motion is analyzed by means of the Wigner function (phase-space distribution function (DF)), which allows one to properly take into account the quantum fluctuations of optical forces. Besides, we consider an improved scheme of the BDT, where CGBs create, apart from plane potential barriers, a narrow cooling layer. We find an asymptotic solution of the Fokker-Planck equation for the DF and show that the DF of particles deeply trapped in a BDT with a cooling layer is the Tsallis distribution with the effective temperature, which can be considerably lower than in a BDT without a cooling layer. Moreover, it can be adjusted by slightly changing the CGBs’ radii. We also study the effect of particle escape from the trap due to the scattering of resonant photons and show that the particle lifetime in a BDT can exceed several tens of hours when it is limited by photon scattering.

  14. Weighted Statistical Binning: Enabling Statistically Consistent Genome-Scale Phylogenetic Analyses

    Science.gov (United States)

    Bayzid, Md Shamsuzzoha; Mirarab, Siavash; Boussau, Bastien; Warnow, Tandy

    2015-01-01

    Because biological processes can result in different loci having different evolutionary histories, species tree estimation requires multiple loci from across multiple genomes. While many processes can result in discord between gene trees and species trees, incomplete lineage sorting (ILS), modeled by the multi-species coalescent, is considered to be a dominant cause for gene tree heterogeneity. Coalescent-based methods have been developed to estimate species trees, many of which operate by combining estimated gene trees, and so are called "summary methods". Because summary methods are generally fast (and much faster than more complicated coalescent-based methods that co-estimate gene trees and species trees), they have become very popular techniques for estimating species trees from multiple loci. However, recent studies have established that summary methods can have reduced accuracy in the presence of gene tree estimation error, and also that many biological datasets have substantial gene tree estimation error, so that summary methods may not be highly accurate in biologically realistic conditions. Mirarab et al. (Science 2014) presented the "statistical binning" technique to improve gene tree estimation in multi-locus analyses, and showed that it improved the accuracy of MP-EST, one of the most popular coalescent-based summary methods. Statistical binning, which uses a simple heuristic to evaluate "combinability" and then uses the larger sets of genes to re-calculate gene trees, has good empirical performance, but using statistical binning within a phylogenomic pipeline does not have the desirable property of being statistically consistent. We show that weighting the re-calculated gene trees by the bin sizes makes statistical binning statistically consistent under the multispecies coalescent, and maintains the good empirical performance. Thus, "weighted statistical binning" enables highly accurate genome-scale species tree estimation, and is also statistically

  15. Weighted Statistical Binning: Enabling Statistically Consistent Genome-Scale Phylogenetic Analyses.

    Directory of Open Access Journals (Sweden)

    Md Shamsuzzoha Bayzid

    Full Text Available Because biological processes can result in different loci having different evolutionary histories, species tree estimation requires multiple loci from across multiple genomes. While many processes can result in discord between gene trees and species trees, incomplete lineage sorting (ILS, modeled by the multi-species coalescent, is considered to be a dominant cause for gene tree heterogeneity. Coalescent-based methods have been developed to estimate species trees, many of which operate by combining estimated gene trees, and so are called "summary methods". Because summary methods are generally fast (and much faster than more complicated coalescent-based methods that co-estimate gene trees and species trees, they have become very popular techniques for estimating species trees from multiple loci. However, recent studies have established that summary methods can have reduced accuracy in the presence of gene tree estimation error, and also that many biological datasets have substantial gene tree estimation error, so that summary methods may not be highly accurate in biologically realistic conditions. Mirarab et al. (Science 2014 presented the "statistical binning" technique to improve gene tree estimation in multi-locus analyses, and showed that it improved the accuracy of MP-EST, one of the most popular coalescent-based summary methods. Statistical binning, which uses a simple heuristic to evaluate "combinability" and then uses the larger sets of genes to re-calculate gene trees, has good empirical performance, but using statistical binning within a phylogenomic pipeline does not have the desirable property of being statistically consistent. We show that weighting the re-calculated gene trees by the bin sizes makes statistical binning statistically consistent under the multispecies coalescent, and maintains the good empirical performance. Thus, "weighted statistical binning" enables highly accurate genome-scale species tree estimation, and is also

  16. A physiologically based in silico kinetic model predicting plasma cholesterol concentrations in humans

    NARCIS (Netherlands)

    Pas, van de N.C.A.; Woutersen, R.A.; Ommen, van B.; Rietjens, I.M.C.M.; Graaf, de A.A.

    2012-01-01

    Increased plasma cholesterol concentration is associated with increased risk of cardiovascular disease. This study describes the development, validation, and analysis of a physiologically based kinetic (PBK) model for the prediction of plasma cholesterol concentrations in humans. This model was dire

  17. Review of reactive kinetic models describing reductive dechlorination of chlorinated ethenes in soil and groundwater

    DEFF Research Database (Denmark)

    Chambon, Julie Claire Claudia; Bjerg, Poul Løgstrup; Scheutz, Charlotte;

    2013-01-01

    Reductive dechlorination is a major degradation pathway of chlorinated ethenes in anaerobic subsurface environments, and reactive kinetic models describing the degradation process are needed in fate and transport models of these contaminants. However, reductive dechlorination is a complex biologi...

  18. A physiologically based in silico kinetic model predicting plasma cholesterol concentrations in humans

    NARCIS (Netherlands)

    Pas, N.C.A. van de; Woutersen, R.A.; Ommen, B. van; Rietjens, I.M.C.M.; Graaf, A.A. de

    2012-01-01

    Increased plasma cholesterol concentration is associated with increased risk of cardiovascular disease. This study describes the development, validation, and analysis of a physiologically based kinetic (PBK) model for the prediction of plasma cholesterol concentrations in humans. This model was

  19. Decarboxylation of Δ 9-tetrahydrocannabinol: Kinetics and molecular modeling

    Science.gov (United States)

    Perrotin-Brunel, Helene; Buijs, Wim; van Spronsen, Jaap; van Roosmalen, Maaike J. E.; Peters, Cor J.; Verpoorte, Rob; Witkamp, Geert-Jan

    2011-02-01

    Efficient tetrahydrocannabinol (Δ 9-THC) production from cannabis is important for its medical application and as basis for the development of production routes of other drugs from plants. This work presents one of the steps of Δ 9-THC production from cannabis plant material, the decarboxylation reaction, transforming the Δ 9-THC-acid naturally present in the plant into the psychoactive Δ 9-THC. Results of experiments showed pseudo-first order reaction kinetics, with an activation barrier of 85 kJ mol -1 and a pre-exponential factor of 3.7 × 10 8 s -1. Using molecular modeling, two options were identified for an acid catalyzed β-keto acid type mechanism for the decarboxylation of Δ 9-THC-acid. Each of these mechanisms might play a role, depending on the actual process conditions. Formic acid proved to be a good model for a catalyst of such a reaction. Also, the computational idea of catalysis by water to catalysis by an acid, put forward by Li and Brill, and Churchev and Belbruno was extended, and a new direct keto-enol route was found. A direct keto-enol mechanism catalyzed by formic acid seems to be the best explanation for the observed activation barrier and the pre-exponential factor of the decarboxylation of Δ 9-THC-acid. Evidence for this was found by performing an extraction experiment with Cannabis Flos. It revealed the presence of short chain carboxylic acids supporting this hypothesis. The presented approach is important for the development of a sustainable production of Δ 9-THC from the plant.

  20. Analysis of a kinetic multi-segment foot model. Part I: Model repeatability and kinematic validity.

    Science.gov (United States)

    Bruening, Dustin A; Cooney, Kevin M; Buczek, Frank L

    2012-04-01

    Kinematic multi-segment foot models are still evolving, but have seen increased use in clinical and research settings. The addition of kinetics may increase knowledge of foot and ankle function as well as influence multi-segment foot model evolution; however, previous kinetic models are too complex for clinical use. In this study we present a three-segment kinetic foot model and thorough evaluation of model performance during normal gait. In this first of two companion papers, model reference frames and joint centers are analyzed for repeatability, joint translations are measured, segment rigidity characterized, and sample joint angles presented. Within-tester and between-tester repeatability were first assessed using 10 healthy pediatric participants, while kinematic parameters were subsequently measured on 17 additional healthy pediatric participants. Repeatability errors were generally low for all sagittal plane measures as well as transverse plane Hindfoot and Forefoot segments (mediansegment rigidity analysis suggested rigid body behavior for the Shank and Hindfoot, with the Forefoot violating the rigid body assumptions in terminal stance/pre-swing. Joint excursions were consistent with previously published studies.

  1. Validation of the point kinetic neutronic model of the PBMR / Deon Marais

    OpenAIRE

    Marais, Deon

    2007-01-01

    This study introduces a new method for the validation of the point kinetic neutronic model of the PBMR. In this study the diffusion equation solution, as implemented in the TlNTE PBMR 268 MW reactor model, replaces the point kinetic model, as implemented in the Flownex V502 PBMR plant model. An indirect coupling method is devised and implemented in an external program called Flownex-Tinte-Interface (FTI) to facilitate the data exchange between these two codes. The validation...

  2. A detailed chemical kinetic model for pyrolysis of the lignin model compound chroman

    Directory of Open Access Journals (Sweden)

    James Bland

    2013-12-01

    Full Text Available The pyrolysis of woody biomass, including the lignin component, is emerging as a potential technology for the production of renewable fuels and commodity chemicals. Here we describe the construction and implementation of an elementary chemical kinetic model for pyrolysis of the lignin model compound chroman and its reaction intermediate ortho-quinone methide (o-QM. The model is developed using both experimental and theoretical data, and represents a hybrid approach to kinetic modeling that has the potential to provide molecular level insight into reaction pathways and intermediates while accurately describing reaction rates and product formation. The kinetic model developed here can replicate all known aspects of chroman pyrolysis, and provides new information on elementary reaction steps. Chroman pyrolysis is found to proceed via an initial retro-Diels–Alder reaction to form o-QM + ethene (C2H4, followed by dissociation of o-QM to the C6H6 isomers benzene and fulvene (+ CO. At temperatures of around 1000–1200 K and above fulvene rapidly isomerizes to benzene, where an activation energy of around 270 kJ mol-1 is required to reproduce experimental observations. A new G3SX level energy surface for the isomerization of fulvene to benzene supports this result. Our modeling also suggests that thermal decomposition of fulvene may be important at around 950 K and above. This study demonstrates that theoretical protocols can provide a significant contribution to the development of kinetic models for biomass pyrolysis by elucidating reaction mechanisms, intermediates, and products, and also by supplying realistic rate coefficients and thermochemical properties.

  3. Modeling of hydrogen production methods: Single particle model and kinetics assessment

    Energy Technology Data Exchange (ETDEWEB)

    Miller, R.S.; Bellan, J. [California Institute of Technology, Pasadena, CA (United States)

    1996-10-01

    The investigation carried out by the Jet Propulsion Laboratory (JPL) is devoted to the modeling of biomass pyrolysis reactors producing an oil vapor (tar) which is a precursor to hydrogen. This is an informal collaboration with NREL whereby JPL uses the experimentally-generated NREL data both as initial and boundary conditions for the calculations, and as a benchmark for model validation. The goal of this investigation is to find drivers of biomass fast-pyrolysis in the low temperature regime. The rationale is that experimental observations produce sparse discrete conditions for model validation, and that numerical simulations produced with a validated model are an economic way to find control parameters and an optimal operation regime, thereby circumventing costly changes in hardware and tests. During this first year of the investigation, a detailed mathematical model has been formulated for the temporal and spatial accurate modeling of solid-fluid reactions in biomass particles. These are porous particles for which volumetric reaction rate data is known a priori and both the porosity and the permeability of the particle are large enough to allow for continuous gas phase flow. The methodology has been applied to the pyrolysis of spherically symmetric biomass particles by considering previously published kinetics schemes for both cellulose and wood. The results show that models which neglect the thermal and species boundary layers exterior to the particle will generally over predict both the pyrolysis rates and experimentally obtainable tar yields. An evaluation of the simulation results through comparisons with experimental data indicates that while the cellulose kinetics is reasonably accurate, the wood pyrolysis kinetics is not accurate; particularly at high reactor temperatures. Current effort in collaboration with NREL is aimed at finding accurate wood kinetics.

  4. Mathematical modeling taking into account of intrinsic kinetic properties of cylinder-type vanadium catalyst

    Institute of Scientific and Technical Information of China (English)

    陈振兴; 李洪桂; 王零森

    2004-01-01

    The method to calculate internal surface effective factor of cylinder-type vanadium catalyst Ls-9 was given. Based on hypothesis of subjunctive one dimension diffusion and combined shape adjustment factor with threestep catalytic mechanism model, the macroscopic kinetic model equation about SO2 oxidation on Ls-9 was deduced.With fixed-bed integral reactor and under the conditions of temperature 350 - 410 ℃, space velocity 1 800 - 5 000h-1, SO2 inlet content 7 %- 12%, the macroscopic kinetic data were detected. Through model parameter estimation,the macroscopic kinetic model equation was obtained.

  5. A model for the occurrence and analysis of ionic thermocurrent spectrum involving different orders of kinetics

    Indian Academy of Sciences (India)

    Jai Prakash

    2013-01-01

    Ionic thermocurrent (ITC) spectrum is much similar to a thermoluminescence (TL) glow curve involving monomolecular kinetics. It has already been reported that different orders of kinetics are involved in TL processes, which depend specifically on the extent of recombination and simultaneous retrapping. It is found that the involvement of different orders of kinetics in ITC spectrum depends on the experimental conditions of polarization and rate of rapid cooling. Consequently, order of kinetics involved in the ITC spectrum does not represent any specific feature of the system under investigation. An equation is developed which explains the occurrence of ITC spectrum involving any order of kinetics. Dielectric relaxation parameters, order of kinetics and approximate number of dipoles per unit volume are evaluated conveniently and easily following the proposed model.

  6. Symmetrical kinematics does not imply symmetrical kinetics in people with transtibial amputation using cycling model.

    Science.gov (United States)

    Childers, W Lee; Kogler, Géza F

    2014-01-01

    People with amputation move asymmetrically with regard to kinematics (joint angles) and kinetics (joint forces and moments). Clinicians have traditionally sought to minimize kinematic asymmetries, assuming kinetic asymmetries would also be minimized. A cycling model evaluated locomotor asymmetries. Eight individuals with unilateral transtibial amputation pedaled with 172 mm-length crank arms on both sides (control condition) and with the crank arm length shortened to 162 mm on the amputated side (CRANK condition). Pedaling kinetics and limb kinematics were recorded. Joint kinetics, joint angles (mean and range of motion [ROM]), and pedaling asymmetries were calculated from force pedals and with a motion capture system. A one-way analysis of variance with tukey post hoc compared kinetics and kinematics across limbs. Statistical significance was set to p kinetic asymmetries as clinically assumed. We propose that future research should concentrate on defining acceptable asymmetry.

  7. Kinetic modelling of RDF pyrolysis: Model-fitting and model-free approaches.

    Science.gov (United States)

    Çepelioğullar, Özge; Haykırı-Açma, Hanzade; Yaman, Serdar

    2016-02-01

    In this study, refuse derived fuel (RDF) was selected as solid fuel and it was pyrolyzed in a thermal analyzer from room temperature to 900°C at heating rates of 5, 10, 20, and 50°C/min in N2 atmosphere. The obtained thermal data was used to calculate the kinetic parameters using Coats-Redfern, Friedman, Flylnn-Wall-Ozawa (FWO) and Kissinger-Akahira-Sunose (KAS) methods. As a result of Coats-Redfern model, decomposition process was assumed to be four independent reactions with different reaction orders. On the other hand, model free methods demonstrated that activation energy trend had similarities for the reaction progresses of 0.1, 0.2-0.7 and 0.8-0.9. The average activation energies were found between 73-161kJ/mol and it is possible to say that FWO and KAS models produced closer results to the average activation energies compared to Friedman model. Experimental studies showed that RDF may be a sustainable and promising feedstock for alternative processes in terms of waste management strategies.

  8. Acceleration of the KINETICS Integrated Dynamical/Chemical Computational Model Using MPI

    Science.gov (United States)

    Grossman, Max; Willacy, Karen; Allen, Mark

    2011-01-01

    Understanding the evolution of a planet's atmosphere not only provides a better theoretical understanding of planetary physics and the formation of planets, but also grants useful insight into Earth's own atmosphere. One of the tools used at JPL for the modeling of planetary atmospheres and protostellar disks is KINETICS. KINETICS can simulate years of complex dynamics and chemistry.

  9. Application of Uncertainty and Sensitivity Analysis to a Kinetic Model for Enzymatic Biodiesel Production

    DEFF Research Database (Denmark)

    Price, Jason Anthony; Nordblad, Mathias; Woodley, John

    2014-01-01

    This paper demonstrates the added benefits of using uncertainty and sensitivity analysis in the kinetics of enzymatic biodiesel production. For this study, a kinetic model by Fedosov and co-workers is used. For the uncertainty analysis the Monte Carlo procedure was used to statistically quantify...

  10. Modelling fungal solid-state fermentation: The role of inactivation kinetics

    NARCIS (Netherlands)

    Smits, J.P.; Sonsbeek, H.M. van; Knol, W.; Tramper, J.; Geelhoed, W.; Peeters, M.; Rinzema, A.

    1999-01-01

    The theoretical mathematical models described in this paper are used to evaluate the effects of fungal biomass inactivation kinetics on a non- isothermal tray solid-state fermentation (SSF). The inactivation kinetics, derived from previously reported experiments done under isothermal conditions and

  11. A calculation of internal kinetic energy and polarizability of compressed argon from the statistical atom model

    NARCIS (Netherlands)

    Seldam, C.A. ten; Groot, S.R. de

    From Jensen's and Gombás' modification of the statistical Thomas-Fermi atom model, a theory for compressed atoms is developed by changing the boundary conditions. Internal kinetic energy and polarizability of argon are calculated as functions of pressure. At 1000 atm. an internal kinetic energy of

  12. Acceleration of the KINETICS Integrated Dynamical/Chemical Computational Model Using MPI

    Science.gov (United States)

    Grossman, Max; Willacy, Karen; Allen, Mark

    2011-01-01

    Understanding the evolution of a planet's atmosphere not only provides a better theoretical understanding of planetary physics and the formation of planets, but also grants useful insight into Earth's own atmosphere. One of the tools used at JPL for the modeling of planetary atmospheres and protostellar disks is KINETICS. KINETICS can simulate years of complex dynamics and chemistry.

  13. Detailed Chemical Kinetic Modeling of Diesel Combustion with Oxygenated Fuels

    Energy Technology Data Exchange (ETDEWEB)

    Curran, H J; Fisher, E M; Glaude, P-A; Marinov, N M; Pitz, W J; Westbrook, C K; Flynn, P F; Durrett, R P; zur Loye, A O; Akinyemi, O C; Dryer, F L

    2000-01-11

    mixing model to study the premixed, rich ignition process. Using n-heptane as a representative diesel fuel, they showed that addition of an oxygenated additive, methanol, to the fuel reduced the concentrations of a number of hydrocarbon species in the products of the rich ignition. Specifically, methanol addition reduced the total concentrations of acetylene, ethylene and 1,3-butadiene, as well as propargyl and vinyl radicals, in the ignition products. These are the same species shown in a number of studies [4-6] to be responsible for formation of aromatic and polycyclic aromatic species in flames, species which lead eventually to production of soot. Flynn et al. did not, however, examine the kinetic processes responsible for the computed reduction in production of soot precursor species. At least two hypotheses have been advanced to explain the role that oxygenated species play in diesel ignition and the reduction in the concentrations of these species. The first is that the additive, methanol in the case of Flynn et al., does not contain any C-C bonds and cannot then produce significant levels of the species such as acetylene, ethylene or the unsaturated radicals which are known to lead to aromatic species. The second hypothesis is that the product distribution changes very naturally as oxygen is added and the overall equivalence ratio is reduced. In the present study, we repeat the ignition calculations of Flynn et al. and include a number of other oxygenated species to determine which of these theories is more applicable to this model.

  14. Comparative evaluation of kinetic, equilibrium and semi-equilibrium models for biomass gasification

    Energy Technology Data Exchange (ETDEWEB)

    Buragohain, Buljit [Center for Energy, Indian Institute of Technology Guwahati, Guwahati – 781 039, Assam (India); Chakma, Sankar; Kumar, Peeush [Department of Chemical Engineering, Indian Institute of Technology Guwahati, Guwahati – 781 039, Assam (India); Mahanta, Pinakeswar [Center for Energy, Indian Institute of Technology Guwahati, Guwahati – 781 039, Assam (India); Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati – 781 039, Assam (India); Moholkar, Vijayanand S. [Center for Energy, Indian Institute of Technology Guwahati, Guwahati – 781 039, Assam (India); Department of Chemical Engineering, Indian Institute of Technology Guwahati, Guwahati – 781 039, Assam (India)

    2013-07-01

    Modeling of biomass gasification has been an active area of research for past two decades. In the published literature, three approaches have been adopted for the modeling of this process, viz. thermodynamic equilibrium, semi-equilibrium and kinetic. In this paper, we have attempted to present a comparative assessment of these three types of models for predicting outcome of the gasification process in a circulating fluidized bed gasifier. Two model biomass, viz. rice husk and wood particles, have been chosen for analysis, with gasification medium being air. Although the trends in molar composition, net yield and LHV of the producer gas predicted by three models are in concurrence, significant quantitative difference is seen in the results. Due to rather slow kinetics of char gasification and tar oxidation, carbon conversion achieved in single pass of biomass through the gasifier, calculated using kinetic model, is quite low, which adversely affects the yield and LHV of the producer gas. Although equilibrium and semi-equilibrium models reveal relative insensitivity of producer gas characteristics towards temperature, the kinetic model shows significant effect of temperature on LHV of the gas at low air ratios. Kinetic models also reveal volume of the gasifier to be an insignificant parameter, as the net yield and LHV of the gas resulting from 6 m and 10 m riser is same. On a whole, the analysis presented in this paper indicates that thermodynamic models are useful tools for quantitative assessment of the gasification process, while kinetic models provide physically more realistic picture.

  15. Comparative evaluation of kinetic, equilibrium and semi-equilibrium models for biomass gasification

    Directory of Open Access Journals (Sweden)

    Buljit Buragohain, Sankar Chakma, Peeush Kumar, Pinakeswar Mahanta, Vijayanand S. Moholkar

    2013-01-01

    Full Text Available Modeling of biomass gasification has been an active area of research for past two decades. In the published literature, three approaches have been adopted for the modeling of this process, viz. thermodynamic equilibrium, semi-equilibrium and kinetic. In this paper, we have attempted to present a comparative assessment of these three types of models for predicting outcome of the gasification process in a circulating fluidized bed gasifier. Two model biomass, viz. rice husk and wood particles, have been chosen for analysis, with gasification medium being air. Although the trends in molar composition, net yield and LHV of the producer gas predicted by three models are in concurrence, significant quantitative difference is seen in the results. Due to rather slow kinetics of char gasification and tar oxidation, carbon conversion achieved in single pass of biomass through the gasifier, calculated using kinetic model, is quite low, which adversely affects the yield and LHV of the producer gas. Although equilibrium and semi-equilibrium models reveal relative insensitivity of producer gas characteristics towards temperature, the kinetic model shows significant effect of temperature on LHV of the gas at low air ratios. Kinetic models also reveal volume of the gasifier to be an insignificant parameter, as the net yield and LHV of the gas resulting from 6 m and 10 m riser is same. On a whole, the analysis presented in this paper indicates that thermodynamic models are useful tools for quantitative assessment of the gasification process, while kinetic models provide physically more realistic picture.

  16. Characterizing the optimal flux space of genome-scale metabolic reconstructions through modified latin-hypercube sampling

    NARCIS (Netherlands)

    Chaudhary, N.; Tøndel, K.; Bhatnagar, R.; Martins dos Santos, V.A.P.; Puchalka, J.

    2016-01-01

    Genome-Scale Metabolic Reconstructions (GSMRs), along with optimization-based methods, predominantly Flux Balance Analysis (FBA) and its derivatives, are widely applied for assessing and predicting the behavior of metabolic networks upon perturbation, thereby enabling identification of potential nov

  17. Effect of heating rate and kinetic model selection on activation energy of nonisothermal crystallization of amorphous felodipine.

    Science.gov (United States)

    Chattoraj, Sayantan; Bhugra, Chandan; Li, Zheng Jane; Sun, Changquan Calvin

    2014-12-01

    The nonisothermal crystallization kinetics of amorphous materials is routinely analyzed by statistically fitting the crystallization data to kinetic models. In this work, we systematically evaluate how the model-dependent crystallization kinetics is impacted by variations in the heating rate and the selection of the kinetic model, two key factors that can lead to significant differences in the crystallization activation energy (Ea ) of an amorphous material. Using amorphous felodipine, we show that the Ea decreases with increase in the heating rate, irrespective of the kinetic model evaluated in this work. The model that best describes the crystallization phenomenon cannot be identified readily through the statistical fitting approach because several kinetic models yield comparable R(2) . Here, we propose an alternate paired model-fitting model-free (PMFMF) approach for identifying the most suitable kinetic model, where Ea obtained from model-dependent kinetics is compared with those obtained from model-free kinetics. The most suitable kinetic model is identified as the one that yields Ea values comparable with the model-free kinetics. Through this PMFMF approach, nucleation and growth is identified as the main mechanism that controls the crystallization kinetics of felodipine. Using this PMFMF approach, we further demonstrate that crystallization mechanism from amorphous phase varies with heating rate. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

  18. Empirical and physics based mathematical models of uranium hydride decomposition kinetics with quantified uncertainties.

    Energy Technology Data Exchange (ETDEWEB)

    Salloum, Maher N.; Gharagozloo, Patricia E.

    2013-10-01

    Metal particle beds have recently become a major technique for hydrogen storage. In order to extract hydrogen from such beds, it is crucial to understand the decomposition kinetics of the metal hydride. We are interested in obtaining a a better understanding of the uranium hydride (UH3) decomposition kinetics. We first developed an empirical model by fitting data compiled from different experimental studies in the literature and quantified the uncertainty resulting from the scattered data. We found that the decomposition time range predicted by the obtained kinetics was in a good agreement with published experimental results. Secondly, we developed a physics based mathematical model to simulate the rate of hydrogen diffusion in a hydride particle during the decomposition. We used this model to simulate the decomposition of the particles for temperatures ranging from 300K to 1000K while propagating parametric uncertainty and evaluated the kinetics from the results. We compared the kinetics parameters derived from the empirical and physics based models and found that the uncertainty in the kinetics predicted by the physics based model covers the scattered experimental data. Finally, we used the physics-based kinetics parameters to simulate the effects of boundary resistances and powder morphological changes during decomposition in a continuum level model. We found that the species change within the bed occurring during the decomposition accelerates the hydrogen flow by increasing the bed permeability, while the pressure buildup and the thermal barrier forming at the wall significantly impede the hydrogen extraction.

  19. Kinetic modelling of nitrogen and organics removal in vertical and horizontal flow wetlands.

    Science.gov (United States)

    Saeed, Tanveer; Sun, Guangzhi

    2011-05-01

    This paper provides a comparative evaluation of the kinetic models that were developed to describe the biodegradation of nitrogen and organics removal in wetland systems. Reaction kinetics that were considered in the model development included first order kinetics, Monod and multiple Monod kinetics; these kinetics were combined with continuous-stirred tank reactor (CSTR) or plug flow pattern to produce equations to link inlet and outlet concentrations of each key pollutants across a single wetland. Using three statistical parameters, a critical evaluation of five potential models was made for vertical and horizontal flow wetlands. The results recommended the models that were developed based on Monod models, for predicting the removal of nitrogen and organics in a vertical and horizontal flow wetland system. No clear correlation was observed between influent BOD/COD values and kinetic coefficients of BOD(5) in VF and HF wetlands, illustrating that the removal of biodegradable organics was insensitive to the nature of organic matter. Higher effluent COD/TN values coincided with greater denitrification kinetic coefficients, signifying the dependency of denitrification on the availability of COD in VF wetland systems. In contrast, the trend was opposite in HF wetlands, indicating that availability of NO(3)-N was the main limiting step for nitrogen removal. Overall, the results suggested the possible application of the developed alternative predictive models, for understanding the complex biodegradation routes of nitrogen and organics removal in VF and HF wetland systems.

  20. Kinetic Potential Model of the Cloud-to-Drizzle Transition

    Science.gov (United States)

    McGraw, Robert; Liu, Yangang; Luke, Edward; Senum, Gunnar

    2013-03-01

    It has been nearly a decade since the kinetic potential theory of drizzle formation in warm clouds was introduced [McGraw and Liu, Phys. Rev. Letts. 90, 018501 (2003)], and much progress in understanding the cloud-drizzle transition, especially regarding the role of turbulence, has been achieved within its framework. This poster will begin with an introduction to the kinetic potential idea, working up to the method it provides for predicting drizzle threshold conditions and rates, and concludes with an analysis this year of DOE/ARM cloud parcel vertical velocity measurements - discussing their implications for assessing turbulence fluctuations in water vapor saturation ratio and cloud droplet size.