WorldWideScience

Sample records for genome-scale structural analysis

  1. 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

  2. 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

  3. 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.

  4. Symbolic flux analysis for genome-scale metabolic networks

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    Peterson Pearu

    2011-05-01

    Full Text Available Abstract Background With the advent of genomic technology, the size of metabolic networks that are subject to analysis is growing. A common task when analyzing metabolic networks is to find all possible steady state regimes. There are several technical issues that have to be addressed when analyzing large metabolic networks including accumulation of numerical errors and presentation of the solution to the researcher. One way to resolve those technical issues is to analyze the network using symbolic methods. The aim of this paper is to develop a routine that symbolically finds the steady state solutions of large metabolic networks. Results A symbolic Gauss-Jordan elimination routine was developed for analyzing large metabolic networks. This routine was tested by finding the steady state solutions for a number of curated stoichiometric matrices with the largest having about 4000 reactions. The routine was able to find the solution with a computational time similar to the time used by a numerical singular value decomposition routine. As an advantage of symbolic solution, a set of independent fluxes can be suggested by the researcher leading to the formation of a desired flux basis describing the steady state solution of the network. These independent fluxes can be constrained using experimental data. We demonstrate the application of constraints by calculating a flux distribution for the central metabolic and amino acid biosynthesis pathways of yeast. Conclusions We were able to find symbolic solutions for the steady state flux distribution of large metabolic networks. The ability to choose a flux basis was found to be useful in the constraint process and provides a strong argument for using symbolic Gauss-Jordan elimination in place of singular value decomposition.

  5. Symbolic flux analysis for genome-scale metabolic networks.

    Science.gov (United States)

    Schryer, David W; Vendelin, Marko; Peterson, Pearu

    2011-05-23

    With the advent of genomic technology, the size of metabolic networks that are subject to analysis is growing. A common task when analyzing metabolic networks is to find all possible steady state regimes. There are several technical issues that have to be addressed when analyzing large metabolic networks including accumulation of numerical errors and presentation of the solution to the researcher. One way to resolve those technical issues is to analyze the network using symbolic methods. The aim of this paper is to develop a routine that symbolically finds the steady state solutions of large metabolic networks. A symbolic Gauss-Jordan elimination routine was developed for analyzing large metabolic networks. This routine was tested by finding the steady state solutions for a number of curated stoichiometric matrices with the largest having about 4000 reactions. The routine was able to find the solution with a computational time similar to the time used by a numerical singular value decomposition routine. As an advantage of symbolic solution, a set of independent fluxes can be suggested by the researcher leading to the formation of a desired flux basis describing the steady state solution of the network. These independent fluxes can be constrained using experimental data. We demonstrate the application of constraints by calculating a flux distribution for the central metabolic and amino acid biosynthesis pathways of yeast. We were able to find symbolic solutions for the steady state flux distribution of large metabolic networks. The ability to choose a flux basis was found to be useful in the constraint process and provides a strong argument for using symbolic Gauss-Jordan elimination in place of singular value decomposition.

  6. 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

  7. Genome-scale metabolic network of Cordyceps militaris useful for comparative analysis of entomopathogenic fungi.

    Science.gov (United States)

    Vongsangnak, Wanwipa; Raethong, Nachon; Mujchariyakul, Warasinee; Nguyen, Nam Ninh; Leong, Hon Wai; Laoteng, Kobkul

    2017-08-30

    The first genome-scale metabolic network of Cordyceps militaris (iWV1170) was constructed representing its whole metabolisms, which consisted of 894 metabolites and 1,267 metabolic reactions across five compartments, including the plasma membrane, cytoplasm, mitochondria, peroxisome and extracellular space. The iWV1170 could be exploited to explain its phenotypes of growth ability, cordycepin and other metabolites production on various substrates. A high number of genes encoding extracellular enzymes for degradation of complex carbohydrates, lipids and proteins were existed in C. militaris genome. By comparative genome-scale analysis, the adenine metabolic pathway towards putative cordycepin biosynthesis was reconstructed, indicating their evolutionary relationships across eleven species of entomopathogenic fungi. The overall metabolic routes involved in the putative cordycepin biosynthesis were also identified in C. militaris, including central carbon metabolism, amino acid metabolism (glycine, l-glutamine and l-aspartate) and nucleotide metabolism (adenosine and adenine). Interestingly, a lack of the sequence coding for ribonucleotide reductase inhibitor was observed in C. militaris that might contribute to its over-production of cordycepin. Copyright © 2017. Published by Elsevier B.V.

  8. Moving image analysis to the cloud: A case study with a genome-scale tomographic study

    Science.gov (United States)

    Mader, Kevin; Stampanoni, Marco

    2016-01-01

    Over the last decade, the time required to measure a terabyte of microscopic imaging data has gone from years to minutes. This shift has moved many of the challenges away from experimental design and measurement to scalable storage, organization, and analysis. As many scientists and scientific institutions lack training and competencies in these areas, major bottlenecks have arisen and led to substantial delays and gaps between measurement, understanding, and dissemination. We present in this paper a framework for analyzing large 3D datasets using cloud-based computational and storage resources. We demonstrate its applicability by showing the setup and costs associated with the analysis of a genome-scale study of bone microstructure. We then evaluate the relative advantages and disadvantages associated with local versus cloud infrastructures.

  9. Genome-scale analysis of positional clustering of mouse testis-specific genes

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    Lee Bernett TK

    2005-01-01

    Full Text Available Abstract Background Genes are not randomly distributed on a chromosome as they were thought even after removal of tandem repeats. The positional clustering of co-expressed genes is known in prokaryotes and recently reported in several eukaryotic organisms such as Caenorhabditis elegans, Drosophila melanogaster, and Homo sapiens. In order to further investigate the mode of tissue-specific gene clustering in higher eukaryotes, we have performed a genome-scale analysis of positional clustering of the mouse testis-specific genes. Results Our computational analysis shows that a large proportion of testis-specific genes are clustered in groups of 2 to 5 genes in the mouse genome. The number of clusters is much higher than expected by chance even after removal of tandem repeats. Conclusion Our result suggests that testis-specific genes tend to cluster on the mouse chromosomes. This provides another piece of evidence for the hypothesis that clusters of tissue-specific genes do exist.

  10. Moving image analysis to the cloud: A case study with a genome-scale tomographic study

    Energy Technology Data Exchange (ETDEWEB)

    Mader, Kevin [4Quant Ltd., Switzerland & Institute for Biomedical Engineering at University and ETH Zurich (Switzerland); Stampanoni, Marco [Institute for Biomedical Engineering at University and ETH Zurich, Switzerland & Swiss Light Source at Paul Scherrer Institut, Villigen (Switzerland)

    2016-01-28

    Over the last decade, the time required to measure a terabyte of microscopic imaging data has gone from years to minutes. This shift has moved many of the challenges away from experimental design and measurement to scalable storage, organization, and analysis. As many scientists and scientific institutions lack training and competencies in these areas, major bottlenecks have arisen and led to substantial delays and gaps between measurement, understanding, and dissemination. We present in this paper a framework for analyzing large 3D datasets using cloud-based computational and storage resources. We demonstrate its applicability by showing the setup and costs associated with the analysis of a genome-scale study of bone microstructure. We then evaluate the relative advantages and disadvantages associated with local versus cloud infrastructures.

  11. Genome-scale metabolic network validation of Shewanella oneidensis using transposon insertion frequency analysis.

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    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.

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

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    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.

  13. 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.

  14. Genome-scale metabolic analysis of Clostridium thermocellum for bioethanol production

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    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

  15. 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.

  16. 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...

  17. Expression induction of P450 genes by imidacloprid in Nilaparvata lugens: A genome-scale analysis.

    Science.gov (United States)

    Zhang, Jianhua; Zhang, Yixi; Wang, Yunchao; Yang, Yuanxue; Cang, Xinzhu; Liu, Zewen

    2016-09-01

    The overexpression of P450 monooxygenase genes is a main mechanism for the resistance to imidacloprid, a representative neonicotinoid insecticide, in Nilaparvata lugens (brown planthopper, BPH). However, only two P450 genes (CYP6AY1 and CYP6ER1), among fifty-four P450 genes identified from BPH genome database, have been reported to play important roles in imidacloprid resistance until now. In this study, after the confirmation of important roles of P450s in imidacloprid resistance by the synergism analysis, the expression induction by imidacloprid was determined for all P450 genes. In the susceptible (Sus) strain, eight P450 genes in Clade4, eight in Clade3 and two in Clade2 were up-regulated by imidacloprid, among which three genes (CYP6CS1, CYP6CW1 and CYP6ER1, all in Clade3) were increased to above 4.0-fold and eight genes to above 2.0-fold. In contrast, no P450 genes were induced in Mito clade. Eight genes induced to above 2.0-fold were selected to determine their expression and induced levels in Huzhou population, in which piperonyl butoxide showed the biggest effects on imidacloprid toxicity among eight field populations. The expression levels of seven P450 genes were higher in Huzhou population than that in Sus strain, with the biggest differences for CYP6CS1 (9.8-fold), CYP6ER1 (7.7-fold) and CYP6AY1 (5.1-fold). The induction levels for all tested genes were bigger in Sus strain than that in Huzhou population except CYP425B1. Screening the induction of P450 genes by imidacloprid in the genome-scale will provide an overall view on the possible metabolic factors in the resistance to neonicotinoid insecticides. The further work, such as the functional study of recombinant proteins, will be performed to validate the roles of these P450s in imidacloprid resistance.

  18. Genome-scale reconstruction and analysis of the Pseudomonas putida KT2440 metabolic network facilitates applications in biotechnology.

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    Jacek Puchałka

    2008-10-01

    Full Text Available A cornerstone of biotechnology is the use of microorganisms for the efficient production of chemicals and the elimination of harmful waste. Pseudomonas putida is an archetype of such microbes due to its metabolic versatility, stress resistance, amenability to genetic modifications, and vast potential for environmental and industrial applications. To address both the elucidation of the metabolic wiring in P. putida and its uses in biocatalysis, in particular for the production of non-growth-related biochemicals, we developed and present here a genome-scale constraint-based model of the metabolism of P. putida KT2440. Network reconstruction and flux balance analysis (FBA enabled definition of the structure of the metabolic network, identification of knowledge gaps, and pin-pointing of essential metabolic functions, facilitating thereby the refinement of gene annotations. FBA and flux variability analysis were used to analyze the properties, potential, and limits of the model. These analyses allowed identification, under various conditions, of key features of metabolism such as growth yield, resource distribution, network robustness, and gene essentiality. The model was validated with data from continuous cell cultures, high-throughput phenotyping data, (13C-measurement of internal flux distributions, and specifically generated knock-out mutants. Auxotrophy was correctly predicted in 75% of the cases. These systematic analyses revealed that the metabolic network structure is the main factor determining the accuracy of predictions, whereas biomass composition has negligible influence. Finally, we drew on the model to devise metabolic engineering strategies to improve production of polyhydroxyalkanoates, a class of biotechnologically useful compounds whose synthesis is not coupled to cell survival. The solidly validated model yields valuable insights into genotype-phenotype relationships and provides a sound framework to explore this versatile

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

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    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.

  20. 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...

  1. 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.

  2. Selection of objective function in genome scale flux balance analysis for process feed development in antibiotic production.

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    Khannapho, Chiraphan; Zhao, Hongjuan; Bonde, Bhushan K; Kierzek, Andrzej M; Avignone-Rossa, Claudio A; Bushell, Michael E

    2008-09-01

    Using flux variability analysis of a genome scale metabolic network of Streptomyces coelicolor, a series of reactions were identified, from disparate pathways that could be combined into an actinorhodin-generating mini-network. Candidate process feed nutrients that might be expected to influence this network were used in process simulations and in silico predictions compared to experimental findings. Ranking potential process feeds by flux balance analysis optimisation, using either growth or antibiotic production as objective function, did not correlate with experimental actinorhodin yields in fed processes. However, the effect of the feeds on glucose assimilation rate (using glucose uptake as objective function) ranked them in the same order as in vivo antibiotic production efficiency, consistent with results of a robustness analysis of the effect of glucose assimilation on actinorhodin production.

  3. Genome-scale reconstruction and analysis of the metabolic network in the hyperthermophilic archaeon Sulfolobus solfataricus.

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    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.

  4. Genome-scale transcriptome analysis in response to nitric oxide in birch cells: implications of the triterpene biosynthetic pathway.

    Directory of Open Access Journals (Sweden)

    Fansuo Zeng

    Full Text Available Evidence supporting nitric oxide (NO as a mediator of plant biochemistry continues to grow, but its functions at the molecular level remains poorly understood and, in some cases, controversial. To study the role of NO at the transcriptional level in Betula platyphylla cells, we conducted a genome-scale transcriptome analysis of these cells. The transcriptome of untreated birch cells and those treated by sodium nitroprusside (SNP were analyzed using the Solexa sequencing. Data were collected by sequencing cDNA libraries of birch cells, which had a long period to adapt to the suspension culture conditions before SNP-treated cells and untreated cells were sampled. Among the 34,100 UniGenes detected, BLASTX search revealed that 20,631 genes showed significant (E-values≤10-5 sequence similarity with proteins from the NR-database. Numerous expressed sequence tags (i.e., 1374 were identified as differentially expressed between the 12 h SNP-treated cells and control cells samples: 403 up-regulated and 971 down-regulated. From this, we specifically examined a core set of NO-related transcripts. The altered expression levels of several transcripts, as determined by transcriptome analysis, was confirmed by qRT-PCR. The results of transcriptome analysis, gene expression quantification, the content of triterpenoid and activities of defensive enzymes elucidated NO has a significant effect on many processes including triterpenoid production, carbohydrate metabolism and cell wall biosynthesis.

  5. 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.

  6. 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.

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

    Directory of Open Access Journals (Sweden)

    Feist Adam M

    2011-10-01

    Full Text Available 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 utility in the study of systems medicine. However, no integrated analysis between human tissues has been done. Results To describe tissue-specific functions, Recon 1 was tailored to describe metabolism in three human cells: adipocytes, hepatocytes, and myocytes. These cell-specific networks were manually curated and validated based on known cellular metabolic functions. To study intercellular interactions, a novel multi-tissue type modeling approach was developed to integrate the metabolic functions for the three cell types, and subsequently used to simulate known integrated metabolic cycles. In addition, the multi-tissue model was used to study diabetes: a pathology with systemic properties. High-throughput data was integrated with the network to determine differential metabolic activity between obese and type II obese gastric bypass patients in a whole-body context. Conclusion The multi-tissue type modeling approach presented provides a platform to study integrated metabolic states. As more cell and tissue-specific models are released, it is critical to develop a framework in which to study their interdependencies.

  8. Genome-scale analysis of the high-efficient protein secretion system of Aspergillus oryzae

    DEFF Research Database (Denmark)

    Liu, Lifang; Feizi, Amir; Osterlund, Tobias

    2014-01-01

    Background: The koji mold, Aspergillus oryzae is widely used for the production of industrial enzymes due to its particularly high protein secretion capacity and ability to perform post-translational modifications. However, systemic analysis of its secretion system is lacking, generally due to th...

  9. 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

    metabolic models or for genome-scale data analysis, no implementations exist that explicitly handle data and models concurrently. The OME Framework structures data in a connected loop with models and the components those models are composed of. This results in the first full, practical implementation of a framework that can enable genome-scale design-build-test. Over the coming years many more software packages will be developed and tools will necessarily change. However, we hope that the underlying designs shared here can help to inform the design of future software.

  10. 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...

  11. 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.

  12. Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

    Science.gov (United States)

    Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

    2008-06-18

    Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson

  13. Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient

    Directory of Open Access Journals (Sweden)

    Loraine Ann

    2008-06-01

    Full Text Available Abstract Background Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. Results In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC, that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. Conclusion

  14. Genome-Scale Analysis of Cell-Specific Regulatory Codes Using Nuclear Enzymes.

    Science.gov (United States)

    Baek, Songjoon; Sung, Myong-Hee

    2016-01-01

    High-throughput sequencing technologies have made it possible for biologists to generate genome-wide profiles of chromatin features at the nucleotide resolution. Enzymes such as nucleases or transposes have been instrumental as a chromatin-probing agent due to their ability to target accessible chromatin for cleavage or insertion. On the scale of a few hundred base pairs, preferential action of the nuclear enzymes on accessible chromatin allows mapping of cell state-specific accessibility in vivo. Such accessible regions contain functionally important regulatory sites, including promoters and enhancers, which undergo active remodeling for cells adapting in a dynamic environment. DNase-seq and the more recent ATAC-seq are two assays that are gaining popularity. Deep sequencing of DNA libraries from these assays, termed genomic footprinting, has been proposed to enable the comprehensive construction of protein occupancy profiles over the genome at the nucleotide level. Recent studies have discovered limitations of genomic footprinting which reduce the scope of detectable proteins. In addition, the identification of putative factors that bind to the observed footprints remains challenging. Despite these caveats, the methodology still presents significant advantages over alternative techniques such as ChIP-seq or FAIRE-seq. Here we describe computational approaches and tools for analysis of chromatin accessibility and genomic footprinting. Proper experimental design and assay-specific data analysis ensure the detection sensitivity and maximize retrievable information. The enzyme-based chromatin profiling approaches represent a powerful and evolving methodology which facilitates our understanding of how the genome is regulated.

  15. Construction and Analysis of Two Genome-Scale Deletion Libraries for Bacillus subtilis.

    Science.gov (United States)

    Koo, Byoung-Mo; Kritikos, George; Farelli, Jeremiah D; Todor, Horia; Tong, Kenneth; Kimsey, Harvey; Wapinski, Ilan; Galardini, Marco; Cabal, Angelo; Peters, Jason M; Hachmann, Anna-Barbara; Rudner, David Z; Allen, Karen N; Typas, Athanasios; Gross, Carol A

    2017-03-22

    A systems-level understanding of Gram-positive bacteria is important from both an environmental and health perspective and is most easily obtained when high-quality, validated genomic resources are available. To this end, we constructed two ordered, barcoded, erythromycin-resistance- and kanamycin-resistance-marked single-gene deletion libraries of the Gram-positive model organism, Bacillus subtilis. The libraries comprise 3,968 and 3,970 genes, respectively, and overlap in all but four genes. Using these libraries, we update the set of essential genes known for this organism, provide a comprehensive compendium of B. subtilis auxotrophic genes, and identify genes required for utilizing specific carbon and nitrogen sources, as well as those required for growth at low temperature. We report the identification of enzymes catalyzing several missing steps in amino acid biosynthesis. Finally, we describe a suite of high-throughput phenotyping methodologies and apply them to provide a genome-wide analysis of competence and sporulation. Altogether, we provide versatile resources for studying gene function and pathway and network architecture in Gram-positive bacteria.

  16. 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.

  17. Genome-scale analysis of gene function in the hydrogenotrophic methanogenic archaeon Methanococcus maripaludis.

    Science.gov (United States)

    Sarmiento, Felipe; Mrázek, Jan; Whitman, William B

    2013-03-19

    A comprehensive whole-genome analysis of gene function by transposon mutagenesis and deep sequencing methodology has been implemented successfully in a representative of the Archaea domain. Libraries of transposon mutants were generated for the hydrogenotrophic, methanogenic archaeon Methanococcus maripaludis S2 using a derivative of the Tn5 transposon. About 89,000 unique insertions were mapped to the genome, which allowed for the classification of 526 genes or about 30% of the genome as possibly essential or strongly advantageous for growth in rich medium. Many of these genes were homologous to eukaryotic genes that encode fundamental processes in replication, transcription, and translation, providing direct evidence for their importance in Archaea. Some genes classified as possibly essential were unique to the archaeal or methanococcal lineages, such as that encoding DNA polymerase PolD. In contrast, the archaeal homolog to the gene encoding DNA polymerase B was not essential for growth, a conclusion confirmed by construction of an independent deletion mutation. Thus PolD, and not PolB, likely plays a fundamental role in DNA replication in methanococci. Similarly, 121 hypothetical ORFs were classified as possibly essential and likely play fundamental roles in methanococcal information processing or metabolism that are not established outside this group of prokaryotes.

  18. Genome-Scale Transcriptome Analysis of the Desert Shrub Artemisia sphaerocephala.

    Directory of Open Access Journals (Sweden)

    Lijing Zhang

    Full Text Available Artemisia sphaerocephala, a semi-shrub belonging to the Artemisia genus of the Compositae family, is an important pioneer plant that inhabits moving and semi-stable sand dunes in the deserts and steppes of northwest and north-central China. It is very resilient in extreme environments. Additionally, its seeds have excellent nutritional value, and the abundant lipids and polysaccharides in the seeds make this plant a potential valuable source of bio-energy. However, partly due to the scarcity of genetic information, the genetic mechanisms controlling the traits and environmental adaptation capacity of A. sphaerocephala are unknown.Here, we present the first in-depth transcriptomic analysis of A. sphaerocephala. To maximize the representation of conditional transcripts, mRNA was obtained from 17 samples, including living tissues of desert-growing A. sphaerocephala, seeds germinated in the laboratory, and calli subjected to no stress (control and high and low temperature, high and low osmotic, and salt stresses. De novo transcriptome assembly performed using an Illumina HiSeq 2500 platform resulted in the generation of 68,373 unigenes. We analyzed the key genes involved in the unsaturated fatty acid synthesis pathway and identified 26 A. sphaerocephala fad2 genes, which is the largest fad2 gene family reported to date. Furthermore, a set of genes responsible for resistance to extreme temperatures, salt, drought and a combination of stresses was identified.The present work provides abundant genomic information for functional dissection of the important traits of A. sphaerocephala and contributes to the current understanding of molecular adaptive mechanisms of A. sphaerocephala in the desert environment. Identification of the key genes in the unsaturated fatty acid synthesis pathway could increase understanding of the biological regulatory mechanisms of fatty acid composition traits in plants and facilitate genetic manipulation of the fatty acid

  19. Genome-Scale Transcriptome Analysis of the Desert Shrub Artemisia sphaerocephala.

    Science.gov (United States)

    Zhang, Lijing; Hu, Xiaowei; Miao, Xiumei; Chen, Xiaolong; Nan, Shuzhen; Fu, Hua

    2016-01-01

    Artemisia sphaerocephala, a semi-shrub belonging to the Artemisia genus of the Compositae family, is an important pioneer plant that inhabits moving and semi-stable sand dunes in the deserts and steppes of northwest and north-central China. It is very resilient in extreme environments. Additionally, its seeds have excellent nutritional value, and the abundant lipids and polysaccharides in the seeds make this plant a potential valuable source of bio-energy. However, partly due to the scarcity of genetic information, the genetic mechanisms controlling the traits and environmental adaptation capacity of A. sphaerocephala are unknown. Here, we present the first in-depth transcriptomic analysis of A. sphaerocephala. To maximize the representation of conditional transcripts, mRNA was obtained from 17 samples, including living tissues of desert-growing A. sphaerocephala, seeds germinated in the laboratory, and calli subjected to no stress (control) and high and low temperature, high and low osmotic, and salt stresses. De novo transcriptome assembly performed using an Illumina HiSeq 2500 platform resulted in the generation of 68,373 unigenes. We analyzed the key genes involved in the unsaturated fatty acid synthesis pathway and identified 26 A. sphaerocephala fad2 genes, which is the largest fad2 gene family reported to date. Furthermore, a set of genes responsible for resistance to extreme temperatures, salt, drought and a combination of stresses was identified. The present work provides abundant genomic information for functional dissection of the important traits of A. sphaerocephala and contributes to the current understanding of molecular adaptive mechanisms of A. sphaerocephala in the desert environment. Identification of the key genes in the unsaturated fatty acid synthesis pathway could increase understanding of the biological regulatory mechanisms of fatty acid composition traits in plants and facilitate genetic manipulation of the fatty acid composition of oil

  20. Genome-scale metabolic reconstruction and in silico analysis of methylotrophic yeast Pichia pastoris for strain improvement

    Directory of Open Access Journals (Sweden)

    Chung Bevan KS

    2010-07-01

    Full Text Available Abstract Background Pichia pastoris has been recognized as an effective host for recombinant protein production. A number of studies have been reported for improving this expression system. However, its physiology and cellular metabolism still remained largely uncharacterized. Thus, it is highly desirable to establish a systems biotechnological framework, in which a comprehensive in silico model of P. pastoris can be employed together with high throughput experimental data analysis, for better understanding of the methylotrophic yeast's metabolism. Results A fully compartmentalized metabolic model of P. pastoris (iPP668, composed of 1,361 reactions and 1,177 metabolites, was reconstructed based on its genome annotation and biochemical information. The constraints-based flux analysis was then used to predict achievable growth rate which is consistent with the cellular phenotype of P. pastoris observed during chemostat experiments. Subsequent in silico analysis further explored the effect of various carbon sources on cell growth, revealing sorbitol as a promising candidate for culturing recombinant P. pastoris strains producing heterologous proteins. Interestingly, methanol consumption yields a high regeneration rate of reducing equivalents which is substantial for the synthesis of valuable pharmaceutical precursors. Hence, as a case study, we examined the applicability of P. pastoris system to whole-cell biotransformation and also identified relevant metabolic engineering targets that have been experimentally verified. Conclusion The genome-scale metabolic model characterizes the cellular physiology of P. pastoris, thus allowing us to gain valuable insights into the metabolism of methylotrophic yeast and devise possible strategies for strain improvement through in silico simulations. This computational approach, combined with synthetic biology techniques, potentially forms a basis for rational analysis and design of P. pastoris metabolic network

  1. 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.

  2. 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.

  3. 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

  4. DNAshape: a method for the high-throughput prediction of DNA structural features on a genomic scale

    Science.gov (United States)

    Zhou, Tianyin; Yang, Lin; Lu, Yan; Dror, Iris; Dantas Machado, Ana Carolina; Ghane, Tahereh; Di Felice, Rosa; Rohs, Remo

    2013-01-01

    We present a method and web server for predicting DNA structural features in a high-throughput (HT) manner for massive sequence data. This approach provides the framework for the integration of DNA sequence and shape analyses in genome-wide studies. The HT methodology uses a sliding-window approach to mine DNA structural information obtained from Monte Carlo simulations. It requires only nucleotide sequence as input and instantly predicts multiple structural features of DNA (minor groove width, roll, propeller twist and helix twist). The results of rigorous validations of the HT predictions based on DNA structures solved by X-ray crystallography and NMR spectroscopy, hydroxyl radical cleavage data, statistical analysis and cross-validation, and molecular dynamics simulations provide strong confidence in this approach. The DNAshape web server is freely available at http://rohslab.cmb.usc.edu/DNAshape/. PMID:23703209

  5. 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....

  6. 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.

  7. 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.

  8. 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.

  9. Genome-scale analysis of metazoan replication origins reveals their organization in specific but flexible sites defined by conserved features

    Science.gov (United States)

    Cayrou, Christelle; Coulombe, Philippe; Vigneron, Alice; Stanojcic, Slavica; Ganier, Olivier; Peiffer, Isabelle; Rivals, Eric; Puy, Aurore; Laurent-Chabalier, Sabine; Desprat, Romain; Méchali, Marcel

    2011-01-01

    In metazoans, thousands of DNA replication origins (Oris) are activated at each cell cycle. Their genomic organization and their genetic nature remain elusive. Here, we characterized Oris by nascent strand (NS) purification and a genome-wide analysis in Drosophila and mouse cells. We show that in both species most CpG islands (CGI) contain Oris, although methylation is nearly absent in Drosophila, indicating that this epigenetic mark is not crucial for defining the activated origin. Initiation of DNA synthesis starts at the borders of CGI, resulting in a striking bimodal distribution of NS, suggestive of a dual initiation event. Oris contain a unique nucleotide skew around NS peaks, characterized by G/T and C/A overrepresentation at the 5′ and 3′ of Ori sites, respectively. Repeated GC-rich elements were detected, which are good predictors of Oris, suggesting that common sequence features are part of metazoan Oris. In the heterochromatic chromosome 4 of Drosophila, Oris correlated with HP1 binding sites. At the chromosome level, regions rich in Oris are early replicating, whereas Ori-poor regions are late replicating. The genome-wide analysis was coupled with a DNA combing analysis to unravel the organization of Oris. The results indicate that Oris are in a large excess, but their activation does not occur at random. They are organized in groups of site-specific but flexible origins that define replicons, where a single origin is activated in each replicon. This organization provides both site specificity and Ori firing flexibility in each replicon, allowing possible adaptation to environmental cues and cell fates. PMID:21750104

  10. Comparative genome-scale analysis of niche-based stress-responsive genes in Lactobacillus helveticus strains.

    Science.gov (United States)

    Senan, Suja; Prajapati, Jashbhai B; Joshi, Chaitanya G

    2014-04-01

    Next generation sequencing technologies with advanced bioinformatic tools present a unique opportunity to compare genomes from diverse niches. The identification of niche-specific stress-responsive genes can help in characterizing robust strains for multiple applications. In this study, we attempted to compare the stress-responsive genes of a potential probiotic strain, Lactobacillus helveticus MTCC 5463, and a cheese starter strain, Lactobacillus helveticus DPC 4571, from a gut and dairy niche, respectively. Sequencing of MTCC 5463 was done using 454 GS FLX, and contigs were assembled using GS Assembler software. Genome analysis was done using BLAST hits and the prokaryotic annotation server RAST. The MTCC 5463 genome carried multiple orthologs of genes governing stress responses, whereas the DPC 4571 genome lacked in the number of major stress-response proteins. The absence of the bile salt hydrolase gene in DPC 4571 and its presence in MTCC 5463 clearly indicated niche adaptation. Further, MTCC 5463 carried higher copy numbers of genes contributing towards heat, cold, osmotic, and oxidative stress resistance as compared with DPC 4571. Through comparative genomics, we could thus identify stress-responsive gene sets required to adapt to gut and dairy niches.

  11. Genome-scale identification of cell-wall related genes in Arabidopsis based on co-expression network analysis

    Directory of Open Access Journals (Sweden)

    Wang Shan

    2012-08-01

    Full Text Available Abstract Background Identification of the novel genes relevant to plant cell-wall (PCW synthesis represents a highly important and challenging problem. Although substantial efforts have been invested into studying this problem, the vast majority of the PCW related genes remain unknown. Results Here we present a computational study focused on identification of the novel PCW genes in Arabidopsis based on the co-expression analyses of transcriptomic data collected under 351 conditions, using a bi-clustering technique. Our analysis identified 217 highly co-expressed gene clusters (modules under some experimental conditions, each containing at least one gene annotated as PCW related according to the Purdue Cell Wall Gene Families database. These co-expression modules cover 349 known/annotated PCW genes and 2,438 new candidates. For each candidate gene, we annotated the specific PCW synthesis stages in which it is involved and predicted the detailed function. In addition, for the co-expressed genes in each module, we predicted and analyzed their cis regulatory motifs in the promoters using our motif discovery pipeline, providing strong evidence that the genes in each co-expression module are transcriptionally co-regulated. From the all co-expression modules, we infer that 108 modules are related to four major PCW synthesis components, using three complementary methods. Conclusions We believe our approach and data presented here will be useful for further identification and characterization of PCW genes. All the predicted PCW genes, co-expression modules, motifs and their annotations are available at a web-based database: http://csbl.bmb.uga.edu/publications/materials/shanwang/CWRPdb/index.html.

  12. Cartilage-selective genes identified in genome-scale analysis of non-cartilage and cartilage gene expression

    Directory of Open Access Journals (Sweden)

    Cohn Zachary A

    2007-06-01

    Full Text Available Abstract Background Cartilage plays a fundamental role in the development of the human skeleton. Early in embryogenesis, mesenchymal cells condense and differentiate into chondrocytes to shape the early skeleton. Subsequently, the cartilage anlagen differentiate to form the growth plates, which are responsible for linear bone growth, and the articular chondrocytes, which facilitate joint function. However, despite the multiplicity of roles of cartilage during human fetal life, surprisingly little is known about its transcriptome. To address this, a whole genome microarray expression profile was generated using RNA isolated from 18–22 week human distal femur fetal cartilage and compared with a database of control normal human tissues aggregated at UCLA, termed Celsius. Results 161 cartilage-selective genes were identified, defined as genes significantly expressed in cartilage with low expression and little variation across a panel of 34 non-cartilage tissues. Among these 161 genes were cartilage-specific genes such as cartilage collagen genes and 25 genes which have been associated with skeletal phenotypes in humans and/or mice. Many of the other cartilage-selective genes do not have established roles in cartilage or are novel, unannotated genes. Quantitative RT-PCR confirmed the unique pattern of gene expression observed by microarray analysis. Conclusion Defining the gene expression pattern for cartilage has identified new genes that may contribute to human skeletogenesis as well as provided further candidate genes for skeletal dysplasias. The data suggest that fetal cartilage is a complex and transcriptionally active tissue and demonstrate that the set of genes selectively expressed in the tissue has been greatly underestimated.

  13. The genome sequence of E. coli W (ATCC 9637: comparative genome analysis and an improved genome-scale reconstruction of E. coli

    Directory of Open Access Journals (Sweden)

    Lee Sang

    2011-01-01

    Full Text Available Abstract Background Escherichia coli is a model prokaryote, an important pathogen, and a key organism for industrial biotechnology. E. coli W (ATCC 9637, one of four strains designated as safe for laboratory purposes, has not been sequenced. E. coli W is a fast-growing strain and is the only safe strain that can utilize sucrose as a carbon source. Lifecycle analysis has demonstrated that sucrose from sugarcane is a preferred carbon source for industrial bioprocesses. Results We have sequenced and annotated the genome of E. coli W. The chromosome is 4,900,968 bp and encodes 4,764 ORFs. Two plasmids, pRK1 (102,536 bp and pRK2 (5,360 bp, are also present. W has unique features relative to other sequenced laboratory strains (K-12, B and Crooks: it has a larger genome and belongs to phylogroup B1 rather than A. W also grows on a much broader range of carbon sources than does K-12. A genome-scale reconstruction was developed and validated in order to interrogate metabolic properties. Conclusions The genome of W is more similar to commensal and pathogenic B1 strains than phylogroup A strains, and therefore has greater utility for comparative analyses with these strains. W should therefore be the strain of choice, or 'type strain' for group B1 comparative analyses. The genome annotation and tools created here are expected to allow further utilization and development of E. coli W as an industrial organism for sucrose-based bioprocesses. Refinements in our E. coli metabolic reconstruction allow it to more accurately define E. coli metabolism relative to previous models.

  14. 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

  15. 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...

  16. 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.

  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. 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.

  19. Genome-scale sequence data processing and epigenetic analysis of DNA methylation%基因组规模DNA 甲基化测序数据处理及其表观遗传分析

    Institute of Scientific and Technical Information of China (English)

    王庭璋; 单杲; 徐建红; 薛庆中

    2013-01-01

    sequences, such as transposable elements. In this paper, we introduce the preprocessing steps of DNA methylation data, by which cytosine (C) and guanine (G) in the reference sequence are transferred to thymine (T) and adenine (A), and cytosine in reads is transferred to thymine, respectively. We also comprehensively review the main content of the DNA methylation analysis on the genomic scale: (1) the cytosine methylation under the context of different sequences; (2) the distribution of genomic methylcytosine; (3) DNA methylation context and the preference for the nucleotides; (4) DNA- protein interaction sites of DNA methylation; (5) degree of methylation of cytosine in the different structural elements of genes. DNA methylation analysis technique provides a powerful tool for the epigenome study in human and other species, and genes and environment interaction, and founds the theoretical basis for further development of disease diagnostics and therapeutics in human.

  20. 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.

  1. Modeling cancer metabolism on a genome scale

    Science.gov (United States)

    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

  2. New statistical Methods of Genome-Scale Data Analysis in Life Science - Applications to enterobacterial Diagnostics, Meta-Analysis of Arabidopsis thaliana Gene Expression and functional Sequence Annotation

    OpenAIRE

    Friedrich, Torben

    2009-01-01

    Recent progresses and developments in molecular biology provide a wealth of new but insufficiently characterised data. This fund comprises amongst others biological data of genomic DNA, protein sequences, 3-dimensional protein structures as well as profiles of gene expression. In the present work, this information is used to develop new methods for the characterisation and classification of organisms and whole groups of organisms as well as to enhance the automated gain and transfer of inform...

  3. 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.

  4. Genome-Scale Multilocus Microsatellite Typing of Trypanosoma cruzi Discrete Typing Unit I Reveals Phylogeographic Structure and Specific Genotypes Linked to Human Infection

    Science.gov (United States)

    Llewellyn, Martin S.; Miles, Michael A.; Carrasco, Hernan J.; Lewis, Michael D.; Yeo, Matthew; Vargas, Jorge; Torrico, Faustino; Diosque, Patricio; Valente, Vera; Valente, Sebastiao A.; Gaunt, Michael W.

    2009-01-01

    Trypanosoma cruzi is the most important parasitic infection in Latin America and is also genetically highly diverse, with at least six discrete typing units (DTUs) reported: Tc I, IIa, IIb, IIc, IId, and IIe. However, the current six-genotype classification is likely to be a poor reflection of the total genetic diversity present in this undeniably ancient parasite. To determine whether epidemiologically important information is “hidden” at the sub-DTU level, we developed a 48-marker panel of polymorphic microsatellite loci to investigate population structure among 135 samples from across the geographic distribution of TcI. This DTU is the major cause of resurgent human disease in northern South America but also occurs in silvatic triatomine vectors and mammalian reservoir hosts throughout the continent. Based on a total dataset of 12,329 alleles, we demonstrate that silvatic TcI populations are extraordinarily genetically diverse, show spatial structuring on a continental scale, and have undergone recent biogeographic expansion into the southern United States of America. Conversely, the majority of human strains sampled are restricted to two distinct groups characterised by a considerable reduction in genetic diversity with respect to isolates from silvatic sources. In Venezuela, most human isolates showed little identity with known local silvatic strains, despite frequent invasion of the domestic setting by infected adult vectors. Multilocus linkage indices indicate predominantly clonal parasite propagation among all populations. However, excess homozygosity among silvatic strains and raised heterozygosity among domestic populations suggest that some level of genetic recombination cannot be ruled out. The epidemiological significance of these findings is discussed. PMID:19412340

  5. Genome-scale multilocus microsatellite typing of Trypanosoma cruzi discrete typing unit I reveals phylogeographic structure and specific genotypes linked to human infection.

    Directory of Open Access Journals (Sweden)

    Martin S Llewellyn

    2009-05-01

    Full Text Available Trypanosoma cruzi is the most important parasitic infection in Latin America and is also genetically highly diverse, with at least six discrete typing units (DTUs reported: Tc I, IIa, IIb, IIc, IId, and IIe. However, the current six-genotype classification is likely to be a poor reflection of the total genetic diversity present in this undeniably ancient parasite. To determine whether epidemiologically important information is "hidden" at the sub-DTU level, we developed a 48-marker panel of polymorphic microsatellite loci to investigate population structure among 135 samples from across the geographic distribution of TcI. This DTU is the major cause of resurgent human disease in northern South America but also occurs in silvatic triatomine vectors and mammalian reservoir hosts throughout the continent. Based on a total dataset of 12,329 alleles, we demonstrate that silvatic TcI populations are extraordinarily genetically diverse, show spatial structuring on a continental scale, and have undergone recent biogeographic expansion into the southern United States of America. Conversely, the majority of human strains sampled are restricted to two distinct groups characterised by a considerable reduction in genetic diversity with respect to isolates from silvatic sources. In Venezuela, most human isolates showed little identity with known local silvatic strains, despite frequent invasion of the domestic setting by infected adult vectors. Multilocus linkage indices indicate predominantly clonal parasite propagation among all populations. However, excess homozygosity among silvatic strains and raised heterozygosity among domestic populations suggest that some level of genetic recombination cannot be ruled out. The epidemiological significance of these findings is discussed.

  6. Genome Scale Mutational Analysis of Geobacter sulfurreducens Reveals Distinct Molecular Mechanisms for Respiration and Sensing of Poised Electrodes versus Fe(III) Oxides.

    Science.gov (United States)

    Chan, Chi Ho; Levar, Caleb E; Jiménez-Otero, Fernanda; Bond, Daniel R

    2017-10-01

    Geobacter sulfurreducens generates electrical current by coupling intracellular oxidation of organic acids to the reduction of proteins on the cell surface that are able to interface with electrodes. This ability is attributed to the bacterium's capacity to respire other extracellular electron acceptors that require contact, such as insoluble metal oxides. To directly investigate the genetic basis of electrode-based respiration, we constructed Geobacter sulfurreducens transposon-insertion sequencing (Tn-Seq) libraries for growth, with soluble fumarate or an electrode as the electron acceptor. Libraries with >33,000 unique insertions and an average of 9 insertions/kb allowed an assessment of each gene's fitness in a single experiment. Mutations in 1,214 different genomic features impaired growth with fumarate, and the significance of 270 genes unresolved by annotation due to the presence of one or more functional homologs was determined. Tn-Seq analysis of -0.1 V versus standard hydrogen electrode (SHE) electrode-grown cells identified mutations in a subset of genes encoding cytochromes, processing systems for proline-rich proteins, sensory networks, extracellular structures, polysaccharides, and metabolic enzymes that caused at least a 50% reduction in apparent growth rate. Scarless deletion mutants of select genes identified via Tn-Seq revealed a new putative porin-cytochrome conduit complex (extABCD) crucial for growth with electrodes, which was not required for Fe(III) oxide reduction. In addition, four mutants lacking components of a putative methyl-accepting chemotaxis-cyclic dinucleotide sensing network (esnABCD) were defective in electrode colonization but grew normally with Fe(III) oxides. These results suggest that G. sulfurreducens possesses distinct mechanisms for recognition, colonization, and reduction of electrodes compared to Fe(III) oxides.IMPORTANCE Since metal oxide electron acceptors are insoluble, one hypothesis is that cells sense and reduce

  7. 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

  8. 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

  9. 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

  10. Microarray Analysis of Serum mRNA in Patients with Head and Neck Squamous Cell Carcinoma at Whole-Genome Scale

    Directory of Open Access Journals (Sweden)

    Markéta Čapková

    2014-01-01

    Full Text Available With the increasing demand for noninvasive approaches in monitoring head and neck cancer, circulating nucleic acids have been shown to be a promising tool. We focused on the global transcriptome of serum samples of head and neck squamous cell carcinoma (HNSCC patients in comparison with healthy individuals. We compared gene expression patterns of 36 samples. Twenty-four participants including 16 HNSCC patients (from 12 patients we obtained blood samples 1 year posttreatment and 8 control subjects were recruited. The Illumina HumanWG-6 v3 Expression BeadChip was used to profile and identify the differences in serum mRNA transcriptomes. We found 159 genes to be significantly changed (Storey’s P value <0.05 between normal and cancer serum specimens regardless of factors including p53 and B-cell lymphoma family members (Bcl-2, Bcl-XL. In contrast, there was no difference in gene expression between samples obtained before and after surgery in cancer patients. We suggest that microarray analysis of serum cRNA in patients with HNSCC should be suitable for refinement of early stage diagnosis of disease that can be important for development of new personalized strategies in diagnosis and treatment of tumours but is not suitable for monitoring further development of disease.

  11. 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.

  12. 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.

  13. 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.

  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. 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

  16. 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.

  17. 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...

  18. 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...

  19. 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....

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

    Science.gov (United States)

    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.

  1. 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...

  2. 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.

  3. 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...

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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.

  9. 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

  10. Sequential computation of elementary modes and minimal cut sets in genome-scale metabolic networks using alternate integer linear programming

    Energy Technology Data Exchange (ETDEWEB)

    Song, Hyun-Seob; Goldberg, Noam; Mahajan, Ashutosh; Ramkrishna, Doraiswami

    2017-03-27

    Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Results: Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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...

  16. 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.

  17. 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/.

  18. 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.

  19. 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.

  20. 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/.

  1. Sequential computation of elementary modes and minimal cut sets in genome-scale metabolic networks using alternate integer linear programming.

    Science.gov (United States)

    Song, Hyun-Seob; Goldberg, Noam; Mahajan, Ashutosh; Ramkrishna, Doraiswami

    2017-08-01

    Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs. The software is implemented in Matlab, and is provided as supplementary information . hyunseob.song@pnnl.gov. Supplementary data are available at Bioinformatics online.

  2. 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....

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

    Directory of Open Access Journals (Sweden)

    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

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. 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.

  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. 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

  16. 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/.

  17. 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.

  18. 基因组水平预测稻瘟菌分泌蛋白组及富集分析%Prediction for Secretome from Magnaporthe oryzae at Genome Scale and Its Enrichment Analysis

    Institute of Scientific and Technical Information of China (English)

    曹继东; 刘俊; 李遂焰

    2016-01-01

    稻瘟菌分泌蛋白在稻瘟菌入侵植物过程中发挥着重要的作用。这些分泌蛋白中有很多是效应蛋白,这些效应蛋白可以干扰寄主的抗性、抑制寄主免疫反应。因此,对稻瘟菌分泌蛋白组的预测及功能分析就显得十分必要,也是目前植物和微生物分子互作研究领域的热点。使用 SignalP、TMHMM 及 SecretomeP 等软件,完成稻瘟菌分泌蛋白组的预测。同时,对含信号肽的经典分泌蛋白进行了 GO 功能富集、KEGG 通路分析、结构域统计以及可降解植物成分的经典分泌蛋白预测等分析。结果显示,稻瘟菌含有约789个分泌蛋白,其长度多集中在100-500 aa ;GO 功能分析发现,这些分泌蛋白多富集在分泌途径及宿主互作中;KEGG 分析显示,分泌蛋白在糖代谢途径中发挥着重要作用;大规模筛选预测到156个分泌蛋白具有降解植物细胞壁等成分的功能;同时还发现稻瘟菌中有可能存在大量不含信号肽的非经典分泌蛋白。通过设计的生物信息学流程,实现了稻瘟菌分泌蛋白组的预测;预测出经典分泌蛋白具有可降解植物细胞壁等成分以及参与糖代谢途径的功能;稻瘟菌中存在大量的无信号肽的非经典分泌蛋白。%Secreted proteins play an important role during pathogenic process of Magnaporthe oryzae. However,many of those secreted proteins are actually effect proteins that interfere the resistance of host plants and inhibit the immune responses of host plants. Therefore,the prediction of secreted proteins by M. oryzae and its functional analysis are necessary and hot topics in the interaction of plant and microbe molecules. The software SignalP,TMHMM,and SecretomeP were applied to complete the prediction of the secretome by M. oryzae. The analyses of classical secreted proteins(CSPs)containing signal peptide by GO function enrichment,KEGG pathway,and statistics of domains were performed

  19. On Genome-scale Identification and Expression Analysis of LEA Genes in Poplar%杨树 LEA 基因家族全基因组鉴定及表达分析

    Institute of Scientific and Technical Information of China (English)

    李军; 赵爱春; 刘长英; 王茜龄; 刘晓清; 余茂德

    2016-01-01

    从杨树基因组中鉴定 LEA 蛋白家族成员,并分析基因在杨树各组织以及在种子形成、吸涨及萌发过程中的表达情况.从 NCBI 下载拟南芥、水稻以及大豆等植物的 LEA 蛋白家族成员,通过 blastP 程序从杨树基因组中鉴定出候选基因,并采用 pfam 程序进行进一步筛选获得杨树 LEA 蛋白基因,最后通过芯片以及 EST 数据分析基因的表达量.通过对杨树 LEA 蛋白基因家族在全基因组水平上的搜索,确定了杨树 LEA 蛋白家族8个亚家族,共87个成员,发现在花中有16个基因高量表达,且其中8个基因具有很高的组织特异性.在吸涨种子中,PtLEA1.1和PtLEA3.1有高量的表达,LEAⅣ,LEAⅤ,LEAⅥ及 SMP 亚家族成员都具有特异的表达.12个基因在萌发种子中有高量的表达,其中4个基因特异表达,5个基因在种子萌发过程中可能受到光照的影响.此外,3个基因在成熟叶片中出现了下调表达,8个基因在根中具有高量表达,3个基因的高量表达在木质部中被发现.杨树 LEA 蛋白不同亚家族成员可能参与了植物种子的生长发育、种子的萌发及对胁迫的响应等多种生理功能.%In our study,LEA gene families have been identified and their expression profiles beenalso bioin-formaticaslly analyzed.The sequences of LEA genes in Arabidopsis thaliana ,Rice,Glycine max have been downloaded from NCBI web site to search the LEA genes in poplar.Candidate gene have been deter-mined by means ofthe pfam program.Microarray Data and EST have been used to value the expression of LEA genes.According to motif analysis,a total of 87 LEA genes have been systematically identified from poplar classified into 8 subfamilies in our study.1 6 LEA genes have been highly expressed in flowers and 8 of them shared tissue-specific expression.PtLEA1.1 and PtLEA3.1 have high abundant expression in im-bibition seeds,as well as members of subfamilies LEAIV,LEAV,LEAVI and SMP.In germination seeds

  20. 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...

  1. 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

  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. 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

  5. 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

  6. 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.

  7. 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.

  8. 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....

  9. 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.

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

    Science.gov (United States)

    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

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

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    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. Identification of novel targets for breast cancer by exploring gene switches on a genome scale

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    Wu Ming

    2011-11-01

    Full Text Available Abstract Background An important feature that emerges from analyzing gene regulatory networks is the "switch-like behavior" or "bistability", a dynamic feature of a particular gene to preferentially toggle between two steady-states. The state of gene switches plays pivotal roles in cell fate decision, but identifying switches has been difficult. Therefore a challenge confronting the field is to be able to systematically identify gene switches. Results We propose a top-down mining approach to exploring gene switches on a genome-scale level. Theoretical analysis, proof-of-concept examples, and experimental studies demonstrate the ability of our mining approach to identify bistable genes by sampling across a variety of different conditions. Applying the approach to human breast cancer data identified genes that show bimodality within the cancer samples, such as estrogen receptor (ER and ERBB2, as well as genes that show bimodality between cancer and non-cancer samples, where tumor-associated calcium signal transducer 2 (TACSTD2 is uncovered. We further suggest a likely transcription factor that regulates TACSTD2. Conclusions Our mining approach demonstrates that one can capitalize on genome-wide expression profiling to capture dynamic properties of a complex network. To the best of our knowledge, this is the first attempt in applying mining approaches to explore gene switches on a genome-scale, and the identification of TACSTD2 demonstrates that single cell-level bistability can be predicted from microarray data. Experimental confirmation of the computational results suggest TACSTD2 could be a potential biomarker and attractive candidate for drug therapy against both ER+ and ER- subtypes of breast cancer, including the triple negative subtype.

  13. 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.

  14. 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.

  15. 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.

  16. 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

  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. 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.

  19. Revealing genome-scale transcriptional regulatory landscape of OmpR highlights its expanded regulatory roles under osmotic stress in Escherichia coli K-12 MG1655

    DEFF Research Database (Denmark)

    Seo, Sang Woo; Gao, Ye; Kim, Donghyuk

    2017-01-01

    A transcription factor (TF), OmpR, plays a critical role in transcriptional regulation of the osmotic stress response in bacteria. Here, we reveal a genome-scale OmpR regulon in Escherichia coli K-12 MG1655. Integrative data analysis reveals that a total of 37 genes in 24 transcription units (TUs...

  20. 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...

  1. Folding Free Energies of 5'-UTRs Impact Post-Transcriptional Regulation on a Genomic Scale in Yeast.

    Directory of Open Access Journals (Sweden)

    2005-12-01

    Full Text Available Using high-throughput technologies, abundances and other features of genes and proteins have been measured on a genome-wide scale in Saccharomyces cerevisiae. In contrast, secondary structure in 5'-untranslated regions (UTRs of mRNA has only been investigated for a limited number of genes. Here, the aim is to study genome-wide regulatory effects of mRNA 5'-UTR folding free energies. We performed computations of secondary structures in 5'-UTRs and their folding free energies for all verified genes in S. cerevisiae. We found significant correlations between folding free energies of 5'-UTRs and various transcript features measured in genome-wide studies of yeast. In particular, mRNAs with weakly folded 5'-UTRs have higher translation rates, higher abundances of the corresponding proteins, longer half-lives, and higher numbers of transcripts, and are upregulated after heat shock. Furthermore, 5'-UTRs have significantly higher folding free energies than other genomic regions and randomized sequences. We also found a positive correlation between transcript half-life and ribosome occupancy that is more pronounced for short-lived transcripts, which supports a picture of competition between translation and degradation. Among the genes with strongly folded 5'-UTRs, there is a huge overrepresentation of uncharacterized open reading frames. Based on our analysis, we conclude that (i there is a widespread bias for 5'-UTRs to be weakly folded, (ii folding free energies of 5'-UTRs are correlated with mRNA translation and turnover on a genomic scale, and (iii transcripts with strongly folded 5'-UTRs are often rare and hard to find experimentally.

  2. 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.

  3. 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

  4. 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.

  5. Genome-scale identification method applied to find cryptic aminoglycoside resistance genes in Pseudomonas aeruginosa.

    Directory of Open Access Journals (Sweden)

    Julie M Struble

    Full Text Available BACKGROUND: The ability of bacteria to rapidly evolve resistance to antibiotics is a critical public health problem. Resistance leads to increased disease severity and death rates, as well as imposes pressure towards the discovery and development of new antibiotic therapies. Improving understanding of the evolution and genetic basis of resistance is a fundamental goal in the field of microbiology. RESULTS: We have applied a new genomic method, Scalar Analysis of Library Enrichments (SCALEs, to identify genomic regions that, given increased copy number, may lead to aminoglycoside resistance in Pseudomonas aeruginosa at the genome scale. We report the result of selections on highly representative genomic libraries for three different aminoglycoside antibiotics (amikacin, gentamicin, and tobramycin. At the genome-scale, we show significant (p<0.05 overlap in genes identified for each aminoglycoside evaluated. Among the genomic segments identified, we confirmed increased resistance associated with an increased copy number of several genomic regions, including the ORF of PA5471, recently implicated in MexXY efflux pump related aminoglycoside resistance, PA4943-PA4946 (encoding a probable GTP-binding protein, a predicted host factor I protein, a delta 2-isopentenylpyrophosphate transferase, and DNA mismatch repair protein mutL, PA0960-PA0963 (encoding hypothetical proteins, a probable cold shock protein, a probable DNA-binding stress protein, and aspartyl-tRNA synthetase, a segment of PA4967 (encoding a topoisomerase IV subunit B, as well as a chimeric clone containing two inserts including the ORFs PA0547 and PA2326 (encoding a probable transcriptional regulator and a probable hypothetical protein, respectively. CONCLUSIONS: The studies reported here demonstrate the application of new a genomic method, SCALEs, which can be used to improve understanding of the evolution of antibiotic resistance in P. aeruginosa. In our demonstration studies, we

  6. Functional states of the genome-scale Escherichia coli transcriptional regulatory system.

    Directory of Open Access Journals (Sweden)

    Erwin P Gianchandani

    2009-06-01

    Full Text Available A transcriptional regulatory network (TRN constitutes the collection of regulatory rules that link environmental cues to the transcription state of a cell's genome. We recently proposed a matrix formalism that quantitatively represents a system of such rules (a transcriptional regulatory system [TRS] and allows systemic characterization of TRS properties. The matrix formalism not only allows the computation of the transcription state of the genome but also the fundamental characterization of the input-output mapping that it represents. Furthermore, a key advantage of this "pseudo-stoichiometric" matrix formalism is its ability to easily integrate with existing stoichiometric matrix representations of signaling and metabolic networks. Here we demonstrate for the first time how this matrix formalism is extendable to large-scale systems by applying it to the genome-scale Escherichia coli TRS. We analyze the fundamental subspaces of the regulatory network matrix (R to describe intrinsic properties of the TRS. We further use Monte Carlo sampling to evaluate the E. coli transcription state across a subset of all possible environments, comparing our results to published gene expression data as validation. Finally, we present novel in silico findings for the E. coli TRS, including (1 a gene expression correlation matrix delineating functional motifs; (2 sets of gene ontologies for which regulatory rules governing gene transcription are poorly understood and which may direct further experimental characterization; and (3 the appearance of a distributed TRN structure, which is in stark contrast to the more hierarchical organization of metabolic networks.

  7. Functional states of the genome-scale Escherichia coli transcriptional regulatory system.

    Science.gov (United States)

    Gianchandani, Erwin P; Joyce, Andrew R; Palsson, Bernhard Ø; Papin, Jason A

    2009-06-01

    A transcriptional regulatory network (TRN) constitutes the collection of regulatory rules that link environmental cues to the transcription state of a cell's genome. We recently proposed a matrix formalism that quantitatively represents a system of such rules (a transcriptional regulatory system [TRS]) and allows systemic characterization of TRS properties. The matrix formalism not only allows the computation of the transcription state of the genome but also the fundamental characterization of the input-output mapping that it represents. Furthermore, a key advantage of this "pseudo-stoichiometric" matrix formalism is its ability to easily integrate with existing stoichiometric matrix representations of signaling and metabolic networks. Here we demonstrate for the first time how this matrix formalism is extendable to large-scale systems by applying it to the genome-scale Escherichia coli TRS. We analyze the fundamental subspaces of the regulatory network matrix (R) to describe intrinsic properties of the TRS. We further use Monte Carlo sampling to evaluate the E. coli transcription state across a subset of all possible environments, comparing our results to published gene expression data as validation. Finally, we present novel in silico findings for the E. coli TRS, including (1) a gene expression correlation matrix delineating functional motifs; (2) sets of gene ontologies for which regulatory rules governing gene transcription are poorly understood and which may direct further experimental characterization; and (3) the appearance of a distributed TRN structure, which is in stark contrast to the more hierarchical organization of metabolic networks.

  8. 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.

  9. 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.

  10. 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

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

    Science.gov (United States)

    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.

  12. Genome scale evolution of myxoma virus reveals host-pathogen adaptation and rapid geographic spread.

    Science.gov (United States)

    Kerr, Peter J; Rogers, Matthew B; Fitch, Adam; Depasse, Jay V; Cattadori, Isabella M; Twaddle, Alan C; Hudson, Peter J; Tscharke, David C; Read, Andrew F; Holmes, Edward C; Ghedin, Elodie

    2013-12-01

    The evolutionary interplay between myxoma virus (MYXV) and the European rabbit (Oryctolagus cuniculus) following release of the virus in Australia in 1950 as a biological control is a classic example of host-pathogen coevolution. We present a detailed genomic and phylogeographic analysis of 30 strains of MYXV, including the Australian progenitor strain Standard Laboratory Strain (SLS), 24 Australian viruses isolated from 1951 to 1999, and three isolates from the early radiation in Britain from 1954 and 1955. We show that in Australia MYXV has spread rapidly on a spatial scale, with multiple lineages cocirculating within individual localities, and that both highly virulent and attenuated viruses were still present in the field through the 1990s. In addition, the detection of closely related virus lineages at sites 1,000 km apart suggests that MYXV moves freely in geographic space, with mosquitoes, fleas, and rabbit migration all providing means of transport. Strikingly, despite multiple introductions, all modern viruses appear to be ultimately derived from the original introductions of SLS. The rapidity of MYXV evolution was also apparent at the genomic scale, with gene duplications documented in a number of viruses. Duplication of potential virulence genes may be important in increasing the expression of virulence proteins and provides the basis for the evolution of novel functions. Mutations leading to loss of open reading frames were surprisingly frequent and in some cases may explain attenuation, but no common mutations that correlated with virulence or attenuation were identified.

  13. 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.

  14. 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.

  15. Factors affecting reproducibility between genome-scale siRNA-based screens

    Science.gov (United States)

    Barrows, Nicholas J.; Le Sommer, Caroline; Garcia-Blanco, Mariano A.; Pearson, James L.

    2011-01-01

    RNA interference-based screening is a powerful new genomic technology which addresses gene function en masse. To evaluate factors influencing hit list composition and reproducibility, we performed two identically designed small interfering RNA (siRNA)-based, whole genome screens for host factors supporting yellow fever virus infection. These screens represent two separate experiments completed five months apart and allow the direct assessment of the reproducibility of a given siRNA technology when performed in the same environment. Candidate hit lists generated by sum rank, median absolute deviation, z-score, and strictly standardized mean difference were compared within and between whole genome screens. Application of these analysis methodologies within a single screening dataset using a fixed threshold equivalent to a p-value ≤ 0.001 resulted in hit lists ranging from 82 to 1,140 members and highlighted the tremendous impact analysis methodology has on hit list composition. Intra- and inter-screen reproducibility was significantly influenced by the analysis methodology and ranged from 32% to 99%. This study also highlighted the power of testing at least two independent siRNAs for each gene product in primary screens. To facilitate validation we conclude by suggesting methods to reduce false discovery at the primary screening stage. In this study we present the first comprehensive comparison of multiple analysis strategies, and demonstrate the impact of the analysis methodology on the composition of the “hit list”. Therefore, we propose that the entire dataset derived from functional genome-scale screens, especially if publicly funded, should be made available as is done with data derived from gene expression and genome-wide association studies. PMID:20625183

  16. Structural analysis for Diagnosis

    DEFF Research Database (Denmark)

    Izadi-Zamanabadi, Roozbeh; Blanke, M.

    2001-01-01

    Aiming at design of algorithms for fault diagnosis, structural analysis of systems offers concise yet easy overall analysis. Graph-based matching, which is the essential technique to obtain redundant information for diagnosis, is re-considered in this paper. Matching is re-formulated as a problem...

  17. Structural analysis for diagnosis

    DEFF Research Database (Denmark)

    Izadi-Zamanabadi, Roozbeh; Blanke, M.

    2002-01-01

    Aiming at design of algorithms for fault diagnosis, structural analysis of systems offers concise yet easy overall analysis. Graph-based matching, which is the essential tech-nique to obtain redundant information for diagnosis, is reconsidered in this paper. Matching is reformulated as a problem...

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Probabilistic Structural Analysis Program

    Science.gov (United States)

    Pai, Shantaram S.; Chamis, Christos C.; Murthy, Pappu L. N.; Stefko, George L.; Riha, David S.; Thacker, Ben H.; Nagpal, Vinod K.; Mital, Subodh K.

    2010-01-01

    NASA/NESSUS 6.2c is a general-purpose, probabilistic analysis program that computes probability of failure and probabilistic sensitivity measures of engineered systems. Because NASA/NESSUS uses highly computationally efficient and accurate analysis techniques, probabilistic solutions can be obtained even for extremely large and complex models. Once the probabilistic response is quantified, the results can be used to support risk-informed decisions regarding reliability for safety-critical and one-of-a-kind systems, as well as for maintaining a level of quality while reducing manufacturing costs for larger-quantity products. NASA/NESSUS has been successfully applied to a diverse range of problems in aerospace, gas turbine engines, biomechanics, pipelines, defense, weaponry, and infrastructure. This program combines state-of-the-art probabilistic algorithms with general-purpose structural analysis and lifting methods to compute the probabilistic response and reliability of engineered structures. Uncertainties in load, material properties, geometry, boundary conditions, and initial conditions can be simulated. The structural analysis methods include non-linear finite-element methods, heat-transfer analysis, polymer/ceramic matrix composite analysis, monolithic (conventional metallic) materials life-prediction methodologies, boundary element methods, and user-written subroutines. Several probabilistic algorithms are available such as the advanced mean value method and the adaptive importance sampling method. NASA/NESSUS 6.2c is structured in a modular format with 15 elements.

  3. 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...

  4. An exact arithmetic toolbox for a consistent and reproducible structural analysis of metabolic network models.

    Science.gov (United States)

    Chindelevitch, Leonid; Trigg, Jason; Regev, Aviv; Berger, Bonnie

    2014-10-07

    Constraint-based models are currently the only methodology that allows the study of metabolism at the whole-genome scale. Flux balance analysis is commonly used to analyse constraint-based models. Curiously, the results of this analysis vary with the software being run, a situation that we show can be remedied by using exact rather than floating-point arithmetic. Here we introduce MONGOOSE, a toolbox for analysing the structure of constraint-based metabolic models in exact arithmetic. We apply MONGOOSE to the analysis of 98 existing metabolic network models and find that the biomass reaction is surprisingly blocked (unable to sustain non-zero flux) in nearly half of them. We propose a principled approach for unblocking these reactions and extend it to the problems of identifying essential and synthetic lethal reactions and minimal media. Our structural insights enable a systematic study of constraint-based metabolic models, yielding a deeper understanding of their possibilities and limitations.

  5. GMATA: an integrated software package for genome-scale SSR mining, marker development and viewing

    Directory of Open Access Journals (Sweden)

    Xuewen Wang

    2016-09-01

    Full Text Available Simple sequence repeats (SSRs, also referred to as microsatellites, are highly variable tandem DNAs that are widely used as genetic markers. The increasing availability of whole-genome and transcript sequences provides information resources for SSR marker development. However, efficient software is required to efficiently identify and display SSR information along with other gene features at a genome scale. We developed novel software package Genome-wide Microsatellite Analyzing Tool Package (GMATA integrating SSR mining, statistical analysis and plotting, marker design, polymorphism screening and marker transferability, and enabled simultaneously display SSR markers with other genome features. GMATA applies novel strategies for SSR analysis and primer design in large genomes, which allows GMATA to perform faster calculation and provides more accurate results than existing tools. Our package is also capable of processing DNA sequences of any size on a standard computer. GMATA is user friendly, only requires mouse clicks or types inputs on the command line, and is executable in multiple computing platforms. We demonstrated the application of GMATA in plants genomes and reveal a novel distribution pattern of SSRs in 15 grass genomes. The most abundant motifs are dimer GA/TC, the A/T monomer and the GCG/CGC trimer, rather than the rich G/C content in DNA sequence. We also revealed that SSR count is a linear to the chromosome length in fully assembled grass genomes. GMATA represents a powerful application tool that facilitates genomic sequence analyses. GAMTA is freely available at http://sourceforge.net/projects/gmata/?source=navbar.

  6. GMATA: An Integrated Software Package for Genome-Scale SSR Mining, Marker Development and Viewing

    Science.gov (United States)

    Wang, Xuewen; Wang, Le

    2016-01-01

    Simple sequence repeats (SSRs), also referred to as microsatellites, are highly variable tandem DNAs that are widely used as genetic markers. The increasing availability of whole-genome and transcript sequences provides information resources for SSR marker development. However, efficient software is required to efficiently identify and display SSR information along with other gene features at a genome scale. We developed novel software package Genome-wide Microsatellite Analyzing Tool Package (GMATA) integrating SSR mining, statistical analysis and plotting, marker design, polymorphism screening and marker transferability, and enabled simultaneously display SSR markers with other genome features. GMATA applies novel strategies for SSR analysis and primer design in large genomes, which allows GMATA to perform faster calculation and provides more accurate results than existing tools. Our package is also capable of processing DNA sequences of any size on a standard computer. GMATA is user friendly, only requires mouse clicks or types inputs on the command line, and is executable in multiple computing platforms. We demonstrated the application of GMATA in plants genomes and reveal a novel distribution pattern of SSRs in 15 grass genomes. The most abundant motifs are dimer GA/TC, the A/T monomer and the GCG/CGC trimer, rather than the rich G/C content in DNA sequence. We also revealed that SSR count is a linear to the chromosome length in fully assembled grass genomes. GMATA represents a powerful application tool that facilitates genomic sequence analyses. GAMTA is freely available at http://sourceforge.net/projects/gmata/?source=navbar. PMID:27679641

  7. RegPrecise 3.0--a resource for genome-scale exploration of transcriptional regulation in bacteria.

    Science.gov (United States)

    Novichkov, Pavel S; Kazakov, Alexey E; Ravcheev, Dmitry A; Leyn, Semen A; Kovaleva, Galina Y; Sutormin, Roman A; Kazanov, Marat D; Riehl, William; Arkin, Adam P; Dubchak, Inna; Rodionov, Dmitry A

    2013-11-01

    Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in prokaryotes is one of the critical tasks of modern genomics. Bacteria from different taxonomic groups, whose lifestyles and natural environments are substantially different, possess highly diverged transcriptional regulatory networks. The comparative genomics approaches are useful for in silico reconstruction of bacterial regulons and networks operated by both transcription factors (TFs) and RNA regulatory elements (riboswitches). RegPrecise (http://regprecise.lbl.gov) is a web resource for collection, visualization and analysis of transcriptional regulons reconstructed by comparative genomics. We significantly expanded a reference collection of manually curated regulons we introduced earlier. RegPrecise 3.0 provides access to inferred regulatory interactions organized by phylogenetic, structural and functional properties. Taxonomy-specific collections include 781 TF regulogs inferred in more than 160 genomes representing 14 taxonomic groups of Bacteria. TF-specific collections include regulogs for a selected subset of 40 TFs reconstructed across more than 30 taxonomic lineages. Novel collections of regulons operated by RNA regulatory elements (riboswitches) include near 400 regulogs inferred in 24 bacterial lineages. RegPrecise 3.0 provides four classifications of the reference regulons implemented as controlled vocabularies: 55 TF protein families; 43 RNA motif families; ~150 biological processes or metabolic pathways; and ~200 effectors or environmental signals. Genome-wide visualization of regulatory networks and metabolic pathways covered by the reference regulons are available for all studied genomes. A separate section of RegPrecise 3.0 contains draft regulatory networks in 640 genomes obtained by an conservative propagation of the reference regulons to closely related genomes. RegPrecise 3.0 gives access to the transcriptional regulons reconstructed in

  8. 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

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

    Directory of Open Access Journals (Sweden)

    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.

  10. 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...

  11. 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

  12. Non-essential genes form the hubs of genome scale protein function and environmental gene expression networks in Salmonella enterica serovar Typhimurium

    DEFF Research Database (Denmark)

    Rosenkrantz, Jesper T.; Aarts, Henk; Abee, Tjakko

    2013-01-01

    Background: Salmonella Typhimurium is an important pathogen of human and animals. It shows a broad growth range and survives in harsh conditions. The aim of this study was to analyze transcriptional responses to a number of growth and stress conditions as well as the relationship of metabolic...... pathways and/or cell functions at the genome-scale-level by network analysis, and further to explore whether highly connected genes ( hubs) in these networks were essential for growth, stress adaptation and virulence. Results: De novo generated as well as published transcriptional data for 425 selected...... genes under a number of growth and stress conditions were used to construct a bipartite network connecting culture conditions and significantly regulated genes (transcriptional network). Also, a genome scale network was constructed for strain LT2. The latter connected genes with metabolic pathways...

  13. 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.

  14. 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.

  15. Genome-Scale Assessment of Age-Related DNA Methylation Changes in Mouse Spermatozoa

    Science.gov (United States)

    Kobayashi, Norio; Okae, Hiroaki; Hiura, Hitoshi; Chiba, Hatsune; Shirakata, Yoshiki; Hara, Kenshiro; Tanemura, Kentaro; Arima, Takahiro

    2016-01-01

    DNA methylation plays important roles in the production and functioning of spermatozoa. Recent studies have suggested that DNA methylation patterns in spermatozoa can change with age, but the regions susceptible to age-related methylation changes remain to be fully elucidated. In this study, we conducted genome-scale DNA methylation profiling of spermatozoa obtained from C57BL/6N mice at 8 weeks (8w), 18 weeks (18w) and 17 months of age (17m). There was no substantial difference in the global DNA methylation patterns between 18w and 17m samples except for a slight increase of methylation levels in long interspersed nuclear elements in the 17m samples. We found that maternally methylated imprinting control regions (mICRs) and spermatogenesis-related gene promoters had 5–10% higher methylation levels in 8w samples than in 18w or 17m samples. Analysis of individual sequence reads suggested that these regions were fully methylated (80–100%) in a subset of 8w spermatozoa. These regions are also known to be highly methylated in a subset of postnatal spermatogonia, which might be the source of the increased DNA methylation in 8w spermatozoa. Another possible source was contamination by somatic cells. Although we carefully purified the spermatozoa, it was difficult to completely exclude the possibility of somatic cell contamination. Further studies are needed to clarify the source of the small increase in DNA methylation in the 8w samples. Overall, our findings suggest that DNA methylation patterns in mouse spermatozoa are relatively stable throughout reproductive life. PMID:27880848

  16. Genome-scale co-evolutionary inference identifies functions and clients of bacterial Hsp90.

    Directory of Open Access Journals (Sweden)

    Maximilian O Press

    Full Text Available The molecular chaperone Hsp90 is essential in eukaryotes, in which it facilitates the folding of developmental regulators and signal transduction proteins known as Hsp90 clients. In contrast, Hsp90 is not essential in bacteria, and a broad characterization of its molecular and organismal function is lacking. To enable such characterization, we used a genome-scale phylogenetic analysis to identify genes that co-evolve with bacterial Hsp90. We find that genes whose gain and loss were coordinated with Hsp90 throughout bacterial evolution tended to function in flagellar assembly, chemotaxis, and bacterial secretion, suggesting that Hsp90 may aid assembly of protein complexes. To add to the limited set of known bacterial Hsp90 clients, we further developed a statistical method to predict putative clients. We validated our predictions by demonstrating that the flagellar protein FliN and the chemotaxis kinase CheA behaved as Hsp90 clients in Escherichia coli, confirming the predicted role of Hsp90 in chemotaxis and flagellar assembly. Furthermore, normal Hsp90 function is important for wild-type motility and/or chemotaxis in E. coli. This novel function of bacterial Hsp90 agreed with our subsequent finding that Hsp90 is associated with a preference for multiple habitats and may therefore face a complex selection regime. Taken together, our results reveal previously unknown functions of bacterial Hsp90 and open avenues for future experimental exploration by implicating Hsp90 in the assembly of membrane protein complexes and adaptation to novel environments.

  17. 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.

  18. Rapid genome-scale mapping of chromatin accessibility in tissue

    Science.gov (United States)

    2012-01-01

    Background The challenge in extracting genome-wide chromatin features from limiting clinical samples poses a significant hurdle in identification of regulatory marks that impact the physiological or pathological state. Current methods that identify nuclease accessible chromatin are reliant on large amounts of purified nuclei as starting material. This complicates analysis of trace clinical tissue samples that are often stored frozen. We have developed an alternative nuclease based procedure to bypass nuclear preparation to interrogate nuclease accessible regions in frozen tissue samples. Results Here we introduce a novel technique that specifically identifies Tissue Accessible Chromatin (TACh). The TACh method uses pulverized frozen tissue as starting material and employs one of the two robust endonucleases, Benzonase or Cyansase, which are fully active under a range of stringent conditions such as high levels of detergent and DTT. As a proof of principle we applied TACh to frozen mouse liver tissue. Combined with massive parallel sequencing TACh identifies accessible regions that are associated with euchromatic features and accessibility at transcriptional start sites correlates positively with levels of gene transcription. Accessible chromatin identified by TACh overlaps to a large extend with accessible chromatin identified by DNase I using nuclei purified from freshly isolated liver tissue as starting material. The similarities are most pronounced at highly accessible regions, whereas identification of less accessible regions tends to be more divergence between nucleases. Interestingly, we show that some of the differences between DNase I and Benzonase relate to their intrinsic sequence biases and accordingly accessibility of CpG islands is probed more efficiently using TACh. Conclusion The TACh methodology identifies accessible chromatin derived from frozen tissue samples. We propose that this simple, robust approach can be applied across a broad range of

  19. Rapid genome-scale mapping of chromatin accessibility in tissue

    Directory of Open Access Journals (Sweden)

    Grøntved Lars

    2012-06-01

    Full Text Available Abstract Background The challenge in extracting genome-wide chromatin features from limiting clinical samples poses a significant hurdle in identification of regulatory marks that impact the physiological or pathological state. Current methods that identify nuclease accessible chromatin are reliant on large amounts of purified nuclei as starting material. This complicates analysis of trace clinical tissue samples that are often stored frozen. We have developed an alternative nuclease based procedure to bypass nuclear preparation to interrogate nuclease accessible regions in frozen tissue samples. Results Here we introduce a novel technique that specifically identifies Tissue Accessible Chromatin (TACh. The TACh method uses pulverized frozen tissue as starting material and employs one of the two robust endonucleases, Benzonase or Cyansase, which are fully active under a range of stringent conditions such as high levels of detergent and DTT. As a proof of principle we applied TACh to frozen mouse liver tissue. Combined with massive parallel sequencing TACh identifies accessible regions that are associated with euchromatic features and accessibility at transcriptional start sites correlates positively with levels of gene transcription. Accessible chromatin identified by TACh overlaps to a large extend with accessible chromatin identified by DNase I using nuclei purified from freshly isolated liver tissue as starting material. The similarities are most pronounced at highly accessible regions, whereas identification of less accessible regions tends to be more divergence between nucleases. Interestingly, we show that some of the differences between DNase I and Benzonase relate to their intrinsic sequence biases and accordingly accessibility of CpG islands is probed more efficiently using TACh. Conclusion The TACh methodology identifies accessible chromatin derived from frozen tissue samples. We propose that this simple, robust approach can be applied

  20. A Genome-Scale Investigation of Incongruence in Culicidae Mosquitoes.

    Science.gov (United States)

    Wang, Yuyu; Zhou, Xiaofan; Yang, Ding; Rokas, Antonis

    2015-12-01

    Comparison of individual gene trees in several recent phylogenomic studies from diverse lineages has revealed a surprising amount of topological conflict or incongruence, but we still know relatively little about its distribution across the tree of life. To further our understanding of incongruence, the factors that contribute to it and how it can be ameliorated, we examined its distribution in a clade of 20 Culicidae mosquito species through the reconstruction and analysis of the phylogenetic histories of 2,007 groups of orthologous genes. Levels of incongruence were generally low, the three exceptions being the internodes concerned with the branching of Anopheles christyi, with the branching of the subgenus Anopheles as well as the already reported incongruence within the Anopheles gambiae species complex. Two of these incongruence events (A. gambiae species complex and A. christyi) are likely due to biological factors, whereas the third (subgenus Anopheles) is likely due to analytical factors. Similar to previous studies, the use of genes or internodes with high bootstrap support or internode certainty values, both of which were positively correlated with gene alignment length, substantially reduced the observed incongruence. However, the clade support values of the internodes concerned with the branching of the subgenus Anopheles as well as within the A. gambiae species complex remained very low. Based on these results, we infer that the prevalence of incongruence in Culicidae mosquitoes is generally low, that it likely stems from both analytical and biological factors, and that it can be ameliorated through the selection of genes with strong phylogenetic signal. More generally, selection of genes with strong phylogenetic signal may be a general empirical solution for reducing incongruence and increasing the robustness of inference in phylogenomic studies.

  1. Structural dynamics analysis

    Science.gov (United States)

    Housner, J. M.; Anderson, M.; Belvin, W.; Horner, G.

    1985-01-01

    Dynamic analysis of large space antenna systems must treat the deployment as well as vibration and control of the deployed antenna. Candidate computer programs for deployment dynamics, and issues and needs for future program developments are reviewed. Some results for mast and hoop deployment are also presented. Modeling of complex antenna geometry with conventional finite element methods and with repetitive exact elements is considered. Analytical comparisons with experimental results for a 15 meter hoop/column antenna revealed the importance of accurate structural properties including nonlinear joints. Slackening of cables in this antenna is also a consideration. The technology of designing actively damped structures through analytical optimization is discussed and results are presented.

  2. 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...

  3. 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.

  4. 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

  5. Structural Analysis Made 'NESSUSary'

    Science.gov (United States)

    2005-01-01

    Everywhere you look, chances are something that was designed and tested by a computer will be in plain view. Computers are now utilized to design and test just about everything imaginable, from automobiles and airplanes to bridges and boats, and elevators and escalators to streets and skyscrapers. Computer-design engineering first emerged in the 1970s, in the automobile and aerospace industries. Since computers were in their infancy, however, architects and engineers during the time were limited to producing only designs similar to hand-drafted drawings. (At the end of 1970s, a typical computer-aided design system was a 16-bit minicomputer with a price tag of $125,000.) Eventually, computers became more affordable and related software became more sophisticated, offering designers the "bells and whistles" to go beyond the limits of basic drafting and rendering, and venture into more skillful applications. One of the major advancements was the ability to test the objects being designed for the probability of failure. This advancement was especially important for the aerospace industry, where complicated and expensive structures are designed. The ability to perform reliability and risk assessment without using extensive hardware testing is critical to design and certification. In 1984, NASA initiated the Probabilistic Structural Analysis Methods (PSAM) project at Glenn Research Center to develop analysis methods and computer programs for the probabilistic structural analysis of select engine components for current Space Shuttle and future space propulsion systems. NASA envisioned that these methods and computational tools would play a critical role in establishing increased system performance and durability, and assist in structural system qualification and certification. Not only was the PSAM project beneficial to aerospace, it paved the way for a commercial risk- probability tool that is evaluating risks in diverse, down- to-Earth application

  6. 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...

  7. 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...

  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. 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.

  10. 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,...

  11. 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.

  12. 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.

  13. 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.

  14. Structural analysis of biodiversity.

    Science.gov (United States)

    Sirovich, Lawrence; Stoeckle, Mark Y; Zhang, Yu

    2010-02-24

    Large, recently-available genomic databases cover a wide range of life forms, suggesting opportunity for insights into genetic structure of biodiversity. In this study we refine our recently-described technique using indicator vectors to analyze and visualize nucleotide sequences. The indicator vector approach generates correlation matrices, dubbed Klee diagrams, which represent a novel way of assembling and viewing large genomic datasets. To explore its potential utility, here we apply the improved algorithm to a collection of almost 17,000 DNA barcode sequences covering 12 widely-separated animal taxa, demonstrating that indicator vectors for classification gave correct assignment in all 11,000 test cases. Indicator vector analysis revealed discontinuities corresponding to species- and higher-level taxonomic divisions, suggesting an efficient approach to classification of organisms from poorly-studied groups. As compared to standard distance metrics, indicator vectors preserve diagnostic character probabilities, enable automated classification of test sequences, and generate high-information density single-page displays. These results support application of indicator vectors for comparative analysis of large nucleotide data sets and raise prospect of gaining insight into broad-scale patterns in the genetic structure of biodiversity.

  15. 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

  16. 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.

  17. 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.

  18. Rapid Prototyping of Microbial Cell Factories via Genome-scale Engineering

    Science.gov (United States)

    Si, Tong; Xiao, Han; Zhao, Huimin

    2014-01-01

    Advances in reading, writing and editing genetic materials have greatly expanded our ability to reprogram biological systems at the resolution of a single nucleotide and on the scale of a whole genome. Such capacity has greatly accelerated the cycles of design, build and test to engineer microbes for efficient synthesis of fuels, chemicals and drugs. In this review, we summarize the emerging technologies that have been applied, or are potentially useful for genome-scale engineering in microbial systems. We will focus on the development of high-throughput methodologies, which may accelerate the prototyping of microbial cell factories. PMID:25450192

  19. Rapid prototyping of microbial cell factories via genome-scale engineering.

    Science.gov (United States)

    Si, Tong; Xiao, Han; Zhao, Huimin

    2015-11-15

    Advances in reading, writing and editing genetic materials have greatly expanded our ability to reprogram biological systems at the resolution of a single nucleotide and on the scale of a whole genome. Such capacity has greatly accelerated the cycles of design, build and test to engineer microbes for efficient synthesis of fuels, chemicals and drugs. In this review, we summarize the emerging technologies that have been applied, or are potentially useful for genome-scale engineering in microbial systems. We will focus on the development of high-throughput methodologies, which may accelerate the prototyping of microbial cell factories.

  20. Genome-scale cold stress response regulatory networks in ten Arabidopsis thaliana ecotypes

    DEFF Research Database (Denmark)

    Barah, Pankaj; Jayavelu, Naresh Doni; Rasmussen, Simon

    2013-01-01

    BACKGROUND: Low temperature leads to major crop losses every year. Although several studies have been conducted focusing on diversity of cold tolerance level in multiple phenotypically divergent Arabidopsis thaliana (A. thaliana) ecotypes, genome-scale molecular understanding is still lacking...... using Arabidopsis NimbleGen ATH6 microarrays. In total 6061 transcripts were significantly cold regulated (p ... be crucial for their local geographic adaptation to cold temperature. Additionally, since the approach presented here is general, it could be adapted to study networks regulating biological process in any biological systems....

  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. Informed Consent in Genome-Scale Research: What Do Prospective Participants Think?

    Science.gov (United States)

    Trinidad, Susan Brown; Fullerton, Stephanie M.; Bares, Julie M.; Jarvik, Gail P.; Larson, Eric B.; Burke, Wylie

    2012-01-01

    Background To promote effective genome-scale research, genomic and clinical data for large population samples must be collected, stored, and shared. Methods We conducted focus groups with 45 members of a Seattle-based integrated healthcare delivery system to learn about their views and expectations for informed consent in genome-scale studies. Results Participants viewed information about study purpose, aims, and how and by whom study data could be used to be at least as important as information about risks and possible harms. They generally supported a tiered consent approach for specific issues, including research purpose, data sharing, and access to individual research results. Participants expressed a continuum of opinions with respect to the acceptability of broad consent, ranging from completely acceptable to completely unacceptable. Older participants were more likely to view the consent process in relational – rather than contractual – terms, compared with younger participants. The majority of participants endorsed seeking study subjects’ permission regarding material changes in study purpose and data sharing. Conclusions Although this study sample was limited in terms of racial and socioeconomic diversity, our results suggest a strong positive interest in genomic research on the part of at least some prospective participants and indicate a need for increased public engagement, as well as strategies for ongoing communication with study participants. PMID:23493836

  3. 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.

  4. 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.

  5. 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.

  6. Genome-scale NAD(H/(+ availability patterns as a differentiating feature between Saccharomyces cerevisiae and Scheffersomyces stipitis in relation to fermentative metabolism.

    Directory of Open Access Journals (Sweden)

    Alejandro Acevedo

    Full Text Available Scheffersomyces stipitis is a yeast able to ferment pentoses to ethanol, unlike Saccharomyces cerevisiae, it does not present the so-called overflow phenomenon. Metabolic features characterizing the presence or not of this phenomenon have not been fully elucidated. This work proposes that genome-scale metabolic response to variations in NAD(H/(+ availability characterizes fermentative behavior in both yeasts. Thus, differentiating features in S. stipitis and S. cerevisiae were determined analyzing growth sensitivity response to changes in available reducing capacity in relation to ethanol production capacity and overall metabolic flux span. Using genome-scale constraint-based metabolic models, phenotypic phase planes and shadow price analyses, an excess of available reducing capacity for growth was found in S. cerevisiae at every metabolic phenotype where growth is limited by oxygen uptake, while in S. stipitis this was observed only for a subset of those phenotypes. Moreover, by using flux variability analysis, an increased metabolic flux span was found in S. cerevisiae at growth limited by oxygen uptake, while in S. stipitis flux span was invariant. Therefore, each yeast can be characterized by a significantly different metabolic response and flux span when growth is limited by oxygen uptake, both features suggesting a higher metabolic flexibility in S. cerevisiae. By applying an optimization-based approach on the genome-scale models, three single reaction deletions were found to generate in S. stipitis the reducing capacity availability pattern found in S. cerevisiae, two of them correspond to reactions involved in the overflow phenomenon. These results show a close relationship between the growth sensitivity response given by the metabolic network and fermentative behavior.

  7. Genome-Scale NAD(H/+) Availability Patterns as a Differentiating Feature between Saccharomyces cerevisiae and Scheffersomyces stipitis in Relation to Fermentative Metabolism

    Science.gov (United States)

    Acevedo, Alejandro; Aroca, German; Conejeros, Raul

    2014-01-01

    Scheffersomyces stipitis is a yeast able to ferment pentoses to ethanol, unlike Saccharomyces cerevisiae, it does not present the so-called overflow phenomenon. Metabolic features characterizing the presence or not of this phenomenon have not been fully elucidated. This work proposes that genome-scale metabolic response to variations in NAD(H/+) availability characterizes fermentative behavior in both yeasts. Thus, differentiating features in S. stipitis and S. cerevisiae were determined analyzing growth sensitivity response to changes in available reducing capacity in relation to ethanol production capacity and overall metabolic flux span. Using genome-scale constraint-based metabolic models, phenotypic phase planes and shadow price analyses, an excess of available reducing capacity for growth was found in S. cerevisiae at every metabolic phenotype where growth is limited by oxygen uptake, while in S. stipitis this was observed only for a subset of those phenotypes. Moreover, by using flux variability analysis, an increased metabolic flux span was found in S. cerevisiae at growth limited by oxygen uptake, while in S. stipitis flux span was invariant. Therefore, each yeast can be characterized by a significantly different metabolic response and flux span when growth is limited by oxygen uptake, both features suggesting a higher metabolic flexibility in S. cerevisiae. By applying an optimization-based approach on the genome-scale models, three single reaction deletions were found to generate in S. stipitis the reducing capacity availability pattern found in S. cerevisiae, two of them correspond to reactions involved in the overflow phenomenon. These results show a close relationship between the growth sensitivity response given by the metabolic network and fermentative behavior. PMID:24489927

  8. Candidate states of Helicobacter pylori's genome-scale metabolic network upon application of "loop law" thermodynamic constraints.

    Science.gov (United States)

    Price, Nathan D; Thiele, Ines; Palsson, Bernhard Ø

    2006-06-01

    Constraint-based modeling has proven to be a useful tool in the analysis of biochemical networks. To date, most studies in this field have focused on the use of linear constraints, resulting from mass balance and capacity constraints, which lead to the definition of convex solution spaces. One additional constraint arising out of thermodynamics is known as the "loop law" for reaction fluxes, which states that the net flux around a closed biochemical loop must be zero because no net thermodynamic driving force exists. The imposition of the loop-law can lead to nonconvex solution spaces making the analysis of the consequences of its imposition challenging. A four-step approach is developed here to apply the loop-law to study metabolic network properties: 1), determine linear equality constraints that are necessary (but not necessarily sufficient) for thermodynamic feasibility; 2), tighten V(max) and V(min) constraints to enclose the remaining nonconvex space; 3), uniformly sample the convex space that encloses the nonconvex space using standard Monte Carlo techniques; and 4), eliminate from the resulting set all solutions that violate the loop-law, leaving a subset of steady-state solutions. This subset of solutions represents a uniform random sample of the space that is defined by the additional imposition of the loop-law. This approach is used to evaluate the effect of imposing the loop-law on predicted candidate states of the genome-scale metabolic network of Helicobacter pylori.

  9. Structures and their analysis

    CERN Document Server

    Fuchs, Maurice Bernard

    2016-01-01

    Addressing structures, this book presents a classic discipline in a modern setting by combining illustrated examples with insights into the solutions. It is the fruit of the author’s many years of teaching the subject and of just as many years of research into the design of optimal structures. Although intended for an advanced level of instruction it has an undergraduate course at its core. Further, the book was written with the advantage of having massive computer power in the background, an aspect which changes the entire approach to many engineering disciplines and in particular to structures. This paradigm shift has dislodged the force (flexibility) method from its former prominence and paved the way for the displacement (stiffness) method, despite the multitude of linear equations it spawns. In this book, however, both methods are taught: the force method offers a perfect vehicle for understanding structural behavior, bearing in mind that it is the displacement method which does the heavy number crunch...

  10. ReacKnock: identifying reaction deletion strategies for microbial strain optimization based on genome-scale metabolic network.

    Directory of Open Access Journals (Sweden)

    Zixiang Xu

    Full Text Available Gene knockout has been used as a common strategy to improve microbial strains for producing chemicals. Several algorithms are available to predict the target reactions to be deleted. Most of them apply mixed integer bi-level linear programming (MIBLP based on metabolic networks, and use duality theory to transform bi-level optimization problem of large-scale MIBLP to single-level programming. However, the validity of the transformation was not proved. Solution of MIBLP depends on the structure of inner problem. If the inner problem is continuous, Karush-Kuhn-Tucker (KKT method can be used to reformulate the MIBLP to a single-level one. We adopt KKT technique in our algorithm ReacKnock to attack the intractable problem of the solution of MIBLP, demonstrated with the genome-scale metabolic network model of E. coli for producing various chemicals such as succinate, ethanol, threonine and etc. Compared to the previous methods, our algorithm is fast, stable and reliable to find the optimal solutions for all the chemical products tested, and able to provide all the alternative deletion strategies which lead to the same industrial objective.

  11. 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

  12. Structured Analysis - IDEF0

    DEFF Research Database (Denmark)

    Larsen, Michael Holm

    1999-01-01

    that require a modelling technique for the analysis, development, re-engineering, integration, or acquisition of information systems; and incorporate a systems or enterprise modelling technique into a business process analysis or software engineering methodology.This note is a summary of the Standard...

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

    Directory of Open Access Journals (Sweden)

    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.

  14. Genome-scale cold stress response regulatory networks in ten Arabidopsis thaliana ecotypes

    DEFF Research Database (Denmark)

    Barah, Pankaj; Jayavelu, Naresh Doni; Rasmussen, Simon

    2013-01-01

    BACKGROUND: Low temperature leads to major crop losses every year. Although several studies have been conducted focusing on diversity of cold tolerance level in multiple phenotypically divergent Arabidopsis thaliana (A. thaliana) ecotypes, genome-scale molecular understanding is still lacking...... using Arabidopsis NimbleGen ATH6 microarrays. In total 6061 transcripts were significantly cold regulated (p majority of the transcripts (75%) showed ecotype specific expression pattern. By using sequence data...... available from Arabidopsis thaliana 1001 genome project, we further investigated sequence polymorphisms in the core cold stress regulon genes. Significant numbers of non-synonymous amino acid changes were observed in the coding region of the CBF regulon genes. Considering the limited knowledge about...

  15. 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....

  16. 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....

  17. 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...

  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. 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...

  20. 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.

  1. 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...

  2. CFMDS: CUDA-based fast multidimensional scaling for genome-scale data.

    Science.gov (United States)

    Park, Sungin; Shin, Soo-Yong; Hwang, Kyu-Baek

    2012-01-01

    Multidimensional scaling (MDS) is a widely used approach to dimensionality reduction. It has been applied to feature selection and visualization in various areas. Among diverse MDS methods, the classical MDS is a simple and theoretically sound solution for projecting data objects onto a low dimensional space while preserving the original distances among them as much as possible. However, it is not trivial to apply it to genome-scale data (e.g., microarray gene expression profiles) on regular desktop computers, because of its high computational complexity. We implemented a highly-efficient software application, called CFMDS (CUDA-based Fast MultiDimensional Scaling), which produces an approximate solution of the classical MDS based on CUDA (compute unified device architecture) and the divide-and-conquer principle. CUDA is a parallel computing architecture exploiting the power of the GPU (graphics processing unit). The principle of divide-and-conquer was adopted for circumventing the small memory problem of usual graphics cards. Our application software has been tested on various benchmark datasets including microarrays and compared with the classical MDS algorithms implemented using C# and MATLAB. In our experiments, CFMDS was more than a hundred times faster for large data than such general solutions. Regarding the quality of dimensionality reduction, our approximate solutions were as good as those from the general solutions, as the Pearson's correlation coefficients between them were larger than 0.9. CFMDS is an expeditious solution for the data dimensionality reduction problem. It is especially useful for efficient processing of genome-scale data consisting of several thousands of objects in several minutes.

  3. Collapse Analysis of Timber Structures

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Sørensen, John Dalsgaard

    2008-01-01

    A probabilistic based collapse analysis has been performed for a glulam frame structure supporting the roof over the main court in a Norwegian sports centre. The robustness analysis is based on the framework for robustness analysis introduced in the Danish Code of Practice for the Safety...... of Structures and a probabilistic modelling of the timber material proposed in the Probabilistic Model Code (PMC) of the Joint Committee on Structural Safety (JCSS). Due to the framework in the Danish Code the timber structure has to be evaluated with respect to the following criteria where at least one shall...... be fulfilled: a) demonstrating that those parts of the structure essential for the safety only have little sensitivity with respect to unintentional loads and defects, or b) demonstrating a load case with „removal of a limited part of the structure‟ in order to document that an extensive failure...

  4. Thai Rhetorical Structure Analysis

    CERN Document Server

    Sinthupoun, Somnuk

    2010-01-01

    A rhetorical structure tree (RS tree) is a representation of discourse relations among elementary discourse units (EDUs). A RS tree is very useful to many text processing tasks employing relationships among EDUs such as text understanding, summarization, and question answering. Thai language with its unique linguistic characteristics requires a unique RS tree construction technique. This paper proposes an approach for Thai RS tree construction which consists of three major steps: EDU segmentation, Thai RS tree construction, and discourse relation (DR) identification. Two hidden markov models derived from grammatical rules are used to segment EDUs, a clustering technique with its similarity measure derived from Thai semantic rules is used to construct a Thai RS tree, and a decision tree whose features extracted from the rules is used to determine the DR between EDUs. The proposed technique is evaluated using three Thai corpora. The results show the Thai RS tree construction and the DR identification effectiven...

  5. Regularized Generalized Structured Component Analysis

    Science.gov (United States)

    Hwang, Heungsun

    2009-01-01

    Generalized structured component analysis (GSCA) has been proposed as a component-based approach to structural equation modeling. In practice, GSCA may suffer from multi-collinearity, i.e., high correlations among exogenous variables. GSCA has yet no remedy for this problem. Thus, a regularized extension of GSCA is proposed that integrates a ridge…

  6. Characterizing the optimal flux space of genome-scale metabolic reconstructions through modified latin-hypercube sampling.

    Science.gov (United States)

    Chaudhary, Neha; Tøndel, Kristin; Bhatnagar, Rakesh; dos Santos, Vítor A P Martins; Puchałka, Jacek

    2016-03-01

    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 novel drug targets and biotechnologically relevant pathways. The abundance of alternate flux profiles has led to the evolution of methods to explore the complete solution space aiming to increase the accuracy of predictions. Herein we present a novel, generic algorithm to characterize the entire flux space of GSMR upon application of FBA, leading to the optimal value of the objective (the optimal flux space). Our method employs Modified Latin-Hypercube Sampling (LHS) to effectively border the optimal space, followed by Principal Component Analysis (PCA) to identify and explain the major sources of variability within it. The approach was validated with the elementary mode analysis of a smaller network of Saccharomyces cerevisiae and applied to the GSMR of Pseudomonas aeruginosa PAO1 (iMO1086). It is shown to surpass the commonly used Monte Carlo Sampling (MCS) in providing a more uniform coverage for a much larger network in less number of samples. Results show that although many fluxes are identified as variable upon fixing the objective value, majority of the variability can be reduced to several main patterns arising from a few alternative pathways. In iMO1086, initial variability of 211 reactions could almost entirely be explained by 7 alternative pathway groups. These findings imply that the possibilities to reroute greater portions of flux may be limited within metabolic networks of bacteria. Furthermore, the optimal flux space is subject to change with environmental conditions. Our method may be a useful device to validate the predictions made by FBA-based tools, by describing the optimal flux space associated with these predictions, thus to improve them.

  7. Metabolic stasis in an ancient symbiosis: genome-scale metabolic networks from two Blattabacterium cuenoti strains, primary endosymbionts of cockroaches.

    Science.gov (United States)

    González-Domenech, Carmen Maria; Belda, Eugeni; Patiño-Navarrete, Rafael; Moya, Andrés; Peretó, Juli; Latorre, Amparo

    2012-01-18

    Cockroaches are terrestrial insects that strikingly eliminate waste nitrogen as ammonia instead of uric acid. Blattabacterium cuenoti (Mercier 1906) strains Bge and Pam are the obligate primary endosymbionts of the cockroaches Blattella germanica and Periplaneta americana, respectively. The genomes of both bacterial endosymbionts have recently been sequenced, making possible a genome-scale constraint-based reconstruction of their metabolic networks. The mathematical expression of a metabolic network and the subsequent quantitative studies of phenotypic features by Flux Balance Analysis (FBA) represent an efficient functional approach to these uncultivable bacteria. We report the metabolic models of Blattabacterium strains Bge (iCG238) and Pam (iCG230), comprising 296 and 289 biochemical reactions, associated with 238 and 230 genes, and 364 and 358 metabolites, respectively. Both models reflect both the striking similarities and the singularities of these microorganisms. FBA was used to analyze the properties, potential and limits of the models, assuming some environmental constraints such as aerobic conditions and the net production of ammonia from these bacterial systems, as has been experimentally observed. In addition, in silico simulations with the iCG238 model have enabled a set of carbon and nitrogen sources to be defined, which would also support a viable phenotype in terms of biomass production in the strain Pam, which lacks the first three steps of the tricarboxylic acid cycle. FBA reveals a metabolic condition that renders these enzymatic steps dispensable, thus offering a possible evolutionary explanation for their elimination. We also confirm, by computational simulations, the fragility of the metabolic networks and their host dependence. The minimized Blattabacterium metabolic networks are surprisingly similar in strains Bge and Pam, after 140 million years of evolution of these endosymbionts in separate cockroach lineages. FBA performed on the

  8. 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

  9. 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

  10. 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/.

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

    Directory of Open Access Journals (Sweden)

    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.

  12. 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.

  13. 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.

  14. AtPID: a genome-scale resource for genotype–phenotype associations in Arabidopsis

    Science.gov (United States)

    Lv, Qi; Lan, Yiheng; Shi, Yan; Wang, Huan; Pan, Xia; Li, Peng; Shi, Tieliu

    2017-01-01

    AtPID (Arabidopsis thaliana Protein Interactome Database, available at http://www.megabionet.org/atpid) is an integrated database resource for protein interaction network and functional annotation. In the past few years, we collected 5564 mutants with significant morphological alterations and manually curated them to 167 plant ontology (PO) morphology categories. These single/multiple-gene mutants were indexed and linked to 3919 genes. After integrated these genotype–phenotype associations with the comprehensive protein interaction network in AtPID, we developed a Naïve Bayes method and predicted 4457 novel high confidence gene-PO pairs with 1369 genes as the complement. Along with the accumulated novel data for protein interaction and functional annotation, and the updated visualization toolkits, we present a genome-scale resource for genotype–phenotype associations for Arabidopsis in AtPID 5.0. In our updated website, all the new genotype–phenotype associations from mutants, protein network, and the protein annotation information can be vividly displayed in a comprehensive network view, which will greatly enhance plant protein function and genotype–phenotype association studies in a systematical way. PMID:27899679

  15. 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.

  16. 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.

  17. 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.

  18. On the road to synthetic life: the minimal cell and genome-scale engineering.

    Science.gov (United States)

    Juhas, Mario

    2016-01-01

    Synthetic biology employs rational engineering principles to build biological systems from the libraries of standard, well characterized biological parts. Biological systems designed and built by synthetic biologists fulfill a plethora of useful purposes, ranging from better healthcare and energy production to biomanufacturing. Recent advancements in the synthesis, assembly and "booting-up" of synthetic genomes and in low and high-throughput genome engineering have paved the way for engineering on the genome-wide scale. One of the key goals of genome engineering is the construction of minimal genomes consisting solely of essential genes (genes indispensable for survival of living organisms). Besides serving as a toolbox to understand the universal principles of life, the cell encoded by minimal genome could be used to build a stringently controlled "cell factory" with a desired phenotype. This review provides an update on recent advances in the genome-scale engineering with particular emphasis on the engineering of minimal genomes. Furthermore, it presents an ongoing discussion to the scientific community for better suitability of minimal or robust cells for industrial applications.

  19. Genome-scale DNA sequence recognition by hybridization to short oligomers.

    Science.gov (United States)

    Milosavljević, A; Savković, S; Crkvenjakov, R; Salbego, D; Serrato, H; Kreuzer, H; Gemmell, A; Batus, S; Grujić, D; Carnahan, S; Tepavcević, J

    1996-01-01

    Recently developed hybridization technology (Drmanac et al. 1994) enables economical large-scale detection of short oligomers within DNA fragments. The newly developed recognition method (Milosavljević 1995b) enables comparison of lists of oligomers detected within DNA fragments against known DNA sequences. We here describe an experiment involving a set of 4,513 distinct genomic E.coli clones of average length 2kb, each hybridized with 636 randomly selected short oligomer probes. High hybridization signal with a particular probe was used as an indication of the presence of a complementary oligomer in the particular clone. For each clone, a list of oligomers with highest hybridization signals was compiled. The database consisting of 4,513 oligomer lists was then searched using known E.coli sequences as queries in an attempt to identify the clones that match the query sequence. Out of a total of 11 clones that were recognized at highest significance level by our method, 8 were single-pass sequenced from both ends. The single-pass sequenced ends were then compared against the query sequences. The sequence comparisons confirmed 7 out of the total of 8 examined recognitions. This experiment represents the first successful example of genome-scale sequence recognition based on hybridization data.

  20. Structural Analysis of Communication Development.

    Science.gov (United States)

    Conville, Richard L.

    This paper discusses the question of the legitimacy of applying structural analysis to actual human behavior and illustrates its legitimacy by using the reasoning in an essay by Paul Ricoeur. It then asks if the principles of communication development (obliqueness, exchange, and dying) derived from Helen Keller's experience of communication…

  1. Genome-scale data suggest reclassifications in the Leisingera-Phaeobacter cluster including proposals for Sedimentitalea gen. nov. and Pseudophaeobacter gen. nov.

    Science.gov (United States)

    Breider, Sven; Scheuner, Carmen; Schumann, Peter; Fiebig, Anne; Petersen, Jörn; Pradella, Silke; Klenk, Hans-Peter; Brinkhoff, Thorsten; Göker, Markus

    2014-01-01

    Earlier phylogenetic analyses of the marine Rhodobacteraceae (class Alphaproteobacteria) genera Leisingera and Phaeobacter indicated that neither genus might be monophyletic. We here used phylogenetic reconstruction from genome-scale data, MALDI-TOF mass-spectrometry analysis and a re-assessment of the phenotypic data from the literature to settle this matter, aiming at a reclassification of the two genera. Neither Phaeobacter nor Leisingera formed a clade in any of the phylogenetic analyses conducted. Rather, smaller monophyletic assemblages emerged, which were phenotypically more homogeneous, too. We thus propose the reclassification of Leisingera nanhaiensis as the type species of a new genus as Sedimentitalea nanhaiensis gen. nov., comb. nov., the reclassification of Phaeobacter arcticus and Phaeobacter leonis as Pseudophaeobacter arcticus gen. nov., comb. nov. and Pseudophaeobacter leonis comb. nov., and the reclassification of Phaeobacter aquaemixtae, Phaeobacter caeruleus, and Phaeobacter daeponensis as Leisingera aquaemixtae comb. nov., Leisingera caerulea comb. nov., and Leisingera daeponensis comb. nov. The genera Phaeobacter and Leisingera are accordingly emended.

  2. 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.

  3. Structural Analysis of Plate Based Tensegrity Structures

    DEFF Research Database (Denmark)

    Hald, Frederik; Kirkegaard, Poul Henning; Damkilde, Lars

    2013-01-01

    Plate tensegrity structures combine tension cables with a cross laminated timber plate and can then form e.g. a roof structure. The topology of plate tensegrity structures is investigated through a parametric investigation. Plate tensegrity structures are investigated, and a method...... for determination of the structures pre-stresses is used. A parametric investigation is performed to determine a more optimized form of the plate based tensegrity structure. Conclusions of the use of plate based tensegrity in civil engineering and further research areas are discussed....

  4. Structural Analysis of Plate Based Tensegrity Structures

    DEFF Research Database (Denmark)

    Hald, Frederik; Kirkegaard, Poul Henning; Damkilde, Lars

    2013-01-01

    Plate tensegrity structures combine tension cables with a cross laminated timber plate and can then form e.g. a roof structure. The topology of plate tensegrity structures is investigated through a parametric investigation. Plate tensegrity structures are investigated, and a method...... for determination of the structures pre-stresses is used. A parametric investigation is performed to determine a more optimized form of the plate based tensegrity structure. Conclusions of the use of plate based tensegrity in civil engineering and further research areas are discussed....

  5. 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...

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

    DEFF Research Database (Denmark)

    Cardoso, Joao; Andersen, Mikael Rørdam; Herrgard, Markus;

    2015-01-01

    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...

  7. Identification of genetic determinants of breast cancer immune phenotypes by integrative genome-scale analysis

    Science.gov (United States)

    Simeone, Ines; Anjum, Samreen; Mokrab, Younes; Bertucci, François; Finetti, Pascal; Curigliano, Giuseppe; Cerulo, Luigi; Tomei, Sara; Delogu, Lucia Gemma; Maccalli, Cristina; Miller, Lance D.; Ceccarelli, Michele

    2017-01-01

    ABSTRACT Cancer immunotherapy is revolutionizing the clinical management of several tumors, but has demonstrated limited activity in breast cancer. The development of more effective treatments is hindered by incomplete knowledge of the genetic determinant of immune responsiveness. To fill this gap, we mined copy number alteration, somatic mutation, and expression data from The Cancer Genome Atlas (TCGA). By using RNA-sequencing data from 1,004 breast cancers, we defined distinct immune phenotypes characterized by progressive expression of transcripts previously associated with immune-mediated rejection. The T helper 1 (Th-1) phenotype (ICR4), which also displays upregulation of immune-regulatory transcripts such as PDL1, PD1, FOXP3, IDO1, and CTLA4, was associated with prolonged patients' survival. We validated these findings in an independent meta-cohort of 1,954 breast cancer gene expression data. Chromosome segment 4q21, which includes genes encoding for the Th-1 chemokines CXCL9-11, was significantly amplified only in the immune favorable phenotype (ICR4). The mutation and neoantigen load progressively decreased from ICR4 to ICR1 but could not fully explain immune phenotypic differences. Mutations of TP53 were enriched in the immune favorable phenotype (ICR4). Conversely, the presence of MAP3K1 and MAP2K4 mutations were tightly associated with an immune-unfavorable phenotype (ICR1). Using both the TCGA and the validation dataset, the degree of MAPK deregulation segregates breast tumors according to their immune disposition. These findings suggest that mutation-driven perturbations of MAPK pathways are linked to the negative regulation of intratumoral immune response in breast cancer. Modulations of MAPK pathways could be experimentally tested to enhance breast cancer immune sensitivity. PMID:28344865

  8. Efficient Analysis of Complex Structures

    Science.gov (United States)

    Kapania, Rakesh K.

    2000-01-01

    Last various accomplishments achieved during this project are : (1) A Survey of Neural Network (NN) applications using MATLAB NN Toolbox on structural engineering especially on equivalent continuum models (Appendix A). (2) Application of NN and GAs to simulate and synthesize substructures: 1-D and 2-D beam problems (Appendix B). (3) Development of an equivalent plate-model analysis method (EPA) for static and vibration analysis of general trapezoidal built-up wing structures composed of skins, spars and ribs. Calculation of all sorts of test cases and comparison with measurements or FEA results. (Appendix C). (4) Basic work on using second order sensitivities on simulating wing modal response, discussion of sensitivity evaluation approaches, and some results (Appendix D). (5) Establishing a general methodology of simulating the modal responses by direct application of NN and by sensitivity techniques, in a design space composed of a number of design points. Comparison is made through examples using these two methods (Appendix E). (6) Establishing a general methodology of efficient analysis of complex wing structures by indirect application of NN: the NN-aided Equivalent Plate Analysis. Training of the Neural Networks for this purpose in several cases of design spaces, which can be applicable for actual design of complex wings (Appendix F).

  9. Marine Structural Analysis and Design

    Institute of Scientific and Technical Information of China (English)

    2015-01-01

    王迎光编上海交通大学出版社出版定价:$68.00内容简介:The material in this book has been continuously developed since the author started to teach Modern Ship Structural Design in the Department of Naval Architecture and Ocean Engineering of Shanghai Jiao Tong University in 2004.The subject of marine structural analysis and design is so broad that it is not possible to incorporate every aspect of this sub-

  10. Structural Analysis of Complex Networks

    CERN Document Server

    Dehmer, Matthias

    2011-01-01

    Filling a gap in literature, this self-contained book presents theoretical and application-oriented results that allow for a structural exploration of complex networks. The work focuses not only on classical graph-theoretic methods, but also demonstrates the usefulness of structural graph theory as a tool for solving interdisciplinary problems. Applications to biology, chemistry, linguistics, and data analysis are emphasized. The book is suitable for a broad, interdisciplinary readership of researchers, practitioners, and graduate students in discrete mathematics, statistics, computer science,

  11. Structured Functional Principal Component Analysis

    Science.gov (United States)

    Shou, Haochang; Zipunnikov, Vadim; Crainiceanu, Ciprian M.; Greven, Sonja

    2015-01-01

    Summary Motivated by modern observational studies, we introduce a class of functional models that expand nested and crossed designs. These models account for the natural inheritance of the correlation structures from sampling designs in studies where the fundamental unit is a function or image. Inference is based on functional quadratics and their relationship with the underlying covariance structure of the latent processes. A computationally fast and scalable estimation procedure is developed for high-dimensional data. Methods are used in applications including high-frequency accelerometer data for daily activity, pitch linguistic data for phonetic analysis, and EEG data for studying electrical brain activity during sleep. PMID:25327216

  12. 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.

  13. 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.

  14. ToMI-FBA: A genome-scale metabolic flux based algorithm to select optimum hosts and media formulations for expressing pathways of interest

    Directory of Open Access Journals (Sweden)

    Hadi Nazem-Bokaee

    2015-09-01

    Full Text Available The Total Membrane Influx constrained Flux Balance Analysis (ToMI-FBA algorithm was developed in this research as a new tool to help researchers decide which microbial host and medium formulation are optimal for expressing a new metabolic pathway. ToMI-FBA relies on genome-scale metabolic flux modeling and a novel in silico cell membrane influx constraint that specifies the flux of atoms (not molecules into the cell through all possible membrane transporters. The ToMI constraint is constructed through the addition of an extra row and column to the stoichiometric matrix of a genome-scale metabolic flux model. In this research, the mathematical formulation of the ToMI constraint is given along with four case studies that demonstrate its usefulness. In Case Study 1, ToMI-FBA returned an optimal culture medium formulation for the production of isobutanol from Bacillus subtilis. Significant levels of L-valine were recommended to optimize production, and this result has been observed experimentally. In Case Study 2, it is demonstrated how the carbon to nitrogen uptake ratio can be specified as an additional ToMI-FBA constraint. This was investigated for maximizing medium chain length polyhydroxyalkanoates (mcl-PHA production from Pseudomonas putida KT2440. In Case Study 3, ToMI-FBA revealed a strategy of adding cellobiose as a means to increase ethanol selectivity during the stationary growth phase of Clostridium acetobutylicum ATCC 824. This strategy was also validated experimentally. Finally, in Case Study 4, B. subtilis was identified as a superior host to Escherichia coli, Saccharomyces cerevisiae, and Synechocystis PCC6803 for the production of artemisinate.

  15. 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

  16. 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

  17. LocateP: Genome-scale subcellular-location predictor for bacterial proteins

    Directory of Open Access Journals (Sweden)

    Zhou Miaomiao

    2008-03-01

    Full Text Available Abstract Background In the past decades, various protein subcellular-location (SCL predictors have been developed. Most of these predictors, like TMHMM 2.0, SignalP 3.0, PrediSi and Phobius, aim at the identification of one or a few SCLs, whereas others such as CELLO and Psortb.v.2.0 aim at a broader classification. Although these tools and pipelines can achieve a high precision in the accurate prediction of signal peptides and transmembrane helices, they have a much lower accuracy when other sequence characteristics are concerned. For instance, it proved notoriously difficult to identify the fate of proteins carrying a putative type I signal peptidase (SPIase cleavage site, as many of those proteins are retained in the cell membrane as N-terminally anchored membrane proteins. Moreover, most of the SCL classifiers are based on the classification of the Swiss-Prot database and consequently inherited the inconsistency of that SCL classification. As accurate and detailed SCL prediction on a genome scale is highly desired by experimental researchers, we decided to construct a new SCL prediction pipeline: LocateP. Results LocateP combines many of the existing high-precision SCL identifiers with our own newly developed identifiers for specific SCLs. The LocateP pipeline was designed such that it mimics protein targeting and secretion processes. It distinguishes 7 different SCLs within Gram-positive bacteria: intracellular, multi-transmembrane, N-terminally membrane anchored, C-terminally membrane anchored, lipid-anchored, LPxTG-type cell-wall anchored, and secreted/released proteins. Moreover, it distinguishes pathways for Sec- or Tat-dependent secretion and alternative secretion of bacteriocin-like proteins. The pipeline was tested on data sets extracted from literature, including experimental proteomics studies. The tests showed that LocateP performs as well as, or even slightly better than other SCL predictors for some locations and outperforms

  18. Soil Retaining Structures: Development of models for structural analysis

    NARCIS (Netherlands)

    Bakker, K.J.

    2000-01-01

    The topic of this thesis is the development of models for the structural analysis of soil retaining structures. The soil retaining structures being looked at are; block revetments, flexible retaining walls and bored tunnels in soft soil. Within this context typical structural behavior of these struc

  19. 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.

  20. 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

  1. Analysis of Pumphouse RCC Frame Structure for Soil Structure Interaction

    Directory of Open Access Journals (Sweden)

    Mr A.S. Thombare

    2016-06-01

    Full Text Available When structure is built on ground some elements of structure are direct contact with soil. When loads are applied on structure internal forces are developed in both the structure as well as in soil. It results in deformation of both the components which are independent to each other. This are called soil structure interaction. The analysis is done by using (Bentley STAAD.Pro V8i Version 2007 software. The analysis carried out been pump house structure R.C.C. frame structure find out shear force Z direction fixed support and fixed but support for different soil. It concluded that soil structure interaction more affected on fixed base. So overcome the effects of the soil structure interaction on the soft soil, it is important to design the structure to standard loading condition and interaction forces. Thus here concluded that pump house building should be design resist the maximum shear force in fixed base

  2. Analysis and prediction of nutritional requirements using structural properties of metabolic networks and support vector machines.

    Science.gov (United States)

    Tamura, Takeyuki; Christian, Nils; Takemoto, Kazuhiro; Ebenhöh, Oliver; Akutsu, Tatsuya

    2010-01-01

    Properties of graph representation of genome scale metabolic networks have been extensively studied. However, the relationship between these structural properties and functional properties of the networks are still very unclear. In this paper, we focus on nutritional requirements of organisms as a functional property and study the relationship with structural properties of a graph representation of metabolic networks. In order to examine the relationship, we study to what extent the nutritional requirements can be predicted by using support vector machines from structural properties, which include degree exponent, edge density, clustering coefficient, degree centrality, closeness centrality, betweenness centrality and eigenvector centrality. Furthermore, we study which properties are influential to the nutritional requirements.

  3. Robustness Analysis of Kinetic Structures

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Sørensen, John Dalsgaard

    2009-01-01

    The present paper considers robustness of kinetic structures. Robustness of structures has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. Especially for these types of structural syst...... systems, it is of interest to investigate how robust the structures are, or what happens if a structural element is added to or removed from the original structure. The present paper discusses this issue for kinetic structures in architecture....

  4. An effective method for controlling false discovery and false nondiscovery rates in genome-scale RNAi screens.

    Science.gov (United States)

    Zhang, Xiaohua Douglas

    2010-10-01

    In most genome-scale RNA interference (RNAi) screens, the ultimate goal is to select siRNAs with a large inhibition or activation effect. The selection of hits typically requires statistical control of 2 errors: false positives and false negatives. Traditional methods of controlling false positives and false negatives do not take into account the important feature in RNAi screens: many small-interfering RNAs (siRNAs) may have very small but real nonzero average effects on the measured response and thus cannot allow us to effectively control false positives and false negatives. To address for deficiencies in the application of traditional approaches in RNAi screening, the author proposes a new method for controlling false positives and false negatives in RNAi high-throughput screens. The false negatives are statistically controlled through a false-negative rate (FNR) or false nondiscovery rate (FNDR). FNR is the proportion of false negatives among all siRNAs examined, whereas FNDR is the proportion of false negatives among declared nonhits. The author also proposes new concepts, q*-value and p*-value, to control FNR and FNDR, respectively. The proposed method should have broad utility for hit selection in which one needs to control both false discovery and false nondiscovery rates in genome-scale RNAi screens in a robust manner.

  5. A genome-scale CRISPR-Cas9 screening method for protein stability reveals novel regulators of Cdc25A.

    Science.gov (United States)

    Wu, Yuanzhong; Zhou, Liwen; Wang, Xin; Lu, Jinping; Zhang, Ruhua; Liang, Xiaoting; Wang, Li; Deng, Wuguo; Zeng, Yi-Xin; Huang, Haojie; Kang, Tiebang

    2016-01-01

    The regulation of stability is particularly crucial for unstable proteins in cells. However, a convenient and unbiased method of identifying regulators of protein stability remains to be developed. Recently, a genome-scale CRISPR-Cas9 library has been established as a genetic tool to mediate loss-of-function screening. Here, we developed a protein stability regulators screening assay (Pro-SRSA) by combining the whole-genome CRISPR-Cas9 library with a dual-fluorescence-based protein stability reporter and high-throughput sequencing to screen for regulators of protein stability. Using Cdc25A as an example, Cul4B-DDB1(DCAF8) was identified as a new E3 ligase for Cdc25A. Moreover, the acetylation of Cdc25A at lysine 150, which was acetylated by p300/CBP and deacetylated by HDAC3, prevented the ubiquitin-mediated degradation of Cdc25A by the proteasome. This is the first study to report that acetylation, as a novel posttranslational modification, modulates Cdc25A stability, and we suggest that this unbiased CRISPR-Cas9 screening method at the genome scale may be widely used to globally identify regulators of protein stability.

  6. Genome-scale prediction of proteins with long intrinsically disordered regions.

    Science.gov (United States)

    Peng, Zhenling; Mizianty, Marcin J; Kurgan, Lukasz

    2014-01-01

    Proteins with long disordered regions (LDRs), defined as having 30 or more consecutive disordered residues, are abundant in eukaryotes, and these regions are recognized as a distinct class of biologically functional domains. LDRs facilitate various cellular functions and are important for target selection in structural genomics. Motivated by the lack of methods that directly predict proteins with LDRs, we designed Super-fast predictor of proteins with Long Intrinsically DisordERed regions (SLIDER). SLIDER utilizes logistic regression that takes an empirically chosen set of numerical features, which consider selected physicochemical properties of amino acids, sequence complexity, and amino acid composition, as its inputs. Empirical tests show that SLIDER offers competitive predictive performance combined with low computational cost. It outperforms, by at least a modest margin, a comprehensive set of modern disorder predictors (that can indirectly predict LDRs) and is 16 times faster compared to the best currently available disorder predictor. Utilizing our time-efficient predictor, we characterized abundance and functional roles of proteins with LDRs over 110 eukaryotic proteomes. Similar to related studies, we found that eukaryotes have many (on average 30.3%) proteins with LDRs with majority of proteomes having between 25 and 40%, where higher abundance is characteristic to proteomes that have larger proteins. Our first-of-its-kind large-scale functional analysis shows that these proteins are enriched in a number of cellular functions and processes including certain binding events, regulation of catalytic activities, cellular component organization, biogenesis, biological regulation, and some metabolic and developmental processes. A webserver that implements SLIDER is available at http://biomine.ece.ualberta.ca/SLIDER/. Copyright © 2013 Wiley Periodicals, Inc.

  7. Design and analysis of heliostat support structure

    Energy Technology Data Exchange (ETDEWEB)

    Zang Chuncheng; Wang Zhifeng [Inst. of Electrical Engineering, CAS, BJ (China); Liu Xiaobing; Zhang Xiliang [Himin Solar Energy Group Co. Ltd, Dezhou, SD (China); Wang Yanzhong [Beijing Univ. of Aeronautics and Astronautics, BJ (China)

    2008-07-01

    The design method of the heliostat support structure with the aim of reducing the cost maximally is described in this paper. In order to guarantee the strength, stiffness and stability of the structure, dynamic performance and static performance including internal stress and distortion are analyzed by means of VSAP (Visual Structural Analysis Program) finite element computational software. Then the support structure is optimized on the basis of the analysis. (orig.)

  8. Genome-scale data suggest reclassifications in the Leisingera-Phaeobacter cluster including proposals for Sedimentitalea gen. nov. and Pseudophaeobacter gen. nov.

    Directory of Open Access Journals (Sweden)

    Sven eBreider

    2014-08-01

    Full Text Available Earlier phylogenetic analyses of the marine Rhodobacteraceae (class Alphaproteobacteria genera Leisingera and Phaeobacter indicated that neither genus might be monophyletic. We here used phylogenetic reconstruction from genome-scale data, MALDI-TOF mass-spectrometry analysis and a re-assessment of the phenotypic data from the literature to settle this matter, aiming at a reclassification of the two genera. Neither Phaeobacter nor Leisingera formed a clade in any of the phylogenetic analyses conducted. Rather, smaller monophyletic assemblages emerged, which were phenotypically more homogeneous, too. We thus propose the reclassification of Leisingera nanhaiensis as the type species of a new genus as Sedimentitalea nanhaiensis gen. nov., comb. nov., the reclassification of Phaeobacter arcticus and Phaeobacter leonis as Pseudophaeobacter arcticus gen. nov., comb. nov. and Pseudophaeobacter leonis comb. nov., and the reclassification of Phaeobacter aquaemixtae, Phaeobacter caeruleus and Phaeobacter daeponensis as Leisingera aquaemixtae comb. nov., Leisingera caerulea comb. nov. and Leisingera daeponensis comb. nov. The genera Phaeobacter and Leisingera are accordingly emended.

  9. Structural analysis considerations for wind turbine blades

    Science.gov (United States)

    Spera, D. A.

    1979-01-01

    Approaches to the structural analysis of wind turbine blade designs are reviewed. Specifications and materials data are discussed along with the analysis of vibrations, loads, stresses, and failure modes.

  10. Analysis of piezoelectric structures and devices

    CERN Document Server

    Chen, Weiqiu; Wang, Ji

    2013-01-01

    This edited work covers piezoelectric materials in the form of beams, plates, shells, and other structural components in modern devices and structures. Applications are frequency control and detection functions in resonators, sensors, actuators, oscillations, and other smart and intelligent structures. The contributions cover novel methods for the analysis of piezoelectric structures including wave propagation, high frequency vibration, material characterization, and optimization of structures. Understanding of these methods is increasingly important in the design and modelling of next generat

  11. Robustness Analysis of Kinetic Structures

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Sørensen, John Dalsgaard

    2009-01-01

    Kinetic structures in architecture follows a new trend which is emerging in responsive architecture coined by Nicholas Negroponte when he proposed that architecture may benefit from the integration of computing power into built spaces and structures, and that better performing, more rational...

  12. Robustness Analysis of Kinetic Structures

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Sørensen, John Dalsgaard

    2009-01-01

    Kinetic structures in architecture follows a new trend which is emerging in responsive architecture coined by Nicholas Negroponte when he proposed that architecture may benefit from the integration of computing power into built spaces and structures, and that better performing, more rational...

  13. COMPARATIVE ANALYSIS OF STEEL AND ALUMINUM STRUCTURES

    Directory of Open Access Journals (Sweden)

    Josip Peko

    2016-12-01

    Full Text Available This study examined steel and aluminum variants of modern exhibition structures in which the main design requirements include low weight (increased span/depth ratio, transportation, and construction and durability (resistance to corrosion. This included a design situation in which the structural application of aluminum alloys provided an extremely convenient and practical solution. Viability of an aluminum structure depends on several factors and requires a detailed analysis. The overall conclusion of the study indicated that aluminum can be used as a structural material and as a viable alternative to steel for Croatian snow and wind load values and evidently in cases in which positive properties of aluminum are required for structural design. Furthermore, a structural fire analysis was conducted for an aluminum variant structure by using a zone model for realistic fire analysis. The results suggested that passive fire protection for the main structural members was not required in the event of areal fire with duration of 60 min.

  14. 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.

  15. NASA Structural Analysis System (NASTRAN)

    Science.gov (United States)

    Purves, L.

    1991-01-01

    Program aids in structural design of wide range of objects, from high-impact printer parts to turbine engine blades, and fully validated. Since source code included, NASTRAN modified or enhanced for new applications.

  16. The Intelligent Use of Structural Analysis.

    Science.gov (United States)

    Grierson, Donald E.

    1983-01-01

    Discusses the use of sensitivity analysis in structural design computation. Such analysis can predict how response quantities will vary with given design changes. In addition, it can help student engineers better understand why and when particular structural analyses are or should be conducted. (JN)

  17. Nonlinear structural analysis using integrated force method

    Indian Academy of Sciences (India)

    N R B Krishnam Raju; J Nagabhushanam

    2000-08-01

    Though the use of the integrated force method for linear investigations is well-recognised, no efforts were made to extend this method to nonlinear structural analysis. This paper presents the attempts to use this method for analysing nonlinear structures. General formulation of nonlinear structural analysis is given. Typically highly nonlinear bench-mark problems are considered. The characteristic matrices of the elements used in these problems are developed and later these structures are analysed. The results of the analysis are compared with the results of the displacement method. It has been demonstrated that the integrated force method is equally viable and efficient as compared to the displacement method.

  18. LISA: a linear structured system analysis program

    OpenAIRE

    Martinez-Martinez, Sinuhé; Mader, Theodor; Boukhobza, Taha; Hamelin, Frédéric

    2007-01-01

    International audience; In this paper the program LISA is presented. LISA is a flexible and portable program which has been developed to analyse structural properties of large scale linear and bilinear structured systems. More precisely, the program LISA contains programmed algorithms which allow us to apply recent results in the analysis of structured systems to some particular cases.

  19. Fourier Analysis and Structure Determination--Part III: X-ray Crystal Structure Analysis.

    Science.gov (United States)

    Chesick, John P.

    1989-01-01

    Discussed is single crystal X-ray crystal structure analysis. A common link between the NMR imaging and the traditional X-ray crystal structure analysis is reported. Claims that comparisons aid in the understanding of both techniques. (MVL)

  20. Structural Analysis of the Upper Internal Structure in PGSFR

    Energy Technology Data Exchange (ETDEWEB)

    Kim, S. H.; Koo, G. H. [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2014-10-15

    The upper internal structure (UIS) is a package of hardware suspended from the rotating plug to about 20 cm above the core assemblies. The functions of the UIS are to support shroud tubes containing the primary and secondary control rod drivelines and preserve critical alignments between these drivelines and the core lattice, under normal and off-normal conditions. In addition, the UIS produces sufficient coolant mixing to mitigate thermal transients to downstream components and provides an opening for the In-Vessel transfer machine to access inner core positions without interfacing with the control rod drive lines and the upper core instrumentation package. The radial position of the shroud tube is fixed by three horizontal guide plates and the lower guide plate is close to the core assemblies and is perforated to permit most of the core effluent to reach the region between guide plates. In this study, the primary stress analysis for dead weight was carried out and the thermal stress analysis considering the coolant temperature around the UIS was performed. In addition, the mode characteristics of the structure by the natural frequency analysis were evaluated. The structural analysis model is developed to evaluate the structural integrity of the UIS. The primary stress analysis, the thermal stress analysis and the natural frequency analysis for the UIS are performed, and the maximum stresses and displacements are evaluated. From the analysis results, it is confirmed that the large local stresses don't occur near the holes and through the wall thicknesses of the structure. In addition, the maximum temperature of the UIS is calculated as 545 .deg. C from the thermal analysis and the structure should be evaluated by the ASME design rules at a high temperature. In the future, the more detailed design will be performed by the high temperature evaluation procedure according to the ASME SEC. III, Div.5.

  1. STATIC ANALYSIS OF CABLE STRUCTURE

    Institute of Scientific and Technical Information of China (English)

    HUANG Yan; LAN Wei-ren

    2006-01-01

    Based on the nonlinear geometric relation between strain and displacement for flexible cable, the equilibrium equation under self-weight and influence of temperature was established and an analytical solution of displacement and tension distribution defined in Eulerian coordinate system was accurately obtained. The nonlinear algebraic equations caused by cable structure were solved directly using the modified Powell hybrid algorithm with high precision routine DNEQNE of Fortran. For example, a cable structure consisting of three cables jointly supported by a vertical spring and all the other ends fixed was calculated and compared with various methods by other scholars.

  2. FINITE ELEMENT ANALYSIS OF STRUCTURES

    Directory of Open Access Journals (Sweden)

    PECINGINA OLIMPIA-MIOARA

    2015-05-01

    Full Text Available The application of finite element method is analytical when solutions can not be applied for deeper study analyzes static, dynamic or other types of requirements in different points of the structures .In practice it is necessary to know the behavior of the structure or certain parts components of the machine under the influence of certain factors static and dynamic . The application of finite element in the optimization of components leads to economic growth , to increase reliability and durability organs studied, thus the machine itself.

  3. Probabilistic structural analysis by extremum methods

    Science.gov (United States)

    Nafday, Avinash M.

    1990-01-01

    The objective is to demonstrate discrete extremum methods of structural analysis as a tool for structural system reliability evaluation. Specifically, linear and multiobjective linear programming models for analysis of rigid plastic frames under proportional and multiparametric loadings, respectively, are considered. Kinematic and static approaches for analysis form a primal-dual pair in each of these models and have a polyhedral format. Duality relations link extreme points and hyperplanes of these polyhedra and lead naturally to dual methods for system reliability evaluation.

  4. Analysis of composite structural elements

    Directory of Open Access Journals (Sweden)

    A. Baier

    2010-12-01

    Full Text Available Purpose: The themes of the study are composite structural components. For this purpose have been designed and built several research positions.Design/methodology/approach: Using different structural materials to build new device components requires multiple tests of the components. Research posts were designed in the advanced graphical program CAx Siemens NX 7.5. Analysed samples were made from the glass fibre, aramid and carbon of various weights. Due to the specific use of composite materials it focuses on the elements in the form of plates and flat bars. For the examination of experimental strain gauge technique was used bead, the force sensor and displacement sensor. The experimental methods were compared with computer simulation using the FEM.Findings: The aim of this study was to determine the basic material constants and a comparison of the experimental method and the method of computer simulation.Research limitations/implications: Change the number of layers and how to connect the laminate with the steel plate changes mechanical properties of the structural component.Practical implications: The ultimate result will be knowledge on the different forms of laminates, such as material properties, the stresses in all layers, strain and comparing the results obtained by two methods.Originality/value: The expected outcome of the study will be the composition and method of joining composite laminate with a steel plate to the possible application in the repair and construction of structural elements of freight wagons.

  5. Structural analysis consultation using artificial intelligence

    Science.gov (United States)

    Melosh, R. J.; Marcal, P. V.; Berke, L.

    1978-01-01

    The primary goal of consultation is definition of the best strategy to deal with a structural engineering analysis objective. The knowledge base to meet the need is designed to identify the type of numerical analysis, the needed modeling detail, and specific analysis data required. Decisions are constructed on the basis of the data in the knowledge base - material behavior, relations between geometry and structural behavior, measures of the importance of time and temperature changes - and user supplied specifics characteristics of the spectrum of analysis types, the relation between accuracy and model detail on the structure, its mechanical loadings, and its temperature states. Existing software demonstrated the feasibility of the approach, encompassing the 36 analysis classes spanning nonlinear, temperature affected, incremental analyses which track the behavior of structural systems.

  6. Complex network perspective on structure and function of Staphylococcus aureus metabolic network

    Indian Academy of Sciences (India)

    L Ying; D W Ding

    2013-02-01

    With remarkable advances in reconstruction of genome-scale metabolic networks, uncovering complex network structure and function from these networks is becoming one of the most important topics in system biology. This work aims at studying the structure and function of Staphylococcus aureus (S. aureus) metabolic network by complex network methods. We first generated a metabolite graph from the recently reconstructed high-quality S. aureus metabolic network model. Then, based on `bow tie' structure character, we explain and discuss the global structure of S. aureus metabolic network. The functional significance, global structural properties, modularity and centrality analysis of giant strong component in S. aureus metabolic networks are studied.

  7. Robustness Analysis of Timber Truss Structure

    DEFF Research Database (Denmark)

    Rajčić, Vlatka; Čizmar, Dean; Kirkegaard, Poul Henning

    2010-01-01

    The present paper discusses robustness of structures in general and the robustness requirements given in the codes. Robustness of timber structures is also an issues as this is closely related to Working group 3 (Robustness of systems) of the COST E55 project. Finally, an example of a robustness...... evaluation of a widespan timber truss structure is presented. This structure was built few years ago near Zagreb and has a span of 45m. Reliability analysis of the main members and the system is conducted and based on this a robustness analysis is preformed....

  8. Reconstruction and modeling protein translocation and compartmentalization in Escherichia coli at the genome-scale

    DEFF Research Database (Denmark)

    Liu, Joanne K.; O’Brien, Edward J.; Lerman, Joshua A.

    2014-01-01

    translocation pathways, (2) assignment of all cellular proteins to one of four compartments (cytoplasm, inner membrane, periplasm, and outer membrane) and a translocation pathway, (3) experimentally determined translocase catalytic and porin diffusion rates, and (4) a novel membrane constraint that reflects......Background: Membranes play a crucial role in cellular functions. Membranes provide a physical barrier, control the trafficking of substances entering and leaving the cell, and are a major determinant of cellular ultra-structure. In addition, components embedded within the membrane participate...... in cell signaling, energy transduction, and other critical cellular functions. All these processes must share the limited space in the membrane; thus it represents a notable constraint on cellular functions. Membrane- and location-based processes have not yet been reconstructed and explicitly integrated...

  9. Thermal and structural analysis of Hermes

    Science.gov (United States)

    Petiau, C.

    1989-08-01

    After a brief recap of Hermes TPS and structure principles, we present the organization of thermal and structural analysis of the Hermes project, and we describe the way to resolve the problems of connections between calculations performed by the different Hermes partners. We describe in detail the interactions between the general model of TPS, used for global dimensioning of insulation, and refined thermal models giving an accurate temperature map inside details of "hot" and "cold" structures. The organization for structural analysis is based on a finite element general model which supports preliminary design, loads and vibration analyses. Boundary conditions for refined subpart analyses are cut to size, into the general model by a super element technique. This process involves the use by all partners of efficient computer codes, in the field of structural analysis and optimization integrated with CAD; for this Dassault proposes as a reference: the CATIA-ELFINI system.

  10. Dynamic analysis and design of offshore structures

    CERN Document Server

    Chandrasekaran, Srinivasan

    2015-01-01

    This book  attempts to provide readers with an overall idea of various types of offshore platform geometries. It covers the various environmental loads encountered by these structures, a detailed description of the fundamentals of structural dynamics in a class-room style, estimate of damping in offshore structures and their applications in the preliminary analysis and design. Basic concepts of structural dynamics are emphasized through simple illustrative examples and exercises. Design methodologies and guidelines, which are FORM based concepts are explained through a few applied example structures. Each chapter also has tutorials and exercises for self-learning. A dedicated chapter on stochastic dynamics will help the students to extend the basic concepts of structural dynamics to this advanced domain of research. Hydrodynamic response of offshore structures with perforated members is one of the recent research applications, which is found to be one of the effective manner of retrofitting offshore structur...

  11. Semantic Antinomies and Deep Structure Analysis

    Science.gov (United States)

    Zuber, Ryszard

    1975-01-01

    This article discusses constructions known as semantic antinomies, that is, the paradoxical results of false presuppositions, and how they can be dealt with by means of deep structure analysis. See FL 508 186 for availability. (CLK)

  12. Semantic Antinomies and Deep Structure Analysis

    Science.gov (United States)

    Zuber, Ryszard

    1975-01-01

    This article discusses constructions known as semantic antinomies, that is, the paradoxical results of false presuppositions, and how they can be dealt with by means of deep structure analysis. See FL 508 186 for availability. (CLK)

  13. Counting and Correcting Thermodynamically Infeasible Flux Cycles in Genome-Scale Metabolic Networks

    Directory of Open Access Journals (Sweden)

    Andrea De Martino

    2013-10-01

    Full Text Available Thermodynamics constrains the flow of matter in a reaction network to occur through routes along which the Gibbs energy decreases, implying that viable steady-state flux patterns should be void of closed reaction cycles. Identifying and removing cycles in large reaction networks can unfortunately be a highly challenging task from a computational viewpoint. We propose here a method that accomplishes it by combining a relaxation algorithm and a Monte Carlo procedure to detect loops, with ad hoc rules (discussed in detail to eliminate them. As test cases, we tackle (a the problem of identifying infeasible cycles in the E. coli metabolic network and (b the problem of correcting thermodynamic infeasibilities in the Flux-Balance-Analysis solutions for 15 human cell-type-specific metabolic networks. Results for (a are compared with previous analyses of the same issue, while results for (b are weighed against alternative methods to retrieve thermodynamically viable flux patterns based on minimizing specific global quantities. Our method, on the one hand, outperforms previous techniques and, on the other, corrects loopy solutions to Flux Balance Analysis. As a byproduct, it also turns out to be able to reveal possible inconsistencies in model reconstructions.

  14. Structural Dynamics and Data Analysis

    Science.gov (United States)

    Luthman, Briana L.

    2013-01-01

    This project consists of two parts, the first will be the post-flight analysis of data from a Delta IV launch vehicle, and the second will be a Finite Element Analysis of a CubeSat. Shock and vibration data was collected on WGS-5 (Wideband Global SATCOM- 5) which was launched on a Delta IV launch vehicle. Using CAM (CAlculation with Matrices) software, the data is to be plotted into Time History, Shock Response Spectrum, and SPL (Sound Pressure Level) curves. In this format the data is to be reviewed and compared to flight instrumentation data from previous flights of the same launch vehicle. This is done to ensure the current mission environments, such as shock, random vibration, and acoustics, are not out of family with existing flight experience. In family means the peaks on the SRS curve for WGS-5 are similar to the peaks from the previous flights and there are no major outliers. The curves from the data will then be compiled into a useful format so that is can be peer reviewed then presented before an engineering review board if required. Also, the reviewed data will be uploaded to the Engineering Review Board Information System (ERBIS) to archive. The second part of this project is conducting Finite Element Analysis of a CubeSat. In 2010, Merritt Island High School partnered with NASA to design, build and launch a CubeSat. The team is now called StangSat in honor of their mascot, the mustang. Over the past few years, the StangSat team has built a satellite and has now been manifested for flight on a SpaceX Falcon 9 launch in 2014. To prepare for the final launch, a test flight was conducted in Mojave, California. StangSat was launched on a Prospector 18D, a high altitude rocket made by Garvey Spacecraft Corporation, along with their sister satellite CP9 built by California Polytechnic University. However, StangSat was damaged during an off nominal landing and this project will give beneficial insights into what loads the CubeSat experienced during the crash

  15. 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

  16. 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

  17. 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

  18. Entity Authentication:Analysis using Structured Intuition

    DEFF Research Database (Denmark)

    Ahmed, Naveed; Jensen, Christian D.

    2010-01-01

    In this paper, we propose a new method for the analysis that uses intuition of the analyst in a structured way. First we define entity authentication in terms of fine level authentication goals (FLAGs). Then we use some relevant structures in protocol narrations and use them to justify FLAGs...... specification of security in terms of FLAGs; and secondly the outcome can be used to transform basic protocol narrations into more detailed specifications, which makes a subsequent formal analysis much more meaningful....

  19. Analysis model of structure-HDS

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Presents the model established for Structure-HDS(hydraulic damper system) analysis on the basis of the theoretical analysis model of non-compressed fluid in the round pipe will an uniform velocity used as the basic variable, and pressure losses resulting from cross section changes of fluid route taken into consideration. Which provides necessary basis for researches on earthquake responses of a structure with a spacious first story, equipped with HDS at first floor.

  20. Using rhetorical structure in sentiment analysis

    NARCIS (Netherlands)

    Hogenboom, Alexander; Frasincar, Flavius; Jong, de Franciska; Kaymak, Uzay

    2015-01-01

    Automated sentiment analysis has become an active field of study with a broad applicability. One of the key open research issues lies in dealing with structural aspects of text when analyzing its conveyed sentiment. Recent work uses structural aspects of text in order to distinguish important text s

  1. Generalized Structured Component Analysis with Latent Interactions

    Science.gov (United States)

    Hwang, Heungsun; Ho, Moon-Ho Ringo; Lee, Jonathan

    2010-01-01

    Generalized structured component analysis (GSCA) is a component-based approach to structural equation modeling. In practice, researchers may often be interested in examining the interaction effects of latent variables. However, GSCA has been geared only for the specification and testing of the main effects of variables. Thus, an extension of GSCA…

  2. Group theory analysis of braided geometry structures

    Institute of Scientific and Technical Information of China (English)

    FENG Wei; MA Wensuo

    2005-01-01

    The braided geometry structures are analyzed with point groups and space groups for which the continuous yarn of the braided preforms is segmented and expressed in some special symbols. All structures of braided material are described and classified with group theory, and new braiding methods are found. The group theory analysis lays the theoretical foundation for optimizing material performance.

  3. Genome-scale transcriptional activation by an engineered CRISPR-Cas9 complex.

    Science.gov (United States)

    Konermann, Silvana; Brigham, Mark D; Trevino, Alexandro E; Joung, Julia; Abudayyeh, Omar O; Barcena, Clea; Hsu, Patrick D; Habib, Naomi; Gootenberg, Jonathan S; Nishimasu, Hiroshi; Nureki, Osamu; Zhang, Feng

    2015-01-29

    Systematic interrogation of gene function requires the ability to perturb gene expression in a robust and generalizable manner. Here we describe structure-guided engineering of a CRISPR-Cas9 complex to mediate efficient transcriptional activation at endogenous genomic loci. We used these engineered Cas9 activation complexes to investigate single-guide RNA (sgRNA) targeting rules for effective transcriptional activation, to demonstrate multiplexed activation of ten genes simultaneously, and to upregulate long intergenic non-coding RNA (lincRNA) transcripts. We also synthesized a library consisting of 70,290 guides targeting all human RefSeq coding isoforms to screen for genes that, upon activation, confer resistance to a BRAF inhibitor. The top hits included genes previously shown to be able to confer resistance, and novel candidates were validated using individual sgRNA and complementary DNA overexpression. A gene expression signature based on the top screening hits correlated with markers of BRAF inhibitor resistance in cell lines and patient-derived samples. These results collectively demonstrate the potential of Cas9-based activators as a powerful genetic perturbation technology.

  4. Bayesian analysis of cosmic structures

    CERN Document Server

    Kitaura, Francisco-Shu

    2011-01-01

    We revise the Bayesian inference steps required to analyse the cosmological large-scale structure. Here we make special emphasis in the complications which arise due to the non-Gaussian character of the galaxy and matter distribution. In particular we investigate the advantages and limitations of the Poisson-lognormal model and discuss how to extend this work. With the lognormal prior using the Hamiltonian sampling technique and on scales of about 4 h^{-1} Mpc we find that the over-dense regions are excellent reconstructed, however, under-dense regions (void statistics) are quantitatively poorly recovered. Contrary to the maximum a posteriori (MAP) solution which was shown to over-estimate the density in the under-dense regions we obtain lower densities than in N-body simulations. This is due to the fact that the MAP solution is conservative whereas the full posterior yields samples which are consistent with the prior statistics. The lognormal prior is not able to capture the full non-linear regime at scales ...

  5. Review: High-performance computing to detect epistasis in genome scale data sets.

    Science.gov (United States)

    Upton, Alex; Trelles, Oswaldo; Cornejo-García, José Antonio; Perkins, James Richard

    2016-05-01

    It is becoming clear that most human diseases have a complex etiology that cannot be explained by single nucleotide polymorphisms (SNPs) or simple additive combinations; the general consensus is that they are caused by combinations of multiple genetic variations. The limited success of some genome-wide association studies is partly a result of this focus on single genetic markers. A more promising approach is to take into account epistasis, by considering the association of multiple SNP interactions with disease. However, as genomic data continues to grow in resolution, and genome and exome sequencing become more established, the number of combinations of variants to consider increases rapidly. Two potential solutions should be considered: the use of high-performance computing, which allows us to consider a larger number of variables, and heuristics to make the solution more tractable, essential in the case of genome sequencing. In this review, we look at different computational methods to analyse epistatic interactions within disease-related genetic data sets created by microarray technology. We also review efforts to use epistatic analysis results to produce biomarkers for diagnostic tests and give our views on future directions in this field in light of advances in sequencing technology and variants in non-coding regions.

  6. Integrated genome-scale prediction of detrimental mutations in transcription networks.

    Directory of Open Access Journals (Sweden)

    Mirko Francesconi

    2011-05-01

    Full Text Available A central challenge in genetics is to understand when and why mutations alter the phenotype of an organism. The consequences of gene inhibition have been systematically studied and can be predicted reasonably well across a genome. However, many sequence variants important for disease and evolution may alter gene regulation rather than gene function. The consequences of altering a regulatory interaction (or "edge" rather than a gene (or "node" in a network have not been as extensively studied. Here we use an integrative analysis and evolutionary conservation to identify features that predict when the loss of a regulatory interaction is detrimental in the extensively mapped transcription network of budding yeast. Properties such as the strength of an interaction, location and context in a promoter, regulator and target gene importance, and the potential for compensation (redundancy associate to some extent with interaction importance. Combined, however, these features predict quite well whether the loss of a regulatory interaction is detrimental across many promoters and for many different transcription factors. Thus, despite the potential for regulatory diversity, common principles can be used to understand and predict when changes in regulation are most harmful to an organism.

  7. Structural Analysis Of Offshore Structures Exposed To Blast Loads

    DEFF Research Database (Denmark)

    Hansen, Hans Jakup; Thygesen, Ulf; Kristensen, Anders;

    2002-01-01

    Numerical methods for simulations of blast loads and resulting structural response are investigated and compared to results obtained from tests. The CFD code EXSIM is used for the simulation of the blast load. This code provides a load profile wich is entered in the FEM analysis model....

  8. Structural Analysis in a Conceptual Design Framework

    Science.gov (United States)

    Padula, Sharon L.; Robinson, Jay H.; Eldred, Lloyd B.

    2012-01-01

    Supersonic aircraft designers must shape the outer mold line of the aircraft to improve multiple objectives, such as mission performance, cruise efficiency, and sonic-boom signatures. Conceptual designers have demonstrated an ability to assess these objectives for a large number of candidate designs. Other critical objectives and constraints, such as weight, fuel volume, aeroelastic effects, and structural soundness, are more difficult to address during the conceptual design process. The present research adds both static structural analysis and sizing to an existing conceptual design framework. The ultimate goal is to include structural analysis in the multidisciplinary optimization of a supersonic aircraft. Progress towards that goal is discussed and demonstrated.

  9. Seismic analysis of nuclear power plant structures

    Science.gov (United States)

    Go, J. C.

    1973-01-01

    Primary structures for nuclear power plants are designed to resist expected earthquakes of the site. Two intensities are referred to as Operating Basis Earthquake and Design Basis Earthquake. These structures are required to accommodate these seismic loadings without loss of their functional integrity. Thus, no plastic yield is allowed. The application of NASTRAN in analyzing some of these seismic induced structural dynamic problems is described. NASTRAN, with some modifications, can be used to analyze most structures that are subjected to seismic loads. A brief review of the formulation of seismic-induced structural dynamics is also presented. Two typical structural problems were selected to illustrate the application of the various methods of seismic structural analysis by the NASTRAN system.

  10. A protein structure data and analysis system.

    Science.gov (United States)

    Tian, Hao; Sunderraman, Rajshekhar; Weber, Irene; Wang, Haibin; Yang, Hong

    2005-01-01

    In this paper, we present the design and implementation of a protein structure data and analysis system that is only used in the lab for analyzing the proprietary data. It is capable of storing public protein data, such as the data in Protein Data Bank (PDB) [1], and life scientists' proprietary data. This toolkit is targeted at life scientists who want to maintain proprietary protein structure data (may be incomplete), to search and query publicly known protein structures and to compare their structure data with others. The comparison functions can be used to find structure differences between two proteins at atom level, especially in mutant versions of proteins. The system can also be used as a tool of choosing better protein structure template in new protein's tertiary structure prediction. The system is developed in Java and the protein data is stored in a relational database (Oracle 9i).

  11. Genome-scale mRNA and small RNA transcriptomic insights into initiation of citrus apomixis

    Science.gov (United States)

    Long, Jian-Mei; Liu, Zheng; Wu, Xiao-Meng; Fang, Yan-Ni; Jia, Hui-Hui; Xie, Zong-Zhou; Deng, Xiu-Xin; Guo, Wen-Wu

    2016-01-01

    Nucellar embryony (NE) is an adventitious form of apomixis common in citrus, wherein asexual embryos initiate directly from nucellar cells surrounding the embryo sac. NE enables the fixation of desirable agronomic traits and the production of clonal offspring of virus-free rootstock, but impedes progress in hybrid breeding. In spite of the great importance of NE in citrus breeding and commercial production, little is understood about the underlying molecular mechanisms. In this study, the stages of nucellar embryo initiation (NEI) were determined for two polyembryonic citrus cultivars via histological observation. To explore the genes and regulatory pathways involved in NEI, we performed mRNA-seq and sRNA-seq analyses of ovules immediately prior to and at stages during NEI in the two pairs of cultivars. A total of 305 differentially expressed genes (DEGs) were identified between the poly- and monoembryonic ovules. Gene ontology (GO) analysis revealed that several processes are significantly enriched based on DEGs. In particular, response to stress, and especially response to oxidative stress, was over-represented in polyembryonic ovules. Nearly 150 miRNAs, comprising ~90 conserved and ~60 novel miRNAs, were identified in the ovules of either cultivar pair. Only two differentially expressed miRNAs (DEMs) were identified, of which the novel miRN23-5p was repressed whereas the targets accumulated in the polyembryonic ovules. This integrated study on the transcriptional and post-transcriptional regulatory profiles between poly- and monoembryonic citrus ovules provides new insights into the mechanism of NE, which should contribute to revealing the regulatory mechanisms of plant apomixis. PMID:27619233

  12. Polarity Analysis of Texts using Discourse Structure

    NARCIS (Netherlands)

    Heerschop, Bas; Goosen, Frank; Hogenboom, Alexander; Frasincar, Flavius; Kaymak, Uzay; Jong, de Franciska

    2011-01-01

    Sentiment analysis has applications in many areas and the exploration of its potential has only just begun. We propose Pathos, a framework which performs document sentiment analysis (partly) based on a document’s discourse structure. We hypothesize that by splitting a text into important and less im

  13. Singular value decomposition of genome-scale mRNA lengths distribution reveals asymmetry in RNA gel electrophoresis band broadening.

    Science.gov (United States)

    Alter, Orly; Golub, Gene H

    2006-08-01

    We describe the singular value decomposition (SVD) of yeast genome-scale mRNA lengths distribution data measured by DNA microarrays. SVD uncovers in the mRNA abundance levels data matrix of genes x arrays, i.e., electrophoretic gel migration lengths or mRNA lengths, mathematically unique decorrelated and decoupled "eigengenes." The eigengenes are the eigenvectors of the arrays x arrays correlation matrix, with the corresponding series of eigenvalues proportional to the series of the "fractions of eigen abundance." Each fraction of eigen abundance indicates the significance of the corresponding eigengene relative to all others. We show that the eigengenes fit "asymmetric Hermite functions," a generalization of the eigenfunctions of the quantum harmonic oscillator and the integral transform which kernel is a generalized coherent state. The fractions of eigen abundance fit a geometric series as do the eigenvalues of the integral transform which kernel is a generalized coherent state. The "asymmetric generalized coherent state" models the measured data, where the profiles of mRNA abundance levels of most genes as well as the distribution of the peaks of these profiles fit asymmetric Gaussians. We hypothesize that the asymmetry in the distribution of the peaks of the profiles is due to two competing evolutionary forces. We show that the asymmetry in the profiles of the genes might be due to a previously unknown asymmetry in the gel electrophoresis thermal broadening of a moving, rather than a stationary, band of RNA molecules.

  14. Improved genome-scale multi-target virtual screening via a novel collaborative filtering approach to cold-start problem

    Science.gov (United States)

    Lim, Hansaim; Gray, Paul; Xie, Lei; Poleksic, Aleksandar

    2016-12-01

    Conventional one-drug-one-gene approach has been of limited success in modern drug discovery. Polypharmacology, which focuses on searching for multi-targeted drugs to perturb disease-causing networks instead of designing selective ligands to target individual proteins, has emerged as a new drug discovery paradigm. Although many methods for single-target virtual screening have been developed to improve the efficiency of drug discovery, few of these algorithms are designed for polypharmacology. Here, we present a novel theoretical framework and a corresponding algorithm for genome-scale multi-target virtual screening based on the one-class collaborative filtering technique. Our method overcomes the sparseness of the protein-chemical interaction data by means of interaction matrix weighting and dual regularization from both chemicals and proteins. While the statistical foundation behind our method is general enough to encompass genome-wide drug off-target prediction, the program is specifically tailored to find protein targets for new chemicals with little to no available interaction data. We extensively evaluate our method using a number of the most widely accepted gene-specific and cross-gene family benchmarks and demonstrate that our method outperforms other state-of-the-art algorithms for predicting the interaction of new chemicals with multiple proteins. Thus, the proposed algorithm may provide a powerful tool for multi-target drug design.

  15. 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.

  16. Parallel Mutual Information Based Construction of Genome-Scale Networks on the Intel® Xeon Phi™ Coprocessor.

    Science.gov (United States)

    Misra, Sanchit; Pamnany, Kiran; Aluru, Srinivas

    2015-01-01

    Construction of whole-genome networks from large-scale gene expression data is an important problem in systems biology. While several techniques have been developed, most cannot handle network reconstruction at the whole-genome scale, and the few that can, require large clusters. In this paper, we present a solution on the Intel Xeon Phi coprocessor, taking advantage of its multi-level parallelism including many x86-based cores, multiple threads per core, and vector processing units. We also present a solution on the Intel® Xeon® processor. Our solution is based on TINGe, a fast parallel network reconstruction technique that uses mutual information and permutation testing for assessing statistical significance. We demonstrate the first ever inference of a plant whole genome regulatory network on a single chip by constructing a 15,575 gene network of the plant Arabidopsis thaliana from 3,137 microarray experiments in only 22 minutes. In addition, our optimization for parallelizing mutual information computation on the Intel Xeon Phi coprocessor holds out lessons that are applicable to other domains.

  17. Structural-Thermal-Optical-Performance (STOP) Analysis

    Science.gov (United States)

    Bolognese, Jeffrey; Irish, Sandra

    2015-01-01

    The presentation will be given at the 26th Annual Thermal Fluids Analysis Workshop (TFAWS 2015) hosted by the Goddard Spaceflight Center (GSFC) Thermal Engineering Branch (Code 545). A STOP analysis is a multidiscipline analysis, consisting of Structural, Thermal and Optical Performance Analyses, that is performed for all space flight instruments and satellites. This course will explain the different parts of performing this analysis. The student will learn how to effectively interact with each discipline in order to accurately obtain the system analysis results.

  18. Kinematic Analysis of a Hybrid Structure

    Directory of Open Access Journals (Sweden)

    Q.J. Duan

    2012-11-01

    Full Text Available This paper presents a kinematic analysis and simulation of a hybrid structure applied to the new design cable-suspended feed structure (CSFS for the next generation of large spherical radio telescopes. First, considering the requirement that feeds should be tilted from 40° to 60° and that the tracking precision in steady state is 4mm, a novel design of the feed supporting structure including a cable-cabin structure, an AB axis structure and a Stewart platform is performed. Next, kinematic analysis and the simulation of the CSFS are done. Simulations have been developed in combination with the 50m CSFS model, which demonstrate the effectiveness and feasibility of the proposed three-level cable-suspended feed system.

  19. Structural Vibration Monitoring Using Cumulative Spectral Analysis

    Directory of Open Access Journals (Sweden)

    Satoru Goto

    2013-01-01

    Full Text Available This paper describes a resonance decay estimation for structural health monitoring in the presence of nonstationary vibrations. In structural health monitoring, the structure's frequency response and resonant decay characteristics are very important for understanding how the structure changes. Cumulative spectral analysis (CSA estimates the frequency decay by using the impulse response. However, measuring the impulse response of buildings is impractical due to the need to shake the building itself. In a previous study, we reported on system damping monitoring using cumulative harmonic analysis (CHA, which is based on CSA. The current study describes scale model experiments on estimating the hidden resonance decay under non-stationary noise conditions by using CSA for structural condition monitoring.

  20. Advanced analysis for structural steel building design

    Institute of Scientific and Technical Information of China (English)

    Wai Fah CHEN

    2008-01-01

    The 2005 AISC LRFD Specifications for Structural Steel Buildings are making it possible for designers to recognize explicitly the structural resistance provided within the elastic and inelastic ranges of beha-vior and up to the maximum load limit state. There is an increasing awareness of the need for practical second-order analysis approaches for a direct determination of overall structural system response. This paper attempts to present a simple, concise and reasonably comprehens-ive introduction to some of the theoretical and practical approaches which have been used in the traditional and modern processes of design of steel building structures.

  1. Analysis of flexible structures under lateral impact

    Energy Technology Data Exchange (ETDEWEB)

    Ramirez, D. F. [Paul C. Kizzo and Associates Inc., Seismic Structural Group, Oakland, CA 94612 (United States); Razavi, H. [AREVA Inc., Civil Seismic Group, San Jose, CA 95119 (United States)

    2012-07-01

    Three methods for analysis of flexible structures under lateral impact are presented. The first proposed method (Method A) consists of: (1) modifying an available deceleration on a rigid target with conservation principles to account for structural flexibility; and (2) transient nonlinear analysis of the structure with the corrected forcing function. The second proposed method (Method B) is similar to Method A in obtaining the forcing function but it solves the equations of motion of an idealized two-degree-of-freedom system instead of directly using conservation principles. The last method simply provides the maximum force in the structure using the conservation of energy and linear momentum. A coupled simulation is also performed in LS-DYNA and compared against the proposed methods. A case study is presented to illustrate the applicability of all three methods and the LS-DYNA simulation. (authors)

  2. Dynamic Analysis of Structures Using Neural Networks

    Directory of Open Access Journals (Sweden)

    N. Ahmadi

    2008-01-01

    Full Text Available In the recent years, neural networks are considered as the best candidate for fast approximation with arbitrary accuracy in the time consuming problems. Dynamic analysis of structures against earthquake has the time consuming process. We employed two kinds of neural networks: Generalized Regression neural network (GR and Back-Propagation Wavenet neural network (BPW, for approximating of dynamic time history response of frame structures. GR is a traditional radial basis function neural network while BPW categorized as a wavelet neural network. In BPW, sigmoid activation functions of hidden layer neurons are substituted with wavelets and weights training are achieved using Scaled Conjugate Gradient (SCG algorithm. Comparison the results of BPW with those of GR in the dynamic analysis of eight story steel frame indicates that accuracy of the properly trained BPW was better than that of GR and therefore, BPW can be efficiently used for approximate dynamic analysis of structures.

  3. Object-Oriented Analysis, Structured Analysis, and Jackson System Development

    NARCIS (Netherlands)

    Wieringa, R.J.; Van Assche, F.; Moulin, B.; Rolland, C.

    1991-01-01

    Conceptual modeling is the activity of producing a conceptual model of an actual or desired version of a universe of discourse (UoD). In this paper, two methods of conceptual modeling are compared, structured analysis (SA) and object-oriented analysis (OOA). This is done by transforming a model prod

  4. Object-Oriented Analysis, Structured Analysis, and Jackson System Development

    NARCIS (Netherlands)

    Van Assche, F.; Wieringa, Roelf J.; Moulin, B.; Rolland, C

    1991-01-01

    Conceptual modeling is the activity of producing a conceptual model of an actual or desired version of a universe of discourse (UoD). In this paper, two methods of conceptual modeling are compared, structured analysis (SA) and object-oriented analysis (OOA). This is done by transforming a model

  5. Data structures and algorithm analysis in Java

    CERN Document Server

    Shaffer, Clifford A

    2011-01-01

    With its focus on creating efficient data structures and algorithms, this comprehensive text helps readers understand how to select or design the tools that will best solve specific problems. It uses Java as the programming language and is suitable for second-year data structure courses and computer science courses in algorithm analysis. Techniques for representing data are presented within the context of assessing costs and benefits, promoting an understanding of the principles of algorithm analysis and the effects of a chosen physical medium. The text also explores tradeoff issues, familiari

  6. Data structures and algorithm analysis in C++

    CERN Document Server

    Shaffer, Clifford A

    2011-01-01

    With its focus on creating efficient data structures and algorithms, this comprehensive text helps readers understand how to select or design the tools that will best solve specific problems. It uses Microsoft C++ as the programming language and is suitable for second-year data structure courses and computer science courses in algorithm analysis.Techniques for representing data are presented within the context of assessing costs and benefits, promoting an understanding of the principles of algorithm analysis and the effects of a chosen physical medium. The text also explores tradeoff issues, f

  7. On the structural analysis of textile composites

    Science.gov (United States)

    Bogdanovich, Alexander E.; Pastore, Christopher M.

    The local structural inhomogeneities which distinguish textile composites from laminated materials are discussed. Techniques for quantifying these inhomogeneities through three dimensional geometric modelling are introduced and methods of translating them into elastic properties are presented. Some basic ideas on application of spline functions to the stress field analysis in textile composites are proposed. The significance of internal continuity conditions for these materials is emphasized. Several analytical techniques based on the concept of a meso-volume are discussed. An example is presented to demonstrate the application of the method to structural analysis of textile composites.

  8. Value of Information Analysis in Structural Safety

    DEFF Research Database (Denmark)

    Konakli, Katerina; Faber, Michael Havbro

    2014-01-01

    of structural systems. In this context, experiments may refer to inspections or techniques of structural health monitoring. The Value of Information concept provides a powerful tool for determining whether the experimental cost is justified by the expected benefit and for identifying the optimal among different......Pre-posterior analysis can be used to assess the potential of an experiment to enhance decision making by providing information on parameters characterized by uncertainty. The present paper describes a framework for pre-posterior analysis for support of decisions related to maintenance...... and quality of information and the probabilistic dependencies between components of a system....

  9. 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.

  10. Genome-scale metabolic reconstructions of Pichia stipitis and Pichia pastoris and in silico evaluation of their potentials

    Directory of Open Access Journals (Sweden)

    Caspeta Luis

    2012-04-01

    Full Text Available Abstract Background Pichia stipitis and Pichia pastoris have long been investigated due to their native abilities to metabolize every sugar from lignocellulose and to modulate methanol consumption, respectively. The latter has been driving the production of several recombinant proteins. As a result, significant advances in their biochemical knowledge, as well as in genetic engineering and fermentation methods have been generated. The release of their genome sequences has allowed systems level research. Results In this work, genome-scale metabolic models (GEMs of P. stipitis (iSS884 and P. pastoris (iLC915 were reconstructed. iSS884 includes 1332 reactions, 922 metabolites, and 4 compartments. iLC915 contains 1423 reactions, 899 metabolites, and 7 compartments. Compared with the previous GEMs of P. pastoris, PpaMBEL1254 and iPP668, iLC915 contains more genes and metabolic functions, as well as improved predictive capabilities. Simulations of physiological responses for the growth of both yeasts on selected carbon sources using iSS884 and iLC915 closely reproduced the experimental data. Additionally, the iSS884 model was used to predict ethanol production from xylose at different oxygen uptake rates. Simulations with iLC915 closely reproduced the effect of oxygen uptake rate on physiological states of P. pastoris expressing a recombinant protein. The potential of P. stipitis for the conversion of xylose and glucose into ethanol using reactors in series, and of P. pastoris to produce recombinant proteins using mixtures of methanol and glycerol or sorbitol are also discussed. Conclusions In conclusion the first GEM of P. stipitis (iSS884 was reconstructed and validated. The expanded version of the P. pastoris GEM, iLC915, is more complete and has improved capabilities over the existing models. Both GEMs are useful frameworks to explore the versatility of these yeasts and to capitalize on their biotechnological potentials.

  11. RNA Secondary Structure Analysis Using RNAstructure.

    Science.gov (United States)

    Mathews, David H

    2014-06-17

    RNAstructure is a user-friendly program for the prediction and analysis of RNA secondary structure. It is available as a Web server, as a program with a graphical user interface, or as a set of command-line tools. The programs are available for Microsoft Windows, Macintosh OS X, or Linux. This unit provides protocols for RNA secondary structure prediction (using the Web server or the graphical user interface) and prediction of high-affinity oligonucleotide biding sites to a structured RNA target (using the graphical user interface). Copyright © 2014 John Wiley & Sons, Inc.

  12. Improving transient analysis technology for aircraft structures

    Science.gov (United States)

    Melosh, R. J.; Chargin, Mladen

    1989-01-01

    Aircraft dynamic analyses are demanding of computer simulation capabilities. The modeling complexities of semi-monocoque construction, irregular geometry, high-performance materials, and high-accuracy analysis are present. At issue are the safety of the passengers and the integrity of the structure for a wide variety of flight-operating and emergency conditions. The technology which supports engineering of aircraft structures using computer simulation is examined. Available computer support is briefly described and improvement of accuracy and efficiency are recommended. Improved accuracy of simulation will lead to a more economical structure. Improved efficiency will result in lowering development time and expense.

  13. Analysis of latent structures in linear systems

    DEFF Research Database (Denmark)

    Høskuldsson, Agnar

    2004-01-01

    that are useful, when studying latent structures. It is shown how loading weight vectors are generated and how they can be interpreted in analyzing the latent structure. It is shown how the covariance can be used to get useful ‘apriori’ information on the modeling task. Also some simple methods are presented...... to use for deciding if single or multiple latent structures should be used. The last part is about choosing the variables that should be used in the analysis. The traditional procedures to select variables to include in the model are presented and the insufficiencies of such approaches are demonstrated...

  14. Entity Authentication:Analysis using Structured Intuition

    DEFF Research Database (Denmark)

    Ahmed, Naveed; Jensen, Christian D.

    2010-01-01

    In this paper, we propose a new method for the analysis that uses intuition of the analyst in a structured way. First we define entity authentication in terms of fine level authentication goals (FLAGs). Then we use some relevant structures in protocol narrations and use them to justify FLAGs...... for the protocol. All along this process, we discover vulnerabilities and unstated assumptions of the protocol. As the method is intuition based, the quality of results depends on the expertise of the security analyst, however, the structured intuition has two major advantages: Firstly we get a precise...

  15. Term Structure Analysis with Big Data

    DEFF Research Database (Denmark)

    Andreasen, Martin Møller; Christensen, Jens H.E.; Rudebusch, Glenn D.

    Analysis of the term structure of interest rates almost always takes a two-step approach. First, actual bond prices are summarized by interpolated synthetic zero-coupon yields, and second, a small set of these yields are used as the source data for further empirical examination. In contrast, we...

  16. A Dynamic Model for Energy Structure Analysis

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Energy structure is a complicated system concerning economic development, natural resources, technological innovation, ecological balance, social progress and many other elements. It is not easy to explain clearly the developmental mechanism of an energy system and the mutual relations between the energy system and its related environments by the traditional methods. It is necessary to develop a suitable dynamic model, which can reflect the dynamic characteristics and the mutual relations of the energy system and its related environments. In this paper, the historical development of China's energy structure was analyzed. A new quantitative analysis model was developed based on system dynamics principles through analysis of energy resources, and the production and consumption of energy in China and comparison with the world. Finally, this model was used to predict China's future energy structures under different conditions.

  17. Structural Analysis of Molecular Clouds: Dendrograms

    CERN Document Server

    Rosolowsky, E W; Kauffmann, J; Goodman, A A

    2008-01-01

    We demonstrate the utility of dendrograms at representing the essential features of the hierarchical structure of the isosurfaces for molecular line data cubes. The dendrogram of a data cube is an abstraction of the changing topology of the isosurfaces as a function of contour level. The ability to track hierarchical structure over a range of scales makes this analysis philosophically different from local segmentation algorithms like CLUMPFIND. Points in the dendrogram structure correspond to specific volumes in data cubes defined by their bounding isosurfaces. We further refine the technique by measuring the properties associated with each isosurface in the analysis allowing for a multiscale calculation of molecular gas properties. Using COMPLETE 13CO(1-0) data from the L1448 region in Perseus and mock observations of a simulated data cube, we identify regions that have a significant contribution by self-gravity to their energetics on a range of scales. We find evidence for self-gravitation on all spatial sc...

  18. A genome scale metabolic network for rice and accompanying analysis of tryptophan, auxin and serotonin biosynthesis regulation under biotic stress

    Science.gov (United States)

    Functional annotations of large plant genome projects mostly provide information on gene function and gene families based on the presence of protein domains and gene homology, but not necessarily in association with gene expression or metabolic and regulatory networks. These additional annotations a...

  19. Meta-Analysis of Heterogeneous Data Sources for Genome-Scale Identification of Risk Genes in Complex Phenotypes

    DEFF Research Database (Denmark)

    Pers, Tune Hannes; Hansen, Niclas Tue; Hansen, Kasper Lage;

    2011-01-01

    Meta‐analyses of large‐scale association studies typically proceed solely within one data type and do not exploit the potential complementarities in other sources of molecular evidence. Here, we present an approach to combine heterogeneous data from genome‐wide association (GWA) studies, protein......) with an odds ratio of 1.28 [1.12–1.48], which replicates a previous case‐control study. In addition, we demonstrate our approach's general applicability by use of type 2 diabetes data sets. The method presented augments moderately powered GWA data, and represents a validated, flexible, and publicly available...

  20. Analysis of 81 genes from 64 plastid genomes resolves relationships in angiosperms and identifies genome-scale evolutionary patterns

    Science.gov (United States)

    Jansen, Robert K.; Cai, Zhengqiu; Raubeson, Linda A.; Daniell, Henry; dePamphilis, Claude W.; Leebens-Mack, James; Müller, Kai F.; Guisinger-Bellian, Mary; Haberle, Rosemarie C.; Hansen, Anne K.; Chumley, Timothy W.; Lee, Seung-Bum; Peery, Rhiannon; McNeal, Joel R.; Kuehl, Jennifer V.; Boore, Jeffrey L.

    2007-01-01

    Angiosperms are the largest and most successful clade of land plants with >250,000 species distributed in nearly every terrestrial habitat. Many phylogenetic studies have been based on DNA sequences of one to several genes, but, despite decades of intensive efforts, relationships among early diverging lineages and several of the major clades remain either incompletely resolved or weakly supported. We performed phylogenetic analyses of 81 plastid genes in 64 sequenced genomes, including 13 new genomes, to estimate relationships among the major angiosperm clades, and the resulting trees are used to examine the evolution of gene and intron content. Phylogenetic trees from multiple methods, including model-based approaches, provide strong support for the position of Amborella as the earliest diverging lineage of flowering plants, followed by Nymphaeales and Austrobaileyales. The plastid genome trees also provide strong support for a sister relationship between eudicots and monocots, and this group is sister to a clade that includes Chloranthales and magnoliids. Resolution of relationships among the major clades of angiosperms provides the necessary framework for addressing numerous evolutionary questions regarding the rapid diversification of angiosperms. Gene and intron content are highly conserved among the early diverging angiosperms and basal eudicots, but 62 independent gene and intron losses are limited to the more derived monocot and eudicot clades. Moreover, a lineage-specific correlation was detected between rates of nucleotide substitutions, indels, and genomic rearrangements. PMID:18048330

  1. Genome-scale regression analysis reveals a linear relationship for promoters and enhancers after combinatorial drug treatment

    KAUST Repository

    Rapakoulia, Trisevgeni

    2017-08-09

    Motivation: Drug combination therapy for treatment of cancers and other multifactorial diseases has the potential of increasing the therapeutic effect, while reducing the likelihood of drug resistance. In order to reduce time and cost spent in comprehensive screens, methods are needed which can model additive effects of possible drug combinations. Results: We here show that the transcriptional response to combinatorial drug treatment at promoters, as measured by single molecule CAGE technology, is accurately described by a linear combination of the responses of the individual drugs at a genome wide scale. We also find that the same linear relationship holds for transcription at enhancer elements. We conclude that the described approach is promising for eliciting the transcriptional response to multidrug treatment at promoters and enhancers in an unbiased genome wide way, which may minimize the need for exhaustive combinatorial screens.

  2. Segmentation of histological structures for fractal analysis

    Science.gov (United States)

    Dixon, Vanessa; Kouznetsov, Alexei; Tambasco, Mauro

    2009-02-01

    Pathologists examine histology sections to make diagnostic and prognostic assessments regarding cancer based on deviations in cellular and/or glandular structures. However, these assessments are subjective and exhibit some degree of observer variability. Recent studies have shown that fractal dimension (a quantitative measure of structural complexity) has proven useful for characterizing structural deviations and exhibits great potential for automated cancer diagnosis and prognosis. Computing fractal dimension relies on accurate image segmentation to capture the architectural complexity of the histology specimen. For this purpose, previous studies have used techniques such as intensity histogram analysis and edge detection algorithms. However, care must be taken when segmenting pathologically relevant structures since improper edge detection can result in an inaccurate estimation of fractal dimension. In this study, we established a reliable method for segmenting edges from grayscale images. We used a Koch snowflake, an object of known fractal dimension, to investigate the accuracy of various edge detection algorithms and selected the most appropriate algorithm to extract the outline structures. Next, we created validation objects ranging in fractal dimension from 1.3 to 1.9 imitating the size, structural complexity, and spatial pixel intensity distribution of stained histology section images. We applied increasing intensity thresholds to the validation objects to extract the outline structures and observe the effects on the corresponding segmentation and fractal dimension. The intensity threshold yielding the maximum fractal dimension provided the most accurate fractal dimension and segmentation, indicating that this quantitative method could be used in an automated classification system for histology specimens.

  3. Stochastic Simulation Tool for Aerospace Structural Analysis

    Science.gov (United States)

    Knight, Norman F.; Moore, David F.

    2006-01-01

    Stochastic simulation refers to incorporating the effects of design tolerances and uncertainties into the design analysis model and then determining their influence on the design. A high-level evaluation of one such stochastic simulation tool, the MSC.Robust Design tool by MSC.Software Corporation, has been conducted. This stochastic simulation tool provides structural analysts with a tool to interrogate their structural design based on their mathematical description of the design problem using finite element analysis methods. This tool leverages the analyst's prior investment in finite element model development of a particular design. The original finite element model is treated as the baseline structural analysis model for the stochastic simulations that are to be performed. A Monte Carlo approach is used by MSC.Robust Design to determine the effects of scatter in design input variables on response output parameters. The tool was not designed to provide a probabilistic assessment, but to assist engineers in understanding cause and effect. It is driven by a graphical-user interface and retains the engineer-in-the-loop strategy for design evaluation and improvement. The application problem for the evaluation is chosen to be a two-dimensional shell finite element model of a Space Shuttle wing leading-edge panel under re-entry aerodynamic loading. MSC.Robust Design adds value to the analysis effort by rapidly being able to identify design input variables whose variability causes the most influence in response output parameters.

  4. EXPERIMENTAL MODAL ANALYSIS OF VISCO-ELASTICALLY DAMPED STRUCTURES

    Institute of Scientific and Technical Information of China (English)

    1998-01-01

    The form of the modal analysis of viscoelastically damped structures is simplified and this simplified form is similar to the form of the modal analysis of linear viscously damped structures. As a result of this simplified form, the experimental modal analysis methods of linear viscously damped structures are applied to the experimental modal analysis of viscoelastically damped structures.

  5. Static Structural and Modal Analysis Using Isogeometric Analysis

    Science.gov (United States)

    Gondegaon, Sangamesh; Voruganti, Hari K.

    2016-12-01

    Isogeometric Analysis (IGA) is a new analysis method for unification of Computer Aided Design (CAD) and Computer Aided Engineering (CAE). With the use of NURBS basis functions for both modelling and analysis, the bottleneck of meshing is avoided and a seamless integration is achieved. The CAD and computational geometry concepts in IGA are new to the analysis community. Though, there is a steady growth of literature, details of calculations, explanations and examples are not reported. The content of the paper is complimentary to the existing literature and addresses the gaps. It includes summary of the literature, overview of the methodology, step-by-step calculations and Matlab codes for example problems in static structural and modal analysis in 1-D and 2-D. At appropriate places, comparison with the Finite Element Analysis (FEM) is also included, so that those familiar with FEM can appreciate IGA better.

  6. Combination of structural reliability and interval analysis

    Institute of Scientific and Technical Information of China (English)

    Zhiping Qiu; Di Yang; saac Elishakoff

    2008-01-01

    In engineering applications,probabilistic reliability theory appears to be presently the most important method,however,in many cases precise probabilistic reliability theory cannot be considered as adequate and credible model of the real state of actual affairs.In this paper,we developed a hybrid of probabilistic and non-probabilistic reliability theory,which describes the structural uncertain parameters as interval variables when statistical data are found insufficient.By using the interval analysis,a new method for calculating the interval of the structural reliability as well as the reliability index is introduced in this paper,and the traditional probabilistic theory is incorporated with the interval analysis.Moreover,the new method preserves the useful part of the traditional probabilistic reliability theory,but removes the restriction of its strict requirement on data acquisition.Example is presented to demonstrate the feasibility and validity of the proposed theory.

  7. Numerical Limit Analysis of Reinforced Concrete Structures

    DEFF Research Database (Denmark)

    Larsen, Kasper Paaske

    methods provide engineers with valuable tools for limit sta- te analysis, their application becomes difficult with increased structural complexity. The main challenge is to solve the optimization problem posed by the extremum principles. This thesis is a study of how numerical methods can be used to solve...... limit state analysis problems. The work focuses on determination of the load bearing capacity of reinforced concrete structures by employing the lower bound theorem and a finite element method using equilibrium elements is developed. The recent year’s development within the field of convex optimization...... is developed for improved perfor- mance. An example is given in which an inverse T-beam is analyzed and the numerical results are compared to laboratory tests. The third and final element is a plane shell element capable of modeling membrane and plate bending behavior. The element employs a layered disk...

  8. Reliability Analysis of Elasto-Plastic Structures

    DEFF Research Database (Denmark)

    1984-01-01

    . Failure of this type of system is defined either as formation of a mechanism or by failure of a prescribed number of elements. In the first case failure is independent of the order in which the elements fail, but this is not so by the second definition. The reliability analysis consists of two parts...... are described and the two definitions of failure can be used by the first formulation, but only the failure definition based on formation of a mechanism by the second formulation. The second part of the reliability analysis is an estimate of the failure probability for the structure on the basis...... are obtained if the failure mechanisms are used. Lower bounds can be calculated on the basis of series systems where the elements are the non-failed elements in a non-failed structure (see Augusti & Baratta [3])....

  9. Limit analysis of solid reinforced concrete structures

    DEFF Research Database (Denmark)

    Larsen, Kasper Paaske

    2009-01-01

    element for lower bound analysis of reinforced concrete structures is presented. The method defines the stress state at a point within the solid as a combination of concrete- and reinforcement stresses and yield criterions are applied to the stress components separately. This method allows for orthotropic......Recent studies have shown that Semidefinite Programming (SDP) can be used effectively for limit analysis of isotropic cohesive-frictional continuums using the classical Mohr-Coulomb yield criterion. In this paper we expand on this previous research by adding reinforcement to the model and a solid...... reinforcement and it is therefore possible to analyze structures with complex reinforcement layouts. Tests are conducted to validate the method against well-known analytical solutions....

  10. EURO AREA FISCAL STRUCTURES. A MULTIVARIATE ANALYSIS

    Directory of Open Access Journals (Sweden)

    HURDUZEU Gheorghe

    2014-07-01

    taxes on income of corporations and taxes on income of individuals and households and other current taxes. Actual social contributions were also split into employer’s actual contributions, employee’s social contributions and social contributions of self- and non-employed persons. As the primary data analysis revealed many differences between Euro Area member states, but also similarities concerning various fiscal aggregates, we completed the analysis through multidimensional analysis, with the aims of classifying Euro Area member states into subgroups with similar fiscal structures. Taking into consideration the above mentioned variables, we used cluster analysis in order to determine which member states have similar fiscal structures and which are the main similarities that characterize Euro Area in this respect.

  11. Non Linear Seismic Analysis of Masonry Structures

    Directory of Open Access Journals (Sweden)

    Sirajuddin, M

    2011-12-01

    Full Text Available Nowadays, even though many new construction techniques have been introduced, masonry has got its own importance in building industry. Masonry structures fail miserably under lateral loading conditions like earth quakes and impact loads. The occurrence of recent earthquakes in India and in different parts of the world have highlighted that most of the loss of human lives and damage to property have been due to the collapse of masonry structures. Though an earthquake could not be prevented, the loss of life and property could be minimized, if necessary steps could be taken to reduce the damages on the existing masonry structures. This paper investigates the application ofNonlinear Seismic Analysis of a masonry building using ANSYS software and check the efficacy of retrofit measuresto protect the existing building.

  12. MBS Analysis Of Kinetic Structures Using ADAMS

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Nielsen, Søren R.K.

    2009-01-01

    The present paper considers multibody system (MBS) analysis of kinetic structures using the software package ADAMS. Deployable, foldable, expandable and reconfigurable kinetic structures can provide a change in the geometric morphology of the envelope by contributing to making it adaptable to e.......g. changing external climate factors, in order to improve the indoor climate performance of the building. The derivation of equations of motion for such spatial mechanical systems is a challenging issue in scientific community. However, with new symbolic tools one can automatically derive equations in so......-called multibody system (MBS) formalism. The present paper considers MBS modeling of kinetic architectural structures using the software packages ADAMS. As a result, it is found that symbolic MBS simulation tools facilitate a useful evaluation environment for MBS users during a design phase of responsive kinetic...

  13. Linking advanced fracture models to structural analysis

    Energy Technology Data Exchange (ETDEWEB)

    Chiesa, Matteo

    2001-07-01

    Shell structures with defects occur in many situations. The defects are usually introduced during the welding process necessary for joining different parts of the structure. Higher utilization of structural materials leads to a need for accurate numerical tools for reliable prediction of structural response. The direct discretization of the cracked shell structure with solid finite elements in order to perform an integrity assessment of the structure in question leads to large size problems, and makes such analysis infeasible in structural application. In this study a link between local material models and structural analysis is outlined. An ''ad hoc'' element formulation is used in order to connect complex material models to the finite element framework used for structural analysis. An improved elasto-plastic line spring finite element formulation, used in order to take cracks into account, is linked to shell elements which are further linked to beam elements. In this way one obtain a global model of the shell structure that also accounts for local flexibilities and fractures due to defects. An important advantage with such an approach is a direct fracture mechanics assessment e.g. via computed J-integral or CTOD. A recent development in this approach is the notion of two-parameter fracture assessment. This means that the crack tip stress tri-axiality (constraint) is employed in determining the corresponding fracture toughness, giving a much more realistic capacity of cracked structures. The present thesis is organized in six research articles and an introductory chapter that reviews important background literature related to this work. Paper I and II address the performance of shell and line spring finite elements as a cost effective tool for performing the numerical calculation needed to perform a fracture assessment. In Paper II a failure assessment, based on the testing of a constraint-corrected fracture mechanics specimen under tension, is

  14. TLP hull structural design and analysis

    Institute of Scientific and Technical Information of China (English)

    Yang Jiahui; Ren Michael

    2013-01-01

    Tension leg platform (TLP) has been one of the most favorite deep-water platform concepts for offshore oil and gas field exploration and development.As of now,a total of 24 TLPs have been installed worldwide with 3 more to be installed in the near future and 5 more under design.Most of these installations are in the Gulf of Mexico (GoM).Water depths for these TLP installations range from 150 m to 1 600 m.It is highly expected that China will have her first TLP designed,fabricated,and installed in the very near future.In order to satisfy the need for a unified hull structural design practice,this paper presents the design philosophy of a conventional TLP hull structure with emphases on critical structural components design and analysis methodologies.

  15. A Structural Analysis of European Union Economy

    Directory of Open Access Journals (Sweden)

    Liliana DUGULEANĂ

    2016-09-01

    Full Text Available Based on the input-output analysis, the paper characterizes the structure of European economy in 2010 and 2011, on six main economic sectors. The sectoral structures of backward and forward linkages, and their absolute effects starting from the final demand, were compared with the real structures of sectors output, sectoral imports, sectoral value added, in 2011 face to 2010. The changes in final demand and in sectoral output can be analyzed in the propagation processes of the inter-sectoral economic flows, and allow us to know the behavior at macroeconomic level of European economy. The common economic policies at European level can be undertaken to keep the equilibrium between different sectors, to stimulate the sectors with high levels of productivity, to ensure the efficiency of using the resources, and the sustainability of economic development, which are the purposes of a smart development.

  16. Structural Analysis About a New Solar Sail

    Institute of Scientific and Technical Information of China (English)

    ZHENG Jinjin; SHENG Zhaoyu; ZHOU Hongjun; HUANG Wenhao; SHENG Lianguan

    2009-01-01

    The article presents a structural analysis of a new space probe-solar sail. It was deployed successfully on ground. The loads for an outer space mission was introduced and expressed with equation. As a special state, the largest load around earth was used to analyze the model by the finite element method. Some results about strain and stress was obtained after setting some initial parameters. Compared to the results in the literature, the results presented here are significant.

  17. Structural analysis at aircraft conceptual design stage

    Science.gov (United States)

    Mansouri, Reza

    In the past 50 years, computers have helped by augmenting human efforts with tremendous pace. The aircraft industry is not an exception. Aircraft industry is more than ever dependent on computing because of a high level of complexity and the increasing need for excellence to survive a highly competitive marketplace. Designers choose computers to perform almost every analysis task. But while doing so, existing effective, accurate and easy to use classical analytical methods are often forgotten, which can be very useful especially in the early phases of the aircraft design where concept generation and evaluation demands physical visibility of design parameters to make decisions [39, 2004]. Structural analysis methods have been used by human beings since the very early civilization. Centuries before computers were invented; the pyramids were designed and constructed by Egyptians around 2000 B.C, the Parthenon was built by the Greeks, around 240 B.C, Dujiangyan was built by the Chinese. Persepolis, Hagia Sophia, Taj Mahal, Eiffel tower are only few more examples of historical buildings, bridges and monuments that were constructed before we had any advancement made in computer aided engineering. Aircraft industry is no exception either. In the first half of the 20th century, engineers used classical method and designed civil transport aircraft such as Ford Tri Motor (1926), Lockheed Vega (1927), Lockheed 9 Orion (1931), Douglas DC-3 (1935), Douglas DC-4/C-54 Skymaster (1938), Boeing 307 (1938) and Boeing 314 Clipper (1939) and managed to become airborne without difficulty. Evidencing, while advanced numerical methods such as the finite element analysis is one of the most effective structural analysis methods; classical structural analysis methods can also be as useful especially during the early phase of a fixed wing aircraft design where major decisions are made and concept generation and evaluation demands physical visibility of design parameters to make decisions

  18. Remote geologic structural analysis of Yucca Flat

    Energy Technology Data Exchange (ETDEWEB)

    Foley, M.G.; Heasler, P.G.; Hoover, K.A. (Pacific Northwest Lab., Richland, WA (United States)); Rynes, N.J. (Northern Illinois Univ., De Kalb, IL (United States)); Thiessen, R.L.; Alfaro, J.L. (Washington State Univ., Pullman, WA (United States))

    1991-12-01

    The Remote Geologic Analysis (RGA) system was developed by Pacific Northwest Laboratory (PNL) to identify crustal structures that may affect seismic wave propagation from nuclear tests. Using automated methods, the RGA system identifies all valleys in a digital elevation model (DEM), fits three-dimensional vectors to valley bottoms, and catalogs all potential fracture or fault planes defined by coplanar pairs of valley vectors. The system generates a cluster hierarchy of planar features having greater-than-random density that may represent areas of anomalous topography manifesting structural control of erosional drainage development. Because RGA uses computer methods to identify zones of hypothesized control of topography, ground truth using a well-characterized test site was critical in our evaluation of RGA's characterization of inaccessible test sites for seismic verification studies. Therefore, we applied RGA to a study area centered on Yucca Flat at the Nevada Test Site (NTS) and compared our results with both mapped geology and geologic structures and with seismic yield-magnitude models. This is the final report of PNL's RGA development project for peer review within the US Department of Energy Office of Arms Control (OAC) seismic-verification community. In this report, we discuss the Yucca Flat study area, the analytical basis of the RGA system and its application to Yucca Flat, the results of the analysis, and the relation of the analytical results to known topography, geology, and geologic structures. 41 refs., 39 figs., 2 tabs.

  19. Remote geologic structural analysis of Yucca Flat

    Energy Technology Data Exchange (ETDEWEB)

    Foley, M.G.; Heasler, P.G.; Hoover, K.A. [Pacific Northwest Lab., Richland, WA (United States); Rynes, N.J. [Northern Illinois Univ., De Kalb, IL (United States); Thiessen, R.L.; Alfaro, J.L. [Washington State Univ., Pullman, WA (United States)

    1991-12-01

    The Remote Geologic Analysis (RGA) system was developed by Pacific Northwest Laboratory (PNL) to identify crustal structures that may affect seismic wave propagation from nuclear tests. Using automated methods, the RGA system identifies all valleys in a digital elevation model (DEM), fits three-dimensional vectors to valley bottoms, and catalogs all potential fracture or fault planes defined by coplanar pairs of valley vectors. The system generates a cluster hierarchy of planar features having greater-than-random density that may represent areas of anomalous topography manifesting structural control of erosional drainage development. Because RGA uses computer methods to identify zones of hypothesized control of topography, ground truth using a well-characterized test site was critical in our evaluation of RGA`s characterization of inaccessible test sites for seismic verification studies. Therefore, we applied RGA to a study area centered on Yucca Flat at the Nevada Test Site (NTS) and compared our results with both mapped geology and geologic structures and with seismic yield-magnitude models. This is the final report of PNL`s RGA development project for peer review within the US Department of Energy Office of Arms Control (OAC) seismic-verification community. In this report, we discuss the Yucca Flat study area, the analytical basis of the RGA system and its application to Yucca Flat, the results of the analysis, and the relation of the analytical results to known topography, geology, and geologic structures. 41 refs., 39 figs., 2 tabs.

  20. Industrial entrepreneurial network: Structural and functional analysis

    Science.gov (United States)

    Medvedeva, M. A.; Davletbaev, R. H.; Berg, D. B.; Nazarova, J. J.; Parusheva, S. S.

    2016-12-01

    Structure and functioning of two model industrial entrepreneurial networks are investigated in the present paper. One of these networks is forming when implementing an integrated project and consists of eight agents, which interact with each other and external environment. The other one is obtained from the municipal economy and is based on the set of the 12 real business entities. Analysis of the networks is carried out on the basis of the matrix of mutual payments aggregated over the certain time period. The matrix is created by the methods of experimental economics. Social Network Analysis (SNA) methods and instruments were used in the present research. The set of basic structural characteristics was investigated: set of quantitative parameters such as density, diameter, clustering coefficient, different kinds of centrality, and etc. They were compared with the random Bernoulli graphs of the corresponding size and density. Discovered variations of random and entrepreneurial networks structure are explained by the peculiarities of agents functioning in production network. Separately, were identified the closed exchange circuits (cyclically closed contours of graph) forming an autopoietic (self-replicating) network pattern. The purpose of the functional analysis was to identify the contribution of the autopoietic network pattern in its gross product. It was found that the magnitude of this contribution is more than 20%. Such value allows using of the complementary currency in order to stimulate economic activity of network agents.

  1. Analysis of waveguiding properties of VCSEL structures

    Energy Technology Data Exchange (ETDEWEB)

    Erteza, I.A. [Sandia National Labs., Albuquerque, NM (United States). Exploratory Systems Development Center

    1996-09-01

    In this paper, the authors explore the feasibility of using the distributed Bragg reflector, grown on the substrate for a VCSEL (Vertical Cavity Surface Emitting Laser), to provide waveguiding within the substrate. This waveguiding could serve as an interconnection among VCSELs in an array. Before determining the feasibility of waveguide interconnected VCSELs, two analysis methods are presented and evaluated for their applicability to this problem. The implementations in Mathematica of both these methods are included. Results of the analysis show that waveguiding in VCSEL structures is feasible. Some of the many possible uses of waveguide interconnected VCSELs are also briefly discussed. The tools and analysis presented in this report can be used to evaluate such system concepts and to do detailed design calculations.

  2. Finite Element Vibration and Dynamic Response Analysis of Engineering Structures

    Directory of Open Access Journals (Sweden)

    Jaroslav Mackerle

    2000-01-01

    Full Text Available This bibliography lists references to papers, conference proceedings, and theses/dissertations dealing with finite element vibration and dynamic response analysis of engineering structures that were published from 1994 to 1998. It contains 539 citations. The following types of structures are included: basic structural systems; ground structures; ocean and coastal structures; mobile structures; and containment structures.

  3. BASE Flexible Array Preliminary Lithospheric Structure Analysis

    Science.gov (United States)

    Yeck, W. L.; Sheehan, A. F.; Anderson, M. L.; Siddoway, C. S.; Erslev, E.; Harder, S. H.; Miller, K. C.

    2009-12-01

    The Bighorns Arch Seismic Experiment (BASE) is a Flexible Array experiment integrated with EarthScope. The goal of BASE is to develop a better understanding of how basement-involved foreland arches form and what their link is to plate tectonic processes. To achieve this goal, the crustal structure under the Bighorn Mountain range, Bighorn Basin, and Powder River Basin of northern Wyoming and southern Montana are investigated through the deployment of 35 broadband seismometers, 200 short period seismometers, 1600 “Texan” instruments using active sources and 800 “Texan” instruments monitoring passive sources, together with field structural analysis of brittle structures. The novel combination of these approaches and anticipated simultaneous data inversion will give a detailed structural crustal image of the Bighorn region at all levels of the crust. Four models have been proposed for the formation of the Bighorn foreland arch: subhorizontal detachment within the crust, lithospheric buckling, pure shear lithospheric thickening, and fault blocks defined by lithosphere-penetrating thrust faults. During the summer of 2009, we deployed 35 broadband instruments, which have already recorded several magnitude 7+ teleseismic events. Through P wave receiver function analysis of these 35 stations folded in with many EarthScope Transportable Array stations in the region, we present a preliminary map of the Mohorovicic discontinuity. This crustal map is our first test of how the unique Moho geometries predicted by the four hypothesized models of basement involved arches fit seismic observations for the Bighorn Mountains. In addition, shear-wave splitting analysis for our first few recorded teleseisms helps us determine if strong lithospheric deformation is preserved under the range. These analyses help lead us to our final goal, a complete 4D (3D spatial plus temporal) lithospheric-scale model of arch formation which will advance our understanding of the mechanisms

  4. Structural Analysis of Sandwich Foam Panels

    Energy Technology Data Exchange (ETDEWEB)

    Kosny, Jan [ORNL; Huo, X. Sharon [Tennessee Technological University

    2010-04-01

    The Sandwich Panel Technologies including Structural Insulated Panels (SIPs) can be used to replace the conventional wooden-frame construction method. The main purpose of this Cooperative Research and Development Agreement (CRADA) between UT-Battelle, LLC and SGI Venture, Inc. was to design a novel high R-value type of metal sandwich panelized technology. This CRADA project report presents design concept discussion and numerical analysis results from thermal performance study of this new building envelope system. The main objective of this work was to develop a basic concept of a new generation of wall panel technologies which will have R-value over R-20 will use thermal mass to improve energy performance in cooling dominated climates and will be 100% termite resistant. The main advantages of using sandwich panels are as follows: (1) better energy saving structural panels with high and uniform overall wall R-value across the elevation that could not be achieved in traditional walls; and (2) reducing the use of raw materials or need for virgin lumber. For better utilization of these Sandwich panels, engineers need to have a thorough understanding of the actual performance of the panels and system. Detailed analysis and study on the capacities and deformation of individual panels and its assembly have to be performed to achieve that goal. The major project activity was to conduct structural analysis of the stresses, strains, load capacities, and deformations of individual sandwich components under various load cases. The analysis simulated the actual loading conditions of the regular residential building and used actual material properties of the steel facings and foam.

  5. Molecular Eigensolution Symmetry Analysis and Fine Structure

    Directory of Open Access Journals (Sweden)

    William G. Harter

    2013-01-01

    Full Text Available Spectra of high-symmetry molecules contain fine and superfine level cluster structure related to J-tunneling between hills and valleys on rovibronic energy surfaces (RES. Such graphic visualizations help disentangle multi-level dynamics, selection rules, and state mixing effects including widespread violation of nuclear spin symmetry species. A review of RES analysis compares it to that of potential energy surfaces (PES used in Born-Oppenheimer approximations. Both take advantage of adiabatic coupling in order to visualize Hamiltonian eigensolutions. RES of symmetric and D2 asymmetric top rank-2-tensor Hamiltonians are compared with Oh spherical top rank-4-tensor fine-structure clusters of 6-fold and 8-fold tunneling multiplets. Then extreme 12-fold and 24-fold multiplets are analyzed by RES plots of higher rank tensor Hamiltonians. Such extreme clustering is rare in fundamental bands but prevalent in hot bands, and analysis of its superfine structure requires more efficient labeling and a more powerful group theory. This is introduced using elementary examples involving two groups of order-6 (C6 and D3~C3v, then applied to families of Oh clusters in SF6 spectra and to extreme clusters.

  6. Structural dynamic analysis of composite beams

    Science.gov (United States)

    Suresh, J. K.; Venkatesan, C.; Ramamurti, V.

    1990-12-01

    In the treatment of the structural dynamic problem of composite materials, two alternate types of formulations, based on the elastic modulus and compliance quantities, exist in the literature. The definitions of the various rigidities are observed to differ in these two approaches. Following these two types of formulation, the structural dynamic characteristics of a composite beam are analyzed. The results of the analysis are compared with those available in the literature. Based on the comparison, the influence of the warping function in defining the coupling terms in the modulus approach and also on the natural frequencies of the beam has been identified. It is found from the analysis that, in certain cases, the difference between the results of the two approaches is appreciable. These differences may be attributed to the constraints imposed on the deformation and flexibility of the beam by the choice of the description of the warping behaviour. Finally, the influence of material properties on the structural dynamic characteristics of the beam is studied for different composites for various angles of orthotropy.

  7. Nonlinear frequency response analysis of structural vibrations

    Science.gov (United States)

    Weeger, Oliver; Wever, Utz; Simeon, Bernd

    2014-12-01

    In this paper we present a method for nonlinear frequency response analysis of mechanical vibrations of 3-dimensional solid structures. For computing nonlinear frequency response to periodic excitations, we employ the well-established harmonic balance method. A fundamental aspect for allowing a large-scale application of the method is model order reduction of the discretized equation of motion. Therefore we propose the utilization of a modal projection method enhanced with modal derivatives, providing second-order information. For an efficient spatial discretization of continuum mechanics nonlinear partial differential equations, including large deformations and hyperelastic material laws, we employ the concept of isogeometric analysis. Isogeometric finite element methods have already been shown to possess advantages over classical finite element discretizations in terms of higher accuracy of numerical approximations in the fields of linear vibration and static large deformation analysis. With several computational examples, we demonstrate the applicability and accuracy of the modal derivative reduction method for nonlinear static computations and vibration analysis. Thus, the presented method opens a promising perspective on application of nonlinear frequency analysis to large-scale industrial problems.

  8. SUPPORT VECTOR MACHINE FOR STRUCTURAL RELIABILITY ANALYSIS

    Institute of Scientific and Technical Information of China (English)

    LI Hong-shuang; L(U) Zhen-zhou; YUE Zhu-feng

    2006-01-01

    Support vector machine (SVM) was introduced to analyze the reliability of the implicit performance function, which is difficult to implement by the classical methods such as the first order reliability method (FORM) and the Monte Carlo simulation (MCS). As a classification method where the underlying structural risk minimization inference rule is employed, SVM possesses excellent learning capacity with a small amount of information and good capability of generalization over the complete data. Hence,two approaches, i.e., SVM-based FORM and SVM-based MCS, were presented for the structural reliability analysis of the implicit limit state function. Compared to the conventional response surface method (RSM) and the artificial neural network (ANN), which are widely used to replace the implicit state function for alleviating the computation cost,the more important advantages of SVM are that it can approximate the implicit function with higher precision and better generalization under the small amount of information and avoid the "curse of dimensionality". The SVM-based reliability approaches can approximate the actual performance function over the complete sampling data with the decreased number of the implicit performance function analysis (usually finite element analysis), and the computational precision can satisfy the engineering requirement, which are demonstrated by illustrations.

  9. Fiber structural analysis by synchrotron radiation

    CERN Document Server

    Kojima, J I; Kikutani, T

    2003-01-01

    Topics of fiber structural analysis by synchrotron radiation are explained. There are only three synchrotron radiation facilities in the world, SPring-8 (Super Photon ring-8) in Japan, APS (Advanced Photon Source) in U.S.A. and ESRF (European Synchrotron Radiation Facility) in France. Online measurement of melt spinning process of PET and Nylon6 is explained in detail. Polypropylene and PBO (poly-p-phenylenebenzobisoxazole) was measured by WAXD (Wide Angle X-ray Diffraction)/SAXS (Small Angle X-ray Scattering) at the same time. Some examples of measure of drawing process of fiber are described. The structure formation process of spider's thread was measured. Micro beam of X-ray of synchrotron facility was improved and it attained to 65nm small angle resolving power by 10 mu m beamsize. (S.Y.)

  10. Probabilistic analysis of linear elastic cracked structures

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    This paper presents a probabilistic methodology for linear fracture mechanics analysis of cracked structures. The main focus is on probabilistic aspect related to the nature of crack in material. The methodology involves finite element analysis; statistical models for uncertainty in material properties, crack size, fracture toughness and loads; and standard reliability methods for evaluating probabilistic characteristics of linear elastic fracture parameter. The uncertainty in the crack size can have a significant effect on the probability of failure, particularly when the crack size has a large coefficient of variation. Numerical example is presented to show that probabilistic methodology based on Monte Carlo simulation provides accurate estimates of failure probability for use in linear elastic fracture mechanics.

  11. Rhetorical structure theory and text analysis

    Science.gov (United States)

    Mann, William C.; Matthiessen, Christian M. I. M.; Thompson, Sandra A.

    1989-11-01

    Recent research on text generation has shown that there is a need for stronger linguistic theories that tell in detail how texts communicate. The prevailing theories are very difficult to compare, and it is also very difficult to see how they might be combined into stronger theories. To make comparison and combination a bit more approachable, we have created a book which is designed to encourage comparison. A dozen different authors or teams, all experienced in discourse research, are given exactly the same text to analyze. The text is an appeal for money by a lobbying organization in Washington, DC. It informs, stimulates and manipulates the reader in a fascinating way. The joint analysis is far more insightful than any one team's analysis alone. This paper is our contribution to the book. Rhetorical Structure Theory (RST), the focus of this paper, is a way to account for the functional potential of text, its capacity to achieve the purposes of speakers and produce effects in hearers. It also shows a way to distinguish coherent texts from incoherent ones, and identifies consequences of text structure.

  12. 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.

  13. 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.

  14. APPLICATIONS OF SURFACE SPLINEFUNCTIONS TO STRUCTURAL ANALYSIS IN COAL GEOLOGY

    Institute of Scientific and Technical Information of China (English)

    HanJinyan; YuZhiwei

    1996-01-01

    A surface spline function is used to fit a coal seam surface in structural analysis in coal geology. From the surface spline function, the first and second partial derivatives can also be derived and used to structural analysis, especially for recognition of the concealed structures. The detection of structures related to faulting is emphasized.

  15. Structured analysis and modeling of complex systems

    Science.gov (United States)

    Strome, David R.; Dalrymple, Mathieu A.

    1992-01-01

    The Aircrew Evaluation Sustained Operations Performance (AESOP) facility at Brooks AFB, Texas, combines the realism of an operational environment with the control of a research laboratory. In recent studies we collected extensive data from the Airborne Warning and Control Systems (AWACS) Weapons Directors subjected to high and low workload Defensive Counter Air Scenarios. A critical and complex task in this environment involves committing a friendly fighter against a hostile fighter. Structured Analysis and Design techniques and computer modeling systems were applied to this task as tools for analyzing subject performance and workload. This technology is being transferred to the Man-Systems Division of NASA Johnson Space Center for application to complex mission related tasks, such as manipulating the Shuttle grappler arm.

  16. Purification and Structural Analysis of Desmoplakin.

    Science.gov (United States)

    Choi, Hee-Jung; Weis, William I

    2016-01-01

    Desmoplakin (DP) is an obligate component of desmosomes, where it links the desmosomal cadherin/plakoglobin/plakophilin assembly to intermediate filaments. DP contains a large amino-terminal domain (DPNT) that binds to the cadherin/plakoglobin/plakophilin complex, a central coiled-coil domain that dimerizes the molecule, and a C-terminal domain (DPCT) that binds to intermediate filaments. DPNT contains a plakin domain, comprising a set of spectrin-like repeats. DPCT contains three plakin repeat domains, each formed by 4.5 repeats of a sequence motif known as a plakin repeat that bind to intermediate filaments. Here, we review purification, biochemical characterization, and structural analysis of the DPNT plakin domain and the DPCT plakin repeat domains.

  17. A DECOMPOSITION METHOD OF STRUCTURAL DECOMPOSITION ANALYSIS

    Institute of Scientific and Technical Information of China (English)

    LI Jinghua

    2005-01-01

    Over the past two decades,structural decomposition analysis(SDA)has developed into a major analytical tool in the field of input-output(IO)techniques,but the method was found to suffer from one or more of the following problems.The decomposition forms,which are used to measure the contribution of a specific determinant,are not unique due to the existence of a multitude of equivalent forms,irrational due to the weights of different determinants not matching,inexact due to the existence of large interaction terms.In this paper,a decomposition method is derived to overcome these deficiencies,and we prove that the result of this approach is equal to the Shapley value in cooperative games,and so some properties of the method are obtained.Beyond that,the two approaches that have been used predominantly in the literature have been proved to be the approximate solutions of the method.

  18. Decision variables analysis for structured modeling

    Institute of Scientific and Technical Information of China (English)

    潘启树; 赫东波; 张洁; 胡运权

    2002-01-01

    Structured modeling is the most commonly used modeling method, but it is not quite addaptive to significant changes in environmental conditions. Therefore, Decision Variables Analysis(DVA), a new modelling method is proposed to deal with linear programming modeling and changing environments. In variant linear programming , the most complicated relationships are those among decision variables. DVA classifies the decision variables into different levels using different index sets, and divides a model into different elements so that any change can only have its effect on part of the whole model. DVA takes into consideration the complicated relationships among decision variables at different levels, and can therefore sucessfully solve any modeling problem in dramatically changing environments.

  19. Inelastic analysis of solids and structures

    CERN Document Server

    Kojic, M; Bathe, K J; Koji?, Milo

    2005-01-01

    Inelastic Analysis of Solids and Structures presents in a unified manner the physical and theoretical background of inelastic material models and computational methods, and illustrates the behavior of the models in typical engineering conditions.It is based on experimental observations and principles of mechanics, thus describing computational algorithms for stress calculation and presenting solved examples.The theoretical background is given to an extent necessary to describe the commonly employed material models in metal isotropic and orthotropic plasticity, thermoplasticity and viscoplasticity, and the plasticity of geological materials.The computational algorithms are developed in a unified manner with some detailed derivations of the algorithmic relations.The solved examples are designed to give insight into the material behavior in various engineering conditions, and to demonstrate the application of the computational algorithms.

  20. Isogeometric analysis in electronic structure calculations

    CERN Document Server

    Cimrman, Robert; Kolman, Radek; Tůma, Miroslav; Vackář, Jiří

    2016-01-01

    In electronic structure calculations, various material properties can be obtained by means of computing the total energy of a system as well as derivatives of the total energy w.r.t. atomic positions. The derivatives, also known as Hellman-Feynman forces, require, because of practical computational reasons, the discretized charge density and wave functions having continuous second derivatives in the whole solution domain. We describe an application of isogeometric analysis (IGA), a spline modification of finite element method (FEM), to achieve the required continuity. The novelty of our approach is in employing the technique of B\\'ezier extraction to add the IGA capabilities to our FEM based code for ab-initio calculations of electronic states of non-periodic systems within the density-functional framework, built upon the open source finite element package SfePy. We compare FEM and IGA in benchmark problems and several numerical results are presented.

  1. Structural analysis of nucleosomal barrier to transcription.

    Science.gov (United States)

    Gaykalova, Daria A; Kulaeva, Olga I; Volokh, Olesya; Shaytan, Alexey K; Hsieh, Fu-Kai; Kirpichnikov, Mikhail P; Sokolova, Olga S; Studitsky, Vasily M

    2015-10-27

    Thousands of human and Drosophila genes are regulated at the level of transcript elongation and nucleosomes are likely targets for this regulation. However, the molecular mechanisms of formation of the nucleosomal barrier to transcribing RNA polymerase II (Pol II) and nucleosome survival during/after transcription remain unknown. Here we show that both DNA-histone interactions and Pol II backtracking contribute to formation of the barrier and that nucleosome survival during transcription likely occurs through allosterically stabilized histone-histone interactions. Structural analysis indicates that after Pol II encounters the barrier, the enzyme backtracks and nucleosomal DNA recoils on the octamer, locking Pol II in the arrested state. DNA is displaced from one of the H2A/H2B dimers that remains associated with the octamer. The data reveal the importance of intranucleosomal DNA-protein and protein-protein interactions during conformational changes in the nucleosome structure on transcription. Mechanisms of nucleosomal barrier formation and nucleosome survival during transcription are proposed.

  2. Steerable wavelet analysis of CMB structures alignment

    CERN Document Server

    Vielva, P; Martínez-González, E; Vandergheynst, P

    2006-01-01

    This paper reviews the application of a novel methodology for analysing the isotropy of the universe by probing the alignment of local structures in the CMB. The strength of the proposed methodology relies on the steerable wavelet filtering of the CMB signal. One the one hand, the filter steerability renders the computation of the local orientation of the CMB features affordable in terms of computation time. On the other hand, the scale-space nature of the wavelet filtering allows to explore the alignment of the local structures at different scales, probing possible different phenomena. We present the WMAP first-year data analysis recently performed by the same authors (Wiaux et al.), where an extremely significant anisotropy was found. In particular, a preferred plane was detected, having a normal direction with a northern end position close to the northern end of the CMB dipole axis. In addition, a most preferred direction was found in that plane, with a northern end direction very close to the north eclipt...

  3. Empirical analysis between industrial structure and economic growth of china

    Institute of Scientific and Technical Information of China (English)

    姚西龙; 尤津; 郝鹏飞

    2008-01-01

    In recent years,the relationship between the industrial structure and economic growth is more and more concerned by scholars. According to the theory of industrial structure and economic development, this article use regression analysis method that estimates the three major industries’ contribute to Chinese economic growth and use cluster analysis methods, then discuss how to optimize the indus-trial structure.

  4. Genome-scale reconstruction of Escherichia coli's transcriptional and translational machinery: a knowledge base, its mathematical formulation, and its functional characterization.

    Directory of Open Access Journals (Sweden)

    Ines Thiele

    2009-03-01

    Full Text Available Metabolic network reconstructions represent valuable scaffolds for '-omics' data integration and are used to computationally interrogate network properties. However, they do not explicitly account for the synthesis of macromolecules (i.e., proteins and RNA. Here, we present the first genome-scale, fine-grained reconstruction of Escherichia coli's transcriptional and translational machinery, which produces 423 functional gene products in a sequence-specific manner and accounts for all necessary chemical transformations. Legacy data from over 500 publications and three databases were reviewed, and many pathways were considered, including stable RNA maturation and modification, protein complex formation, and iron-sulfur cluster biogenesis. This reconstruction represents the most comprehensive knowledge base for these important cellular functions in E. coli and is unique in its scope. Furthermore, it was converted into a mathematical model and used to: (1 quantitatively integrate gene expression data as reaction constraints and (2 compute functional network states, which were compared to reported experimental data. For example, the model predicted accurately the ribosome production, without any parameterization. Also, in silico rRNA operon deletion suggested that a high RNA polymerase density on the remaining rRNA operons is needed to reproduce the reported experimental ribosome numbers. Moreover, functional protein modules were determined, and many were found to contain gene products from multiple subsystems, highlighting the functional interaction of these proteins. This genome-scale reconstruction of E. coli's transcriptional and translational machinery presents a milestone in systems biology because it will enable quantitative integration of '-omics' datasets and thus the study of the mechanistic principles underlying the genotype-phenotype relationship.

  5. Analysis of single nucleotide polymorphisms based on RNA sequencing data of diverse bio-geographical accessions in barley

    Science.gov (United States)

    Takahagi, Kotaro; Uehara-Yamaguchi, Yukiko; Yoshida, Takuhiro; Sakurai, Tetsuya; Shinozaki, Kazuo; Mochida, Keiichi; Saisho, Daisuke

    2016-01-01

    Barley is one of the founder crops of Old world agriculture and has become the fourth most important cereal worldwide. Information on genome-scale DNA polymorphisms allows elucidating the evolutionary history behind domestication, as well as discovering and isolating useful genes for molecular breeding. Deep transcriptome sequencing enables the exploration of sequence variations in transcribed sequences; such analysis is particularly useful for species with large and complex genomes, such as barley. In this study, we performed RNA sequencing of 20 barley accessions, comprising representatives of several biogeographic regions and a wild ancestor. We identified 38,729 to 79,949 SNPs in the 19 domesticated accessions and 55,403 SNPs in the wild barley and revealed their genome-wide distribution using a reference genome. Genome-scale comparisons among accessions showed a clear differentiation between oriental and occidental barley populations. The results based on population structure analyses provide genome-scale properties of sub-populations grouped to oriental, occidental and marginal groups in barley. Our findings suggest that the oriental population of domesticated barley has genomic variations distinct from those in occidental groups, which might have contributed to barley’s domestication. PMID:27616653

  6. Analysis of latent structures in linear systems

    DEFF Research Database (Denmark)

    Høskuldsson, Agnar

    2004-01-01

    In chemometrics the emphasis is on latent structure models. The latent structure is the part of the data that the modeling task is based upon. This paper is addressing some fundamental issues, when latent structures are used. The paper consists of three parts. The first part is concerned defining...

  7. Structural Response Analysis under Dependent Variables Based on Probability Boxes

    National Research Council Canada - National Science Library

    Xiao, Z; Yang, G

    2015-01-01

      This paper considers structural response analysis when structural uncertainty parameters distribution cannot be specified precisely due to lack of information and there are complex dependencies in the variables...

  8. Development of numerical procedures for analysis of complex structures

    Science.gov (United States)

    Gupta, K. K.

    1984-01-01

    The paper is concerned with the development of novel numerical procedures for the solution of static, stability, free vibration and dynamic response analysis of large, complex practical structures. Thus, details of numerical algorithms evolved for dynamic analysis of usual non-rotating and also rotating structures as well as finite dynamic elements are presented in the paper. Furthermore, the article provides some description of a general-purpose computer program STARS specifically developed for efficient analysis of complex practical structures.

  9. Analysis of slender structures using mechanics of structure genome and open source codes

    Science.gov (United States)

    Liu, Xin

    Structural genome (SG) is the smallest mathematical building block that contains all constitutive information of a structure. SG is a bridge connecting the material microstructures and the macroscopic structural analysis, so mechanics of structure genome (MSG) is an approach that unifies micromechanics and structural mechanics. There are three types of SG: 1D SG, 2D SG and 3D SG depending on the heterogeneity of the original structure. Once the SG of a structure is identified, the effective properties for corresponding structures including beams, plates/shells, or 3D solids can be obtained by the homogenization analysis of the SG. These effective properties can be used for the macroscopic structural analysis. After macroscopic structural analysis, the global structural responses can be the input parameters to get the local displacements/stress/strain using dehomogenization analysis of the SG. The mechanics of structure genome is implemented in a general purpose composites software called SwiftComp(TM). Slender structures are widely used in various industries, such as civil, aerospace and structural engineering. Using MSG, a new structural analysis approach is used to study the slender structures. In order to let users easily get the access to the software using this approach, several open source codes have been modified and upgraded. Graphical user interface is built on Gmsh, and CalculiX is chosen as the structural solver. New beam elements have been added to CalculiX to make the better use of the capability of SwiftComp(TM). Both linear and quadratic beam elements for Euler-Bernoulli and Timoshenko beam models are derived. Several numerical models show that the results using MSG and its companion code SwiftComp(TM) agree well with the 3D finite element analysis. The MSG approach greatly simplified the modeling process while maintaining accuracy. Therefore, the MSG approach provides an alternative way to analyze structures, especially when the structures are

  10. Fourier Transform Infrared Spectroscopic Analysis of Protein Secondary Structures

    Institute of Scientific and Technical Information of China (English)

    Jilie KONG; Shaoning YU

    2007-01-01

    Infrared spectroscopy is one of the oldest and well established experimental techniques for the analysis of secondary structure of polypeptides and proteins. It is convenient, non-destructive, requires less sample preparation, and can be used under a wide variety of conditions. This review introduces the recent developments in Fourier transform infrared (FTIR) spectroscopy technique and its applications to protein structural studies. The experimental skills, data analysis, and correlations between the FTIR spectroscopic bands and protein secondary structure components are discussed. The applications of FTIR to the secondary structure analysis, conformational changes, structural dynamics and stability studies of proteins are also discussed.

  11. Optimal analysis of structures by concepts of symmetry and regularity

    CERN Document Server

    Kaveh, Ali

    2013-01-01

    Optimal analysis is defined as an analysis that creates and uses sparse, well-structured and well-conditioned matrices. The focus is on efficient methods for eigensolution of matrices involved in static, dynamic and stability analyses of symmetric and regular structures, or those general structures containing such components. Powerful tools are also developed for configuration processing, which is an important issue in the analysis and design of space structures and finite element models. Different mathematical concepts are combined to make the optimal analysis of structures feasible. Canonical forms from matrix algebra, product graphs from graph theory and symmetry groups from group theory are some of the concepts involved in the variety of efficient methods and algorithms presented. The algorithms elucidated in this book enable analysts to handle large-scale structural systems by lowering their computational cost, thus fulfilling the requirement for faster analysis and design of future complex systems. The ...

  12. Interval Analysis of the Finite Element Method for Stochastic Structures

    Institute of Scientific and Technical Information of China (English)

    刘长虹; 刘筱玲; 陈虬

    2004-01-01

    A random parameter can be transformed into an interval number in the structural analysis with the concept of the confidence interval. Hence, analyses of uncertain structural systems can be used in the traditional FEM software. In some cases, the amount of solutions in stochastic structures is nearly as many as that in the traditional structural problems. In addition, a new method to evaluate the failure probability of structures is presented for the needs of the modern engineering design.

  13. Crystal structure analysis of intermetallic compounds

    Science.gov (United States)

    Conner, R. A., Jr.; Downey, J. W.; Dwight, A. E.

    1968-01-01

    Study concerns crystal structures and lattice parameters for a number of new intermetallic compounds. Crystal structure data have been collected on equiatomic compounds, formed between an element of the Sc, Ti, V, or Cr group and an element of the Co or Ni group. The data, obtained by conventional methods, are presented in an easily usable tabular form.

  14. Liquefaction mathematical analysis for improvement structures stability

    Directory of Open Access Journals (Sweden)

    Azam Khodashenas Pelko

    2010-10-01

    Full Text Available The stability of any structure is possible if foundation is appropriately designed. The Bandar abbas is the largest and most important port of Iran, with high seismicity and occurring strong earthquakes in this territory, the soil mechanical properties of different parts of city have been selected as the subject of current research. The data relating to the design of foundation for improvement of structure at different layer of subsoil have been collected and, accordingly, soil mechanical properties have been evaluated. The results of laboratory experiments can be used for evaluation of geotechnical characteristics of urban area for development a region with high level of structural stability. Ultimately, a new method for calculation of liquefaction force is suggested. It is applicable for improving geotechnical and structure codes and also for reanalysis of structure stability of previously constructed buildings.

  15. Interrogating the druggable genome with structural informatics.

    Science.gov (United States)

    Hambly, Kevin; Danzer, Joseph; Muskal, Steven; Debe, Derek A

    2006-08-01

    Structural genomics projects are producing protein structure data at an unprecedented rate. In this paper, we present the Target Informatics Platform (TIP), a novel structural informatics approach for amplifying the rapidly expanding body of experimental protein structure information to enhance the discovery and optimization of small molecule protein modulators on a genomic scale. In TIP, existing experimental structure information is augmented using a homology modeling approach, and binding sites across multiple target families are compared using a clique detection algorithm. We report here a detailed analysis of the structural coverage for the set of druggable human targets, highlighting drug target families where the level of structural knowledge is currently quite high, as well as those areas where structural knowledge is sparse. Furthermore, we demonstrate the utility of TIP's intra- and inter-family binding site similarity analysis using a series of retrospective case studies. Our analysis underscores the utility of a structural informatics infrastructure for extracting drug discovery-relevant information from structural data, aiding researchers in the identification of lead discovery and optimization opportunities as well as potential "off-target" liabilities.

  16. Shielding structure analysis for LSDS facility

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Hong Yeop; Kim, Jeong Dong; Lee, Yong Deok; Kim, Ho Dong [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2014-05-15

    The nuclear material (Pyro, Spent nuclear fuel) itself and the target material to generate neutrons is the LSDS system for isotopic fissile assay release of high intensity neutron and gamma rays. This research was performed to shield from various strong radiation. A shielding evaluation was carried out with a facilities model of LSDS system. The MCNPX 2.5 code was used and a shielding evaluation was performed for the shielding structure and location. The radiation dose based on the hole structure and location of the wall was evaluated. The shielding evaluation was performed to satisfy the safety standard for a normal person (1 μSv/h) and to use enough interior space. The MCNPX2.5 code was used and a dose evaluation was performed for the location of the shielding material, shielding structure, and hole structure. The evaluation result differs according to the shielding material location. The dose rate was small when the shielding material was positioned at the center. The dose evaluation result regarding the location of the shielding material was applied to the facility and the shielding thickness was determined (In 50 cm + Borax 5 cm + Out 45cm). In the existing hole structure, the radiation leak is higher than the standard. A hole structure model to prevent leakage of radiation was proposed. The general public dose limit was satisfied when using the concrete reinforcement and a zigzag structure. The shielding result will be of help to the facility shielding optimization.

  17. Field distribution analysis in deflecting structures

    Energy Technology Data Exchange (ETDEWEB)

    Paramonov, V.V. [Joint Inst. for Nuclear Research, Moscow (Russian Federation)

    2013-02-15

    Deflecting structures are used now manly for bunch rotation in emittance exchange concepts, bunch diagnostics and to increase the luminosity. The bunch rotation is a transformation of a particles distribution in the six dimensional phase space. Together with the expected transformations, deflecting structures introduce distortions due to particularities - aberrations - in the deflecting field distribution. The distributions of deflecting fields are considered with respect to non linear additions, which provide emittance deteriorations during a transformation. The deflecting field is treated as combination of hybrid waves HE{sub 1} and HM{sub 1}. The criteria for selection and formation of deflecting structures with minimized level of aberrations are formulated and applied to known structures. Results of the study are confirmed by comparison with results of numerical simulations.

  18. Solid Propellant Grain Structural Integrity Analysis

    Science.gov (United States)

    1973-01-01

    The structural properties of solid propellant rocket grains were studied to determine the propellant resistance to stresses. Grain geometry, thermal properties, mechanical properties, and failure modes are discussed along with design criteria and recommended practices.

  19. LACTOFERRIN: ANALYSIS OF THE STRUCTURE PROFILE

    Directory of Open Access Journals (Sweden)

    Lilia Anghel

    2014-12-01

    Full Text Available The multitude of physiological processes in which the binding of iron ions takes part makes its mechanism worth investigating. The multiple sequence alignment method was applied to investigate the structure similarities of five lactoferrin X-ray crystallographic structures and outline the differences and similarities between lactoferrin and serum transferrin. The results of this study provide useful insights into the mechanism of iron-binding of lactoferrin protein molecule.

  20. Tools for analysis of Dirac structures on banach spaces

    NARCIS (Netherlands)

    Iftime, Orest V.; Sandovici, Adrian; Golo, Goran

    2005-01-01

    Power-conserving and Dirac structures are known as an approach to mathematical modeling of physical engineering systems. In this paper connections between Dirac structures and well known tools from standard functional analysis are presented. The analysis can be seen as a possible starting framework

  1. Structural analysis and functional characteristics of greenhouses in ...

    African Journals Online (AJOL)

    USER

    2010-05-24

    May 24, 2010 ... This study was carried out to determine the structural analysis and functional characteristics of the greenhouses ..... Duncan test results for mean separation of calculated stretch ratios, ... and Organic Fertilizers and Possible Effects in the Greenhouses of ... Structural analysis of greenhouses: A case study in.

  2. Method of morphological analysis of enterprise management organizational structure

    OpenAIRE

    Heorhiadi, N.; Iwaszczuk, N.; Vilhutska, R.

    2013-01-01

    The essence of the method of morphological analysis of enterprise management organizational structure is described in the article. Setting levels of morphological decomposition and specification of sets of elements are necessary for morphological analysis. Based on empirical research identified factors that influence the formation and use of enterprises management organizational structures.

  3. Using Event Structure Analysis to Understand Planned Social Change

    Directory of Open Access Journals (Sweden)

    William Stevenson

    2003-06-01

    Full Text Available In this article, the authors explore the application of Event Structure Analysis in understanding the linkages between events in planned social change. An illustrative example from the Comprehensive Strategy for Serious, Violent and Chronic Juvenile Offenders is used to highlight the key features of Event Structure Analysis.

  4. Shear Effects in Shakedown Analysis of Offshore Structures

    Institute of Scientific and Technical Information of China (English)

    M.J.Fadaee; H.Saffari; R.Tabatabaei

    2008-01-01

    In this paper, a formulation for shakedown analysis of elastic-plastic offshore structures under cyclic wave loading is presented. In this formulation, a fast numerical solution method is used, suitable for the Finite Element Method (FEM) analysis of large offshore structures on which shear effects in addition to bending and axial effects are taken into account. The Morison equation is adopted for converting the velocity and acceleration terms into resultant forces and it is extended to consider arbitrary orientations of the structural members. The theoretical methods of the shakedown analysis are discussed in detail and the formulation is applied to an offshore structure to verify the concept employed and its analytical capabilities.

  5. Structural analysis with the finite element method linear statics

    CERN Document Server

    Oñate, Eugenio

    2013-01-01

    STRUCTURAL ANALYSIS WITH THE FINITE ELEMENT METHOD Linear Statics Volume 1 : The Basis and Solids Eugenio Oñate The two volumes of this book cover most of the theoretical and computational aspects of the linear static analysis of structures with the Finite Element Method (FEM). The content of the book is based on the lecture notes of a basic course on Structural Analysis with the FEM taught by the author at the Technical University of Catalonia (UPC) in Barcelona, Spain for the last 30 years. Volume1 presents the basis of the FEM for structural analysis and a detailed description of the finite element formulation for axially loaded bars, plane elasticity problems, axisymmetric solids and general three dimensional solids. Each chapter describes the background theory for each structural model considered, details of the finite element formulation and guidelines for the application to structural engineering problems. The book includes a chapter on miscellaneous topics such as treatment of inclined supports, elas...

  6. Stochastic Fatigue Analysis of Jacket Type Offshore Structures

    DEFF Research Database (Denmark)

    Sigurdsson, Gudfinnur

    In this paper, a stochastic reliability assessment for jacket type offshore structures subjected to wave loads in deep water environments is outlined. In the reliability assessment, structural and loading uncertainties are taken into account by means of some stochastic variables. To estimate...... statistical measures of structural stress variations the modal spectral analysis method is applied....

  7. Probabilistic structural analysis algorithm development for computational efficiency

    Science.gov (United States)

    Wu, Y.-T.

    1991-01-01

    The PSAM (Probabilistic Structural Analysis Methods) program is developing a probabilistic structural risk assessment capability for the SSME components. An advanced probabilistic structural analysis software system, NESSUS (Numerical Evaluation of Stochastic Structures Under Stress), is being developed as part of the PSAM effort to accurately simulate stochastic structures operating under severe random loading conditions. One of the challenges in developing the NESSUS system is the development of the probabilistic algorithms that provide both efficiency and accuracy. The main probability algorithms developed and implemented in the NESSUS system are efficient, but approximate in nature. In the last six years, the algorithms have improved very significantly.

  8. Unascertained Factor Method of Dynamic Characteristic Analysis for Antenna Structures

    Institute of Scientific and Technical Information of China (English)

    ZHU Zeng-qing; LIANG Zhen-tao; CHEN Jian-jun

    2008-01-01

    The dynamic characteristic analysis model of antenna structures is built, in which the structural physical parameters and geometrical dimensions are all considered as unascertained variables, And a structure dynamic characteristic analysis method based on the unascertained factor method is given. The computational expression of structural characteristic is developed by the mathematics expression of unascertained factor and the principles of unascertained rational numbers arithmetic. An example is given, in which the possible values and confidence degrees of the unascertained structure characteristics are obtained. The calculated results show that the method is feasible and effective.

  9. Meta-analysis a structural equation modeling approach

    CERN Document Server

    Cheung, Mike W-L

    2015-01-01

    Presents a novel approach to conducting meta-analysis using structural equation modeling. Structural equation modeling (SEM) and meta-analysis are two powerful statistical methods in the educational, social, behavioral, and medical sciences. They are often treated as two unrelated topics in the literature. This book presents a unified framework on analyzing meta-analytic data within the SEM framework, and illustrates how to conduct meta-analysis using the metaSEM package in the R statistical environment. Meta-Analysis: A Structural Equation Modeling Approach begins by introducing the impo

  10. Correct use of Membrane Elements in Structural Analysis

    Directory of Open Access Journals (Sweden)

    Rothman Timothy

    2016-01-01

    Full Text Available Structural analysis of consumer electronic devices such as phones and tablets involves Finite Element Analysis (FEA. Dynamic loading conditions such as device dropping and bending dictate accurate FEA models to reduce design risk in many areas. The solid elements typically used in structural analysis do not have integration points on the surface. The outer surface is of most interest because that is where the cracks start. Analysts employ a post processing trick through using membranes to bring accurate stress/strain results to the surface. This paper explains numerical issues with implementation of membranes and recommends a methodology for accurate structural analysis.

  11. Rapid Electromagnetic Analysis of Entire Accelerator Structures

    CERN Document Server

    Cooke, Simon

    2005-01-01

    We present results of a new method for fast, accurate calculation, in 3-D, of the electromagnetic mode spectrum of long, tapered accelerator structures. Instead of discretizing the entire structure directly and solving a huge matrix eigenvalue problem, we use a new two-step technique that scales much better to long, multi-cavity structures. In the first step we compute a small number of eigenmodes of individual cavities, achieving 0.05% frequency accuracy using a new second-order finite-element code. In the second step we use these 3-D mode solutions as field basis functions to obtain a reduced matrix representation of Maxwell's equations for the complete structure. Solving the reduced system takes just a few minutes on a desktop PC even with more than 100 non-identical cavities, and gives the complete mode spectrum in the first few bands of the structure. By judicious choice of the basis modes, we retain 0.05% frequency accuracy for these global solutions, and can reconstruct the complete 3-D field of each m...

  12. Earthquake analysis of structures using nonlinear models

    OpenAIRE

    Cemalovic, Miran

    2015-01-01

    Throughout the governing design codes, several different methods are presented for the evaluation of seismic problems. This thesis assesses the non-linear static and dynamic procedures presented in EN 1998-1 through the structural response of a RC wall-frame building. The structure is designed in detail according to the guidelines for high ductility (DCH) in EN 1998-1. The applied procedures are meticulously evaluated and the requirements in EN 1998-1 are reviewed. In addition, the finite ele...

  13. Exact analysis of bi-periodic structures

    CERN Document Server

    Cai, C W; Chan, H C

    2002-01-01

    By using the U-transformation method, it is possible to uncouple linear simultaneous equations, either algebraic or differential, with cyclic periodicity. This book presents a procedure for applying the U-transformation technique twice to uncouple the two sets of unknown variables in a doubly periodic structure to achieve an analytical exact solution. Explicit exact solutions for the static and dynamic analyses for certain engineering structures with doubly periodic properties - such as a continuous truss with any number of spans, cable network and grillwork on supports with periodicity, and g

  14. ROLE OF UNDERGROUND STRUCTURE DEFORMATION VELOCITY IN THE ANALYSIS OF BLAST-RESISTANT STRUCTURES

    Institute of Scientific and Technical Information of China (English)

    赵晓兵; 方秦

    2002-01-01

    The structural deformation velocity plays a significant role in the dynamic calculation of underground blast-resistant structures. The motion differentiating equation of a structure system taking into account the role of deformation velocity of the structure will truthfully describe the actual situation of structural vibration. With the one-dimensional plane wave theory, the expression of load on the structural periphery is developed, and the generalized variation principle for the dynamic analysis of underground arched-bar structures is given. At the same time, the results of the numerical calculation are compared.

  15. 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.

  16. Structural Analysis Extended with Active Fault Isolation - Methods and Algorithms

    DEFF Research Database (Denmark)

    Gelso, Esteban R.; Blanke, Mogens

    2009-01-01

    on system inputs can considerably enhance fault isolability. This paper investigates this possibility of active fault isolation from a structural point of view. While such extension of the structural analysis approach was suggested earlier, algorithms and case studies were needed to explore this theory....... The paper develops algorithms for investigation of the possibilities of active structural isolation and it offers illustrative examples and a larger case study to explore the properties of active structural isolability ideas....

  17. Earthquake Analysis of Structure by Base Isolation Technique in SAP

    OpenAIRE

    T. Subramani; J. Jothi

    2014-01-01

    This paper presents an overview of the present state of base isolation techniques with special emphasis and a brief on other techniques developed world over for mitigating earthquake forces on the structures. The dynamic analysis procedure for isolated structures is briefly explained. The provisions of FEMA 450 for base isolated structures are highlighted. The effects of base isolation on structures located on soft soils and near active faults are given in brief. Simple case s...

  18. Total-System Approach To Design And Analysis Of Structures

    Science.gov (United States)

    Verderaime, V.

    1995-01-01

    Paper presents overview and study of, and comprehensive approach to, multidisciplinary engineering design and analysis of structures. Emphasizes issues related to design of semistatic structures in environments in which spacecraft launched, underlying concepts applicable to other structures within unique terrestrial, marine, or flight environments. Purpose of study to understand interactions among traditionally separate engineering design disciplines with view toward optimizing not only structure but also overall design process.

  19. RNA structural analysis by evolving SHAPE chemistry.

    Science.gov (United States)

    Spitale, Robert C; Flynn, Ryan A; Torre, Eduardo A; Kool, Eric T; Chang, Howard Y

    2014-01-01

    RNA is central to the flow of biological information. From transcription to splicing, RNA localization, translation, and decay, RNA is intimately involved in regulating every step of the gene expression program, and is thus essential for health and understanding disease. RNA has the unique ability to base-pair with itself and other nucleic acids to form complex structures. Hence the information content in RNA is not simply its linear sequence of bases, but is also encoded in complex folding of RNA molecules. A general chemical functionality that all RNAs have is a 2'-hydroxyl group in the ribose ring, and the reactivity of the 2'-hydroxyl in RNA is gated by local nucleotide flexibility. In other words, the 2'-hydroxyl is reactive at single-stranded and conformationally flexible positions but is unreactive at nucleotides constrained by base-pairing. Recent efforts have been focused on developing reagents that modify RNA as a function of RNA 2' hydroxyl group reactivity. Such RNA structure probing techniques can be read out by primer extension in experiments termed RNA SHAPE (selective 2'- hydroxyl acylation and primer extension). Herein, we describe the efforts devoted to the design and utilization of SHAPE probes for characterizing RNA structure. We also describe current technological advances that are being applied to utilize SHAPE chemistry with deep sequencing to probe many RNAs in parallel. The merging of chemistry with genomics is sure to open the door to genome-wide exploration of RNA structure and function.

  20. Failure Analysis of Composite Structure Materials.

    Science.gov (United States)

    1986-05-01

    8MATERIAL STRUCTURES DISCONTINUITY T•R PLY DROPOFF i 7ARC LAP/GAP . PRPAATION A, ,OM LY , 1e, ’ •INS ERVICE MAINTENANCE DAMAGE SVv , S IMPACT \\\\ CHESIE ...composite joints such as box beam members, for example, are difficult to inspect by ultrasonic techniques, and the X-ray attenuation coefficients of

  1. Spatial Analysis Of Human Capital Structures

    Directory of Open Access Journals (Sweden)

    Gajdos Artur

    2014-12-01

    Full Text Available The main purpose of this paper is to analyse the interdependence between labour productivity and the occupational structure of human capital in a spatial cross-section. Research indicates (see Fischer 2009 the possibility to assess the impact of the quality of human capital (measured by means of the level of education on labour productivity in a spatial cross-section.

  2. RNA Structural Analysis by Evolving SHAPE Chemistry

    Science.gov (United States)

    Spitale, Robert C.; Flynn, Ryan A.; Torre, Eduardo A.; Kool, Eric T.; Chang, Howard Y.

    2017-01-01

    RNA is central to the flow of biological information. From transcription to splicing, RNA localization, translation, and decay, RNA is intimately involved in regulating every step of the gene expression program, and is thus essential for health and understanding disease. RNA has the unique ability to base-pair with itself and other nucleic acids to form complex structures. Hence the information content in RNA is not simply its linear sequence of bases, but is also encoded in complex folding of RNA molecules. A general chemical functionality that all RNAs have is a 2’-hydroxyl group in the ribose ring, and the reactivity of the 2'-hydroxyl in RNA is gated by local nucleotide flexibility. In other words, the 2'-hydroxyl is reactive at single-stranded and conformationally flexible positions but is unreactive at nucleotides constrained by base pairing. Recent efforts have been focused on developing reagents that modify RNA as a function of RNA 2’ hydroxyl group flexibility. Such RNA structure probing techniques can be read out by primer extension in experiments termed RNA SHAPE (Selective 2’ Hydroxyl Acylation and Primer Extension). Herein we describe the efforts devoted to the design and utilization of SHAPE probes for characterizing RNA structure. We also describe current technological advances that are being used to utilize SHAPE chemistry with deep sequencing to probe many RNAs in parallel. The merger of chemistry with genomics is sure to open the door to genome-wide exploration of RNA structure and function. PMID:25132067

  3. Stochastic finite element analysis of steel structures

    NARCIS (Netherlands)

    Waarts, P.H.; Vrouwenvelder, A.C.W.M.

    1999-01-01

    The paper describes two well known but adapted methods for calculating the probability of failure of structures. First the First Order Reliability Method (FORM) is described using an adapted response surface. Secondly the Directional Sampling (DS) procedure is described using truncated stochastic di

  4. Structure function analysis of mammalian cryptochromes

    NARCIS (Netherlands)

    F. Tamanini (Filippo); I. Chaves (Ines); M.I. Bajek (Monika); G.T.J. van der Horst (Gijsbertus)

    2007-01-01

    textabstractMembers of the photolyase/cryptochrome family are flavoproteins that share an extraordinary conserved core structure (photolyase homology region, PHR), but the presence of a carboxy-terminal extension is limited to the cryptochromes. Photolyases are DNA-repair enzymes that remove

  5. Reliability Analysis of an Offshore Structure

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Thoft-Christensen, Palle; Rackwitz, R.

    1992-01-01

    A jacket type offshore structure from the North Sea is considered. The time variant reliability is estimated for failure defined as brittie fradure and crack through the tubular roerober walls. The stochastic modeiling is described. The hot spot stress speetral moments as fundion of the stochastic...

  6. Structural Analysis of a Dragonfly Wing

    NARCIS (Netherlands)

    Jongerius, S.R.; Lentink, D.

    2010-01-01

    Dragonfly wings are highly corrugated, which increases the stiffness and strength of the wing significantly, and results in a lightweight structure with good aerodynamic performance. How insect wings carry aerodynamic and inertial loads, and how the resonant frequency of the flapping wings is tuned

  7. Design and analysis of composite structures with applications to aerospace structures

    CERN Document Server

    Kassapoglou, Christos

    2010-01-01

    Design and Analysis of Composite Structures enables graduate students and engineers to generate meaningful and robust designs of complex composite structures. Combining analysis and design methods for structural components, the book begins with simple topics such as skins and stiffeners and progresses through to entire components of fuselages and wings. Starting with basic mathematical derivation followed by simplifications used in real-world design, Design and Analysis of Composite Structures presents the level of accuracy and range of applicability of each method. Examples taken from ac

  8. SECOM: A novel hash seed and community detection based-approach for genome-scale protein domain identification

    KAUST Repository

    Fan, Ming

    2012-06-28

    With rapid advances in the development of DNA sequencing technologies, a plethora of high-throughput genome and proteome data from a diverse spectrum of organisms have been generated. The functional annotation and evolutionary history of proteins are usually inferred from domains predicted from the genome sequences. Traditional database-based domain prediction methods cannot identify novel domains, however, and alignment-based methods, which look for recurring segments in the proteome, are computationally demanding. Here, we propose a novel genome-wide domain prediction method, SECOM. Instead of conducting all-against-all sequence alignment, SECOM first indexes all the proteins in the genome by using a hash seed function. Local similarity can thus be detected and encoded into a graph structure, in which each node represents a protein sequence and each edge weight represents the shared hash seeds between the two nodes. SECOM then formulates the domain prediction problem as an overlapping community-finding problem in this graph. A backward graph percolation algorithm that efficiently identifies the domains is proposed. We tested SECOM on five recently sequenced genomes of aquatic animals. Our tests demonstrated that SECOM was able to identify most of the known domains identified by InterProScan. When compared with the alignment-based method, SECOM showed higher sensitivity in detecting putative novel domains, while it was also three orders of magnitude faster. For example, SECOM was able to predict a novel sponge-specific domain in nucleoside-triphosphatase (NTPases). Furthermore, SECOM discovered two novel domains, likely of bacterial origin, that are taxonomically restricted to sea anemone and hydra. SECOM is an open-source program and available at http://sfb.kaust.edu.sa/Pages/Software.aspx. © 2012 Fan et al.

  9. Structural Analysis Using NX Nastran 9.0

    Science.gov (United States)

    Rolewicz, Benjamin M.

    2014-01-01

    NX Nastran is a powerful Finite Element Analysis (FEA) software package used to solve linear and non-linear models for structural and thermal systems. The software, which consists of both a solver and user interface, breaks down analysis into four files, each of which are important to the end results of the analysis. The software offers capabilities for a variety of types of analysis, and also contains a respectable modeling program. Over the course of ten weeks, I was trained to effectively implement NX Nastran into structural analysis and refinement for parts of two missions at NASA's Kennedy Space Center, the Restore mission and the Orion mission.

  10. Seeking Development in the Succession-An Analysis of Saussure's Structuralism and Strauss' Cultural Structuralism

    Institute of Scientific and Technical Information of China (English)

    杨绍芳

    2009-01-01

    With an analysis of Saussure's linguistic structuralism and Strauss' cultural structuralism and exploration of their great impact on linguistic and cultural theory respectively, the author of this paper can safely draw the conclusion that "Saussure's perspective was to provide an intellectual seed that was to flower in later decades as structuralism became a general approach to the study of culture". Saussure, together

  11. Isogeometric analysis for thin-walled composite structures

    NARCIS (Netherlands)

    Guo, Y.

    2016-01-01

    The conceptual ideas behind isogeometric analysis (IGA) are aimed at unifying computer aided design (CAD) and finite element analysis (FEA). Isogeometric analysis employs the non-uniform rational B-spline functions (NURBS) used for the geometric description of a structure to approximate its physical

  12. Impact factors of fractal analysis of porous structure

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Characterization of pore structure is one of the key problems for fabrication and application research on porous materials. But, complexity of pore structure makes it difficult to characterize pore structure by Euclidean geometry and traditional experimental methods. Fractal theory has been proved effective to characterize the complex pore structure. The box dimension method based on fractal theory was applied to characterizing the pore structure of fiber porous materials by analyzing the electronic scanning microscope (SEM) images of the porous materials in this paper. The influences of image resolution, threshold value, and image magnification on fractal analysis were investigated. The results indicate that such factors greatly affect fractal analysis process and results. The appropriate magnification threshold and fractal analysis are necessary for fractal analysis.

  13. Large-scale structural analysis: The structural analyst, the CSM Testbed and the NAS System

    Science.gov (United States)

    Knight, Norman F., Jr.; Mccleary, Susan L.; Macy, Steven C.; Aminpour, Mohammad A.

    1989-01-01

    The Computational Structural Mechanics (CSM) activity is developing advanced structural analysis and computational methods that exploit high-performance computers. Methods are developed in the framework of the CSM testbed software system and applied to representative complex structural analysis problems from the aerospace industry. An overview of the CSM testbed methods development environment is presented and some numerical methods developed on a CRAY-2 are described. Selected application studies performed on the NAS CRAY-2 are also summarized.

  14. TRFBA: an algorithm to integrate genome-scale metabolic and transcriptional regulatory networks with incorporation of expression data.

    Science.gov (United States)

    Motamedian, Ehsan; Mohammadi, Maryam; Shojaosadati, Seyed Abbas; Heydari, Mona

    2017-04-01

    Integration of different biological networks and data-types has been a major challenge in systems biology. The present study introduces the transcriptional regulated flux balance analysis (TRFBA) algorithm that integrates transcriptional regulatory and metabolic models using a set of expression data for various perturbations. TRFBA considers the expression levels of genes as a new continuous variable and introduces two new linear constraints. The first constraint limits the rate of reaction(s) supported by a metabolic gene using a constant parameter (C) that converts the expression levels to the upper bounds of the reactions. Considering the concept of constraint-based modeling, the second set of constraints correlates the expression level of each target gene with that of its regulating genes. A set of constraints and binary variables was also added to prevent the second set of constraints from overlapping. TRFBA was implemented on Escherichia coli and Saccharomyces cerevisiae models to estimate growth rates under various environmental and genetic perturbations. The error sensitivity to the algorithm parameter was evaluated to find the best value of C. The results indicate a significant improvement in the quantitative prediction of growth in comparison with previously presented algorithms. The robustness of the algorithm to change in the expression data and the regulatory network was tested to evaluate the effect of noisy and incomplete data. Furthermore, the use of added constraints for perturbations without their gene expression profile demonstrates that these constraints can be applied to improve the growth prediction of FBA. TRFBA is implemented in Matlab software and requires COBRA toolbox. Source code is freely available at http://sbme.modares.ac.ir . : motamedian@modares.ac.ir. Supplementary data are available at Bioinformatics online.

  15. In Depth Analysis of Food Structures

    DEFF Research Database (Denmark)

    Nielsen, Otto Højager Attermann; Dahl, Anders Lindbjerg; Larsen, Rasmus

    2011-01-01

    In this paper we describe a computer vision system based on SLS (Subsurface Laser Scattering) for industrial food inspection. To ob- tain high and uniform quality, in for example dairy products like yoghurt and cheese, it is important to monitor the change in size and shape of microscopic particles...... over time. In this paper we demonstrate the use- fulness of our SLS system for characterizing food items. We use a laser source that can be tuned to any wavelength in the range of 455 nm - 1020 nm by applying an AOTF (Acousto-Optical Tunable Filter) to an optical beam generated by a Super......K (supercontinuum) laser system. In our experiments we show how the system can be used for discriminating dairy products with dierent structure and how the structural change of a foam can be monitored over time. Time stability of the system is essential for measurements over several hours, and we demonstrate...

  16. Truncated Moment Analysis of Nucleon Structure Functions

    Energy Technology Data Exchange (ETDEWEB)

    A. Psaker; W. Melnitchouk; M. E. Christy; C. E. Keppel

    2007-11-16

    We employ a novel new approach using "truncated" moments, or integrals of structure functions over restricted regions of x, to study local quark-hadron duality, and the degree to which individual resonance regions are dominated by leading twists. Because truncated moments obey the same Q^2 evolution equations as the leading twist parton distributions, this approach makes possible for the first time a description of resonance region data and the phenomenon of quark-hadron duality directly from QCD.

  17. Analysis and Synthesis of Robust Data Structures

    Science.gov (United States)

    1990-08-01

    1.3.2 Multiversion Software. .. .. .. .. .. .... .. ... .. ...... 5 1.3.3 Robust Data Structure .. .. .. .. .. .. .. .. .. ... .. ..... 6 1.4...context are 0 multiversion software, which is an adaptation oi N-modulo redundancy (NMR) tech- nique. * recovery blocks, which is an adaptation of...implementations using these features for such a hybrid approach. 1.3.2 Multiversion Software Avizienis [AC77] was the first to adapt NMR technique into

  18. Finite Element Analysis of Eutectic Structures

    Science.gov (United States)

    2014-03-12

    by solid state sintering . The microstructure can exhibit many geometrical forms: dendritic, lamellar, and rods. The self-assembled structure can be...Thermal data was measured in the temperature range of 373 to 1273 K by the laser flash method (Anter Flashline 5000, Anter Corporation, Pittsburgh, PA...therefore is not believed to alter thermal measurements significantly. Specimens were also coated with carbon 4 paint in accordance with standard flash

  19. Structural Analysis of a Dragonfly Wing

    OpenAIRE

    Jongerius, S.R.; Lentink, D.

    2010-01-01

    Dragonfly wings are highly corrugated, which increases the stiffness and strength of the wing significantly, and results in a lightweight structure with good aerodynamic performance. How insect wings carry aerodynamic and inertial loads, and how the resonant frequency of the flapping wings is tuned for carrying these loads, is however not fully understood. To study this we made a three-dimensional scan of a dragonfly (Sympetrum vulgatum) fore- and hindwing with a micro-CT scanner. The scans c...

  20. DNA sequence recognition by hybridization to short oligomers : experimental determination of accuracy of the method in a genome-scale search.

    Energy Technology Data Exchange (ETDEWEB)

    Milosavljevic, A.; Savkovic, S.; Crkvenjakov, R.; Salbego, D.; Serrato, H.; Kreuzer, H.; Gemmell, A.; Batus, S.; Grujic, D.; Carnahan, S.; Tepavcevic, J.; Center for Mechanistic Biology and Biotechnology

    1996-01-01

    Recently developed hybridization technology enables economical large-scale detection of short oligomers within DNA fragments. The newly developed recognition method enables comparison of lists of oligomers detected within DNA fragments against known DNA sequences. We here describe an experiment involving a set of 4513 distinct genomic E. coli clones of average length 2kb, each hybridized with 636 randomly selected short oligomer probes. High hybridization signal with a particular probe was used as an indication of the presence of a complementary oligomer in the particular clone. For each clone, a list of oligomers with highest hybridization signals was compiled. The database consisting of 4513 oligomer lists was then searched using known E. coli sequences as queries in an attempt to identify the clones that match the query sequence. Out of a total of 11 clones that were recognized at highest significance level by our method, 8 were single-pass sequenced from both ends. The single-pass sequenced ends were then compared against the query sequences. The sequence comparisons confirmed 7 out of the total of 8 examined recognitions. This experiment represents the first successful example of genome-scale sequence recognition based on hybridization data.

  1. Numerical Limit Analysis of Precast Concrete Structures

    DEFF Research Database (Denmark)

    Herfelt, Morten Andersen; Poulsen, Peter Noe; Hoang, Linh Cao

    2016-01-01

    optimisation as well as material optimisation is given and a four-storey shear wall is analysed using load optimisation. The analysis yields a capacity more than three times larger than the design load for the critical load case, and the collapse mode and stress distribution are analysed. Finally, numerical...

  2. Modal analysis of kagome-lattice structures

    Science.gov (United States)

    Perez, H.; Blakley, S.; Zheltikov, A. M.

    2015-05-01

    The first few lowest order circularly symmetric electromagnetic eigenmodes of a full kagome lattice are compared to those of a kagome lattice with a hexagonal defect. This analysis offers important insights into the physics behind the waveguiding properties of hollow-core fibers with a kagome-lattice cladding.

  3. Protein structure similarity from principle component correlation analysis

    Directory of Open Access Journals (Sweden)

    Chou James

    2006-01-01

    Full Text Available Abstract Background Owing to rapid expansion of protein structure databases in recent years, methods of structure comparison are becoming increasingly effective and important in revealing novel information on functional properties of proteins and their roles in the grand scheme of evolutionary biology. Currently, the structural similarity between two proteins is measured by the root-mean-square-deviation (RMSD in their best-superimposed atomic coordinates. RMSD is the golden rule of measuring structural similarity when the structures are nearly identical; it, however, fails to detect the higher order topological similarities in proteins evolved into different shapes. We propose new algorithms for extracting geometrical invariants of proteins that can be effectively used to identify homologous protein structures or topologies in order to quantify both close and remote structural similarities. Results We measure structural similarity between proteins by correlating the principle components of their secondary structure interaction matrix. In our approach, the Principle Component Correlation (PCC analysis, a symmetric interaction matrix for a protein structure is constructed with relationship parameters between secondary elements that can take the form of distance, orientation, or other relevant structural invariants. When using a distance-based construction in the presence or absence of encoded N to C terminal sense, there are strong correlations between the principle components of interaction matrices of structurally or topologically similar proteins. Conclusion The PCC method is extensively tested for protein structures that belong to the same topological class but are significantly different by RMSD measure. The PCC analysis can also differentiate proteins having similar shapes but different topological arrangements. Additionally, we demonstrate that when using two independently defined interaction matrices, comparison of their maximum

  4. Global Analysis and Structural Performance of the Tubed Mega Frame

    OpenAIRE

    Zhang, Han

    2014-01-01

    The Tubed Mega Frame is a new structure concept for high-rise buildings which is developed by Tyréns. In order to study the structural performance as well as the efficiency of this new concept, a global analysis of the Tubed Mega Frame structure is performed using finite element analysis software ETABS. Besides, the lateral loads that should be applied on the structure according to different codes are also studied. From the design code study for wind loads and seismic design response spectrum...

  5. Nonlinear dynamic analysis of quasi-symmetric anisotropic structures

    Science.gov (United States)

    Noor, Ahmed K.; Peters, Jeanne M.

    1987-01-01

    An efficient computational method for the nonlinear dynamic analysis of quasi-symmetric anisotropic structures is proposed. The application of mixed models simplifies the analytical development and improves the accuracy of the response predictions, and operator splitting allows the reduction of the analysis model of the quasi-symmetric structure to that of the corresponding symmetric structure. The preconditoned conjugate gradient provides a stable and effective technique for generating the unsymmetric response of the structure as the sum of a symmetrized response plus correction modes. The effectiveness of the strategy is demonstrated with the example of a laminated anisotropic shallow shell of quadrilateral planform subjected to uniform normal loading.

  6. Acoustic design sensitivity analysis of structural sound radiation

    Institute of Scientific and Technical Information of China (English)

    许智生

    2009-01-01

    This paper presents an acoustic design sensitivity(ADS)analysis on sound radiation of structures by using the boundary element method(BEM).We calculated the velocity distribution of the thin plate by analytical method and the surface sound pressure by Rayleigh integral,and expressed the sound radiation power of the structure in a positive definite quadratic form of the Hermitian with an impedance matrix.The ADS analysis of the plate was thus translated into the analysis of structure dynamic sensitivity and ...

  7. The dream of Irma's injection: a structural analysis.

    Science.gov (United States)

    Kuper, A; Stone, A A

    1982-10-01

    Lévi-Strauss developed a radically new, structural approach to the analysis of myth that may be adapted for use in the analysis of dreams. The method provides an alternative to psychoanalytic dream interpretation, focusing particularly on the internal dialectic of the dream--the movement from the initial premise to the resolution. This emphasis on the internal coherence and structured development of the dream contrasts strongly with the Freudian piecemeal decoding of dreams. The method is exemplified by analysis of Freud's classic Irma dream; it reveals a structure and message that have hitherto remained obscure. The interpretation connects the dream to Freud's theoretical ideas rather than to his supposed psychosexual fixations.

  8. ANOVA like analysis for structured families of stochastic matrices

    Science.gov (United States)

    Dias, Cristina; Santos, Carla; Varadinov, Maria; Mexia, João T.

    2016-12-01

    Symmetric stochastic matrices width a width a dominant eigenvalue λ and the corresponding eigenvector α appears in many applications. Such matrices can be written as M =λ α αt+E¯. Thus β = λ α will be the structure vector. When the matrices in such families correspond to the treatments of a base design we can carry out a ANOVA like analysis of the action of the treatments in the model on the structured vectors. This analysis can be transversal-when we worked width homologous components and - longitudinal when we consider contrast on the components of each structure vector. The analysis will be briefly considered at the end of our presentation.

  9. Protective Structure Backpacking and In-Structure Shock Isolation Systems Analysis and Design.

    Science.gov (United States)

    A parametric analysis is used to develop feasible backpacking -structure configurations and to determine the effect of backpacking on the responses of...the study determined the effectiveness of backpacking in attenuating the structure motions and in reducing the peak stresses and peak accelerations...in the structure. The second phase investigated the response of various shock isolation systems to structure input motions from preferred backpacking

  10. Molecular and structural analysis of viscoelastic properties

    Science.gov (United States)

    Yapp, Rebecca D.; Kalyanam, Sureshkumar; Insana, Michael F.

    2007-03-01

    Elasticity imaging is emerging as an important tool for breast cancer detection and monitoring of treatment. Viscoelastic image contrast in breast lesions is generated by disease specific processes that modify the molecular structure of connective tissues. We showed previously that gelatin hydrogels exhibit mechanical behavior similar to native collagen found in breast tissue and therefore are suitable as phantoms for elasticity imaging. This paper summarizes our study of the viscoelastic properties of hydrogels designed to discover molecular-scale sources of elasticity image contrast.

  11. Structural analysis of ITER multi-purpose deployer

    Energy Technology Data Exchange (ETDEWEB)

    Manuelraj, Manoah Stephen, E-mail: manoah@ipr.res.in [Institute for Plasma Research, Gandhinagar, Gujarat 382428 (India); Dutta, Pramit; Gotewal, Krishan Kumar; Rastogi, Naveen [Institute for Plasma Research, Gandhinagar, Gujarat 382428 (India); Tesini, Alessandro [ITER Organization, Route de Vinon-sur-Verdon, CS 90046, 1306 St Paul lez Durance Cedex (France); Choi, Chang-Hwan, E-mail: chang-hwan.choi@iter.org [ITER Organization, Route de Vinon-sur-Verdon, CS 90046, 1306 St Paul lez Durance Cedex (France)

    2016-11-01

    Highlights: • System modelling for structural analysis of the Multi-Purpose Deployer (MPD). • Finite element modeling of the Multi-Purpose Deployer (MPD). • Static, modal and seismic response analysis of the Multi-Purpose Deployer (MPD). • Iterative structural analysis and design update to satisfy the structural criteria. • Modal analysis for various kinematic configurations. • Reaction force calculations on the interfacing systems. - Abstract: The Multi-Purpose Deployer (MPD) is a general purpose ITER in-vessel remote handling (RH) system. The main handling equipment, known as the MPD Transporter, consists of a series of linked bodies, which provide anchoring to the vacuum vessel port and an articulated multi-degree of freedom motion to perform various in-vessel maintenance tasks. During the in-vessel operations, the structural integrity of the system should be guaranteed against various operational and seismic loads. This paper presents the structural analysis results of the concept design of the MPD Transporter considering the seismic events. Static structural, modal and frequency response spectrum analyses have been performed to verify the structural integrity of the system, and to provide reaction forces to the interfacing systems such as vacuum vessel and cask. Iterative analyses and design updates are carried out based on the reference design of the system to improve the structural behavior of the system. The frequency responses of the system in various kinematics and payloads are assessed.

  12. Structural analysis of reactor fuel elements

    Energy Technology Data Exchange (ETDEWEB)

    Weeks, R.W.

    1977-01-01

    An overview of fuel-element modeling is presented that traces the development of codes for the prediction of light-water-reactor and fast-breeder-reactor fuel-element performance. It is concluded that although the mathematical analysis is now far advanced, the development and incorporation of mechanistic constitutive equations has not kept pace. The resultant reliance on empirical correlations severely limits the physical insight that can be gained from code extrapolations. Current efforts include modeling of alternate fuel systems, analysis of local fuel-cladding interactions, and development of a predictive capability for off-normal behavior. Future work should help remedy the current constitutive deficiencies and should include the development of deterministic failure criteria for use in design.

  13. Musical Structural Analysis Database Based on GTTM

    OpenAIRE

    Hamanaka, Masatoshi; Hirata, Keiji; Tojo, Satoshi

    2014-01-01

    This paper, we present the publication of our analysis data and analyzing tool based on the generative theory of tonal music (GTTM). Musical databases such as score databases, instrument sound databases, and musical pieces with standard MIDI files and annotated data are key to advancements in the field of music information technology. We started implementing the GTTM on a computer in 2004 and ever since have collected and publicized test data by musicologists in a step-by-step manner. In our ...

  14. Structure analysis on synthetic emerald crystals

    Science.gov (United States)

    Lee, Pei-Lun; Lee, Jiann-Shing; Huang, Eugene; Liao, Ju-Hsiou

    2013-05-01

    Single crystals of emerald synthesized by means of the flux method were adopted for crystallographic analyses. Emerald crystals with a wide range of Cr3+-doping content up to 3.16 wt% Cr2O3 were examined by X-ray single crystal diffraction refinement method. The crystal structures of the emerald crystals were refined to R 1 (all data) of 0.019-0.024 and w R 2 (all data) of 0.061-0.073. When Cr3+ substitutes for Al3+, the main adjustment takes place in the Al-octahedron and Be-tetrahedron. The effect of substitution of Cr3+ for Al3+ in the beryl structure results in progressively lengthening of the Al-O distance, while the length of the other bonds remains nearly unchanged. The substitution of Cr3+ for Al3+ may have caused the expansion of a axis, while keeping the c axis unchanged in the emerald lattice. As a consequence, the Al-O-Si and Al-O-Be bonding angles are found to decrease, while the angle of Si-O-Be increases as the Al-O distance increases during the Cr replacement.

  15. Structural and quantitative analysis of Equisetum alkaloids.

    Science.gov (United States)

    Cramer, Luise; Ernst, Ludger; Lubienski, Marcus; Papke, Uli; Schiebel, Hans-Martin; Jerz, Gerold; Beuerle, Till

    2015-08-01

    Equisetum palustre L. is known for its toxicity for livestock. Several studies in the past addressed the isolation and identification of the responsible alkaloids. So far, palustrine (1) and N(5)-formylpalustrine (2) are known alkaloids of E. palustre. A HPLC-ESI-MS/MS method in combination with simple sample work-up was developed to identify and quantitate Equisetum alkaloids. Besides the two known alkaloids six related alkaloids were detected in different Equisetum samples. The structure of the alkaloid palustridiene (3) was derived by comprehensive 1D and 2D NMR experiments. N(5)-Acetylpalustrine (4) was also thoroughly characterized by NMR for the first time. The structure of N(5)-formylpalustridiene (5) is proposed based on mass spectrometry results. Twenty-two E. palustre samples were screened by a HPLC-ESI-MS/MS method after development of a simple sample work-up and in most cases the set of all eight alkaloids were detected in all parts of the plant. A high variability of the alkaloid content and distribution was found depending on plant organ, plant origin and season ranging from 88 to 597mg/kg dried weight. However, palustrine (1) and the alkaloid palustridiene (3) always represented the main alkaloids. For the first time, a comprehensive identification, quantitation and distribution of Equisetum alkaloids was achieved.

  16. Nonlinear transient analysis of joint dominated structures

    Science.gov (United States)

    Chapman, J. M.; Shaw, F. H.; Russell, W. C.

    1987-01-01

    A residual force technique is presented that can perform the transient analyses of large, flexible, and joint dominated structures. The technique permits substantial size reduction in the number of degrees of freedom describing the nonlinear structural models and can account for such nonlinear joint phenomena as free-play and hysteresis. In general, joints can have arbitrary force-state map representations but these are used in the form of residual force maps. One essential feature of the technique is to replace the arbitrary force-state maps describing the nonlinear joints with residual force maps describing the truss links. The main advantage of this replacement is that the incrementally small relative displacements and velocities across a joint are not monitored directly thereby avoiding numerical difficulties. Instead, very small and 'soft' residual forces are defined giving a numerically attractive form for the equations of motion and thereby permitting numerically stable integration algorithms. The technique was successfully applied to the transient analyses of a large 58 bay, 60 meter truss having nonlinear joints. A method to perform link testing is also presented.

  17. Data analysis of asymmetric structures advanced approaches in computational statistics

    CERN Document Server

    Saito, Takayuki

    2004-01-01

    Data Analysis of Asymmetric Structures provides a comprehensive presentation of a variety of models and theories for the analysis of asymmetry and its applications and provides a wealth of new approaches in every section. It meets both the practical and theoretical needs of research professionals across a wide range of disciplines and  considers data analysis in fields such as psychology, sociology, social science, ecology, and marketing. In seven comprehensive chapters this guide details theories, methods, and models for the analysis of asymmetric structures in a variety of disciplines and presents future opportunities and challenges affecting research developments and business applications.

  18. Statistical energy analysis of complex structures, phase 2

    Science.gov (United States)

    Trudell, R. W.; Yano, L. I.

    1980-01-01

    A method for estimating the structural vibration properties of complex systems in high frequency environments was investigated. The structure analyzed was the Materials Experiment Assembly, (MEA), which is a portion of the OST-2A payload for the space transportation system. Statistical energy analysis (SEA) techniques were used to model the structure and predict the structural element response to acoustic excitation. A comparison of the intial response predictions and measured acoustic test data is presented. The conclusions indicate that: the SEA predicted the response of primary structure to acoustic excitation over a wide range of frequencies; and the contribution of mechanically induced random vibration to the total MEA is not significant.

  19. Applications of Mass Spectrometry to Structural Analysis of Marine Oligosaccharides

    Directory of Open Access Journals (Sweden)

    Yinzhi Lang

    2014-06-01

    Full Text Available Marine oligosaccharides have attracted increasing attention recently in developing potential drugs and biomaterials for their particular physical and chemical properties. However, the composition and sequence analysis of marine oligosaccharides are very challenging for their structural complexity and heterogeneity. Mass spectrometry (MS has become an important technique for carbohydrate analysis by providing more detailed structural information, including molecular mass, sugar constituent, sequence, inter-residue linkage position and substitution pattern. This paper provides an overview of the structural analysis based on MS approaches in marine oligosaccharides, which are derived from some biologically important marine polysaccharides, including agaran, carrageenan, alginate, sulfated fucan, chitosan, glycosaminoglycan (GAG and GAG-like polysaccharides. Applications of electrospray ionization mass spectrometry (ESI-MS are mainly presented and the general applications of matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS are also outlined. Some technical challenges in the structural analysis of marine oligosaccharides by MS have also been pointed out.

  20. Applications of mass spectrometry to structural analysis of marine oligosaccharides.

    Science.gov (United States)

    Lang, Yinzhi; Zhao, Xia; Liu, Lili; Yu, Guangli

    2014-06-30

    Marine oligosaccharides have attracted increasing attention recently in developing potential drugs and biomaterials for their particular physical and chemical properties. However, the composition and sequence analysis of marine oligosaccharides are very challenging for their structural complexity and heterogeneity. Mass spectrometry (MS) has become an important technique for carbohydrate analysis by providing more detailed structural information, including molecular mass, sugar constituent, sequence, inter-residue linkage position and substitution pattern. This paper provides an overview of the structural analysis based on MS approaches in marine oligosaccharides, which are derived from some biologically important marine polysaccharides, including agaran, carrageenan, alginate, sulfated fucan, chitosan, glycosaminoglycan (GAG) and GAG-like polysaccharides. Applications of electrospray ionization mass spectrometry (ESI-MS) are mainly presented and the general applications of matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) are also outlined. Some technical challenges in the structural analysis of marine oligosaccharides by MS have also been pointed out.

  1. Economic analysis of the structure, Integration and Performance of ...

    African Journals Online (AJOL)

    Economic analysis of the structure, Integration and Performance of Rice Markets in Dekina Local Government Area of Kogi ... Open Access DOWNLOAD FULL TEXT ... The data for the study were collected with the aid of a questionnaire.

  2. Convected transient analysis for large space structures maneuver and deployment

    Science.gov (United States)

    Housner, J.

    1984-01-01

    Convected-transient analysis techniques in the finite-element method are used to investigate the deployment and maneuver of large spacecraft structures with multiple-member flexible trusses and frames. Numerical results are presented for several sample problems.

  3. Wheat yield dynamics: a structural econometric analysis.

    Science.gov (United States)

    Sahin, Afsin; Akdi, Yilmaz; Arslan, Fahrettin

    2007-10-15

    In this study we initially have tried to explore the wheat situation in Turkey, which has a small-open economy and in the member countries of European Union (EU). We have observed that increasing the wheat yield is fundamental to obtain comparative advantage among countries by depressing domestic prices. Also the changing structure of supporting schemes in Turkey makes it necessary to increase its wheat yield level. For this purpose, we have used available data to determine the dynamics of wheat yield by Ordinary Least Square Regression methods. In order to find out whether there is a linear relationship among these series we have checked each series whether they are integrated at the same order or not. Consequently, we have pointed out that fertilizer usage and precipitation level are substantial inputs for producing high wheat yield. Furthermore, in respect for our model, fertilizer usage affects wheat yield more than precipitation level.

  4. Structural shell analysis understanding and application

    CERN Document Server

    Blaauwendraad, Johan

    2014-01-01

    The mathematical description of the properties of a shell is much more elaborate than those of beam and plate structures. Therefore many engineers and architects are unacquainted with aspects of shell behaviour and design, and are not familiar with sufficiently reliable shell theories for the different shell types as derived in the middle of the 20th century. Rather than contributing to theory development, this university textbook focuses on architectural and civil engineering schools. Of course, practising professionals will profit from it as well. The book deals with thin elastic shells, in particular with cylindrical, conical and spherical types, and with elliptic and hyperbolic paraboloids. The focus is on roofs, chimneys, pressure vessels and storage tanks. Special attention is paid to edge bending disturbance zones, which is indispensable knowledge in FE meshing. A substantial part of the book results from research efforts in the mid 20th century at Delft University of Technology. As such, it is a valua...

  5. Ellipsometric Analysis of Cadmium Telluride Films’ Structure

    OpenAIRE

    Anna Evmenova; Volodymyr Odarych; Mykola Vuichyk; Fedir Sizov

    2015-01-01

    Ellipsometric analysis of CdTe films grown on Si and CdHgTe substrates at the “hot-wall” epitaxy vacuum setup has been performed. It has been found that ellipsometric data calculation carried out by using a simple one-layer film model leads to radical distortion of optical constants spectra: this fact authenticates the necessity to attract a more complicated model that should include heterogeneity of films. Ellipsometric data calculation within a two-layer film model permitted to conclude tha...

  6. ‘Designerly’ Analysis of Participation Structures

    DEFF Research Database (Denmark)

    Buur, Jacob; Beuthel, Maria Rosa; Caglio, Agnese

    2013-01-01

    With the inclusion of not only users but stake-holders of many different kinds, design processes turn into complex collaborative challenges. Thus, improving design practices requires research into how people participate and contribute in social interaction. But research methods for understand......-ing such activities tend to be highly analytical and hence difficult for design researchers to engage with, if results are meant to be actionable. Through a series of experiments we develop tangible support for a ‘designerly’ interaction analysis of one important aspect of collaborative design activities...

  7. Push-Over Analysis for Concrete Structures of Tall Building

    Institute of Scientific and Technical Information of China (English)

    朱杰江; 张佩军; 吕西林; 容柏生

    2004-01-01

    In this paper, push-over analysis for tall concrete structures was made and a corresponding computer program was given.Several kinds of elements in the program were considered to meet the demand of tall buildings with complex structural type. These elements included beam-column element for beams and columns, single slice wall element and three vertical line element for walls, and tube-wall element for tubes. Computational example for verifying the models indicates that the result obtained by this method is identical with a well-known test result and the program can be used to search for the full process of structural reaction, even the softening stage of the structure. With this push-over analysis method, an actual tall building with complex structural type was analyzed, and the result has been put into practice of the structural design of the building.

  8. Discrete Discriminant analysis based on tree-structured graphical models

    DEFF Research Database (Denmark)

    Perez de la Cruz, Gonzalo; Eslava, Guillermina

    The purpose of this paper is to illustrate the potential use of discriminant analysis based on tree{structured graphical models for discrete variables. This is done by comparing its empirical performance using estimated error rates for real and simulated data. The results show that discriminant...... analysis based on tree{structured graphical models is a simple nonlinear method competitive with, and sometimes superior to, other well{known linear methods like those assuming mutual independence between variables and linear logistic regression....

  9. Probabilistic Nonlinear Analysis of Reinforced Concrete Bubbler Tower Structure Failure

    Directory of Open Access Journals (Sweden)

    Králik Juraj

    2014-06-01

    Full Text Available This paper describes the reliability analysis of concrete bubbler tower structure of nuclear power plant with the reactor WWER 440 under high internal overpressure. There is showed summary of calculation models and calculation methods for the probability analysis of the structural integrity considering degradation effects and high internal overpressure. The uncertainties of the resistance and the calculation model were taking in the account in the RSM method.

  10. Implementation of efficient sensitivity analysis for optimization of large structures

    Science.gov (United States)

    Umaretiya, J. R.; Kamil, H.

    1990-01-01

    The paper presents the theoretical bases and implementation techniques of sensitivity analyses for efficient structural optimization of large structures, based on finite element static and dynamic analysis methods. The sensitivity analyses have been implemented in conjunction with two methods for optimization, namely, the Mathematical Programming and Optimality Criteria methods. The paper discusses the implementation of the sensitivity analysis method into our in-house software package, AutoDesign.

  11. Discrete Discriminant analysis based on tree-structured graphical models

    DEFF Research Database (Denmark)

    Perez de la Cruz, Gonzalo; Eslava, Guillermina

    The purpose of this paper is to illustrate the potential use of discriminant analysis based on tree{structured graphical models for discrete variables. This is done by comparing its empirical performance using estimated error rates for real and simulated data. The results show that discriminant a...... analysis based on tree{structured graphical models is a simple nonlinear method competitive with, and sometimes superior to, other well{known linear methods like those assuming mutual independence between variables and linear logistic regression....

  12. Seismic design and analysis of nuclear power plant structures

    Institute of Scientific and Technical Information of China (English)

    Pentti Varpasuo

    2013-01-01

    The seismic design and analysis of nuclear power plant (NPP) begin with the seismic hazard assessment and design ground motion development for the site.The following steps are needed for the seismic hazard assessment and design ground motion development:a.the development of regional seismo-tectonic model with seismic source areas within 500 km radius centered to the site; b.the development of strong motion prediction equations;c.logic three development for taking into account uncertainties and seismic hazard quantification; d.the development of uniform hazard response spectra for ground motion at the site; e.simulation of acceleration time histories compatible with uniform hazard response spectra.The following phase two in seismic design of NPP structures is the analysis of structural response for the design ground motion.This second phase of the process consists of the following steps:a.development of structural models of the plant buildings; b.development of the soil model underneath the plant buildings for soil-structure interaction response analysis; c.determination of in-structure response spectra for the plant buildings for the equipment response analysis.In the third phase of the seismic design and analysis the equipment is analyzed on the basis of in-structure response spectra.For this purpose the structural models of the mechanical components and piping in the plant are set up.In large 3D-structural models used today the heaviest equipment of the primary coolant circuit is included in the structural model of the reactor building.In the fourth phase the electrical equipment and automation and control equipment are seismically qualified with the aid of the in-structure spectra developed in the phase two using large three-axial shaking tables.For this purpose the smoothed envelope spectra for calculated in-structure spectra are constructed and acceleration time is fitted to these smoothed envelope spectra.

  13. Structural and functional analysis of rice genome

    Indian Academy of Sciences (India)

    Akhilesh K. Tyagi; Jitendra P. Khurana; Paramjit Khurana; Saurabh Raghuvanshi; Anupama Gaur; Anita Kapur; Vikrant Gupta; Dibyendu Kumar; V. Ravi; Shubha Vij; Parul Khurana; Sulabha Sharma

    2004-04-01

    Rice is an excellent system for plant genomics as it represents a modest size genome of 430 Mb. It feeds more than half the population of the world. Draft sequences of the rice genome, derived by whole-genome shotgun approach at relatively low coverage (4–6 X), were published and the International Rice Genome Sequencing Project (IRGSP) declared high quality (>10 X), genetically anchored, phase 2 level sequence in 2002. In addition, phase 3 level finished sequence of chromosomes 1, 4 and 10 (out of 12 chromosomes of rice) has already been reported by scientists from IRGSP consortium. Various estimates of genes in rice place the number at > 50,000. Already, over 28,000 full-length cDNAs have been sequenced, most of which map to genetically anchored genome sequence. Such information is very useful in revealing novel features of macro- and micro-level synteny of rice genome with other cereals. Microarray analysis is unraveling the identity of rice genes expressing in temporal and spatial manner and should help target candidate genes useful for improving traits of agronomic importance. Simultaneously, functional analysis of rice genome has been initiated by marker-based characterization of useful genes and employing functional knock-outs created by mutation or gene tagging. Integration of this enormous information is expected to catalyze tremendous activity on basic and applied aspects of rice genomics.

  14. Structural Analysis of Women’s Heptathlon

    Directory of Open Access Journals (Sweden)

    Freya Gassmann

    2016-02-01

    Full Text Available The heptathlon comprises the results of seven single disciplines, assuming an equal influence from each discipline, depending on the measured performance. Data analysis was based on the data recorded for the individual performances of the 10 winning heptathletes in the World Athletics Championships from 1987 to 2013 and the Olympic Games from 1988 to 2012. In addition to descriptive analysis methods, correlations, bivariate and multivariate linear regressions, and panel data regressions were used. The transformation of the performances from seconds, centimeters, and meters into points showed that the individual disciplines do not equally affect the overall competition result. The currently valid conversion formula for the run, jump, and throw disciplines prefers the sprint and jump disciplines but penalizes the athletes performing in the 800 m run, javelin throw, and shotput disciplines. Furthermore, 21% to 48% of the variance of the sum of points can be attributed to the performances in the disciplines of long jump, 200 m sprint, 100 m hurdles, and high jump. To balance the effects of the single disciplines in the heptathlon, the formula to calculate points should be reevaluated.

  15. Multiscale analysis of structure development in expanded starch snacks

    NARCIS (Netherlands)

    Sman, van der R.G.M.; Broeze, J.

    2014-01-01

    In this paper we perform a multiscale analysis of the food structuring process of the expansion of starchy snack foods like keropok, which obtains a solid foam structure. In particular, we want to investigate the validity of the hypothesis of Kokini and coworkers, that expansion is optimal at the mo

  16. Tools for analysis of Dirac structures on Hilbert spaces

    NARCIS (Netherlands)

    Golo, G.; Iftime, O.V.; Zwart, Heiko J.; van der Schaft, Arjan

    2004-01-01

    In this paper tools for the analysis of Dirac structures on Hilbert spaces are developed. Some properties are pointed out and two natural representations of Dirac structures on Hilbert spaces are presented. The theory is illustrated on the example of the ideal transmission line.

  17. Reliability-Analysis of Offshore Structures using Directional Loads

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Bloch, Allan; Sterndorff, M. J.

    2000-01-01

    Reliability analyses of offshore structures such as steel jacket platforms are usually performed using stochastic models for the wave loads based on the omnidirectional wave height. However, reliability analyses with respect to structural failure modes such as total collapse of a structure...... heights from the central part of the North Sea. It is described how the stochastic model for the directional wave heights can be used in a reliability analysis where total collapse of offshore steel jacket platforms is considered....

  18. Ellipsometric Analysis of Cadmium Telluride Films’ Structure

    Directory of Open Access Journals (Sweden)

    Anna Evmenova

    2015-01-01

    Full Text Available Ellipsometric analysis of CdTe films grown on Si and CdHgTe substrates at the “hot-wall” epitaxy vacuum setup has been performed. It has been found that ellipsometric data calculation carried out by using a simple one-layer film model leads to radical distortion of optical constants spectra: this fact authenticates the necessity to attract a more complicated model that should include heterogeneity of films. Ellipsometric data calculation within a two-layer film model permitted to conclude that cadmium telluride films have an outer layer that consists of the three-component mixture of CdTe, cavities, and basic matter oxide. Ratio of mixture components depends on the time of deposition, that is, on the film thickness. The inner layer consists of cadmium telluride.

  19. Sediment Analysis Using a Structured Programming Approach

    Directory of Open Access Journals (Sweden)

    Daniela Arias-Madrid

    2012-12-01

    Full Text Available This paper presents an algorithm designed for the analysis of a sedimentary sample of unconsolidated material and seeks to identify very quickly the main features that occur in a sediment and thus classify them fast and efficiently. For this purpose, it requires that the weight of each particle size to be entered in the program and using the method of Moments, which is based on four equations representing the mean, standard deviation, skewness and kurtosis, is found the attributes of the sample in few seconds. With the program these calculations are performed in an effective and more accurately way, obtaining also the explanations of the results of the features such as grain size, sorting, symmetry and origin, which helps to improve the study of sediments and in general the study of sedimentary rocks.

  20. Structural model analysis of multiple quantitative traits.

    Directory of Open Access Journals (Sweden)

    Renhua Li

    2006-07-01

    Full Text Available We introduce a method for the analysis of multilocus, multitrait genetic data that provides an intuitive and precise characterization of genetic architecture. We show that it is possible to infer the magnitude and direction of causal relationships among multiple correlated phenotypes and illustrate the technique using body composition and bone density data from mouse intercross populations. Using these techniques we are able to distinguish genetic loci that affect adiposity from those that affect overall body size and thus reveal a shortcoming of standardized measures such as body mass index that are widely used in obesity research. The identification of causal networks sheds light on the nature of genetic heterogeneity and pleiotropy in complex genetic systems.

  1. Tanker Structural Analysis for Minor Collisions

    Science.gov (United States)

    1975-12-01

    masses (including virtual masses of the water), the initial bearings, and velocities. 2. Throughout the analysis, the bow of the striking ship Is...initial velocity of the striking ship: m( F ______ (1 t 0 V20) =0.0 f= virtual mass, ship I 2 = virtual mass, ship 2~ m I V . V f ’ K’ Jt 11 FIUR m-2...situ .K. 5Y( i~ lZAKD bow $H 14ILIQj P Lh5T I C. EQ k Y kps) 0 0 94-1 W~IAk) J~~E 0 oC4O.1 ,I Hi PL~c,1C. tlA% ;OQ)- AULA / ;0) 4 4 4~IN -c Q

  2. A method for rapid similarity analysis of RNA secondary structures

    Directory of Open Access Journals (Sweden)

    Liu Na

    2006-11-01

    Full Text Available Abstract Background Owing to the rapid expansion of RNA structure databases in recent years, efficient methods for structure comparison are in demand for function prediction and evolutionary analysis. Usually, the similarity of RNA secondary structures is evaluated based on tree models and dynamic programming algorithms. We present here a new method for the similarity analysis of RNA secondary structures. Results Three sets of real data have been used as input for the example applications. Set I includes the structures from 5S rRNAs. Set II includes the secondary structures from RNase P and RNase MRP. Set III includes the structures from 16S rRNAs. Reasonable phylogenetic trees are derived for these three sets of data by using our method. Moreover, our program runs faster as compared to some existing ones. Conclusion The famous Lempel-Ziv algorithm can efficiently extract the information on repeated patterns encoded in RNA secondary structures and makes our method an alternative to analyze the similarity of RNA secondary structures. This method will also be useful to researchers who are interested in evolutionary analysis.

  3. Modelization and structural analysis of FDM parts

    Science.gov (United States)

    Martínez, J.; Diéguez, J. L.; Ares, J. E.; Pereira, A.; Pérez, J. A.

    2012-04-01

    Get prototypes from technologies of Rapid Prototyping (RP) is a very important step for the development of new products. In some cases, these prototypes have mechanical properties lower than the final product, which prevents the designers to use all of the potential that these technologies can provide. In this study the RP technology known as FDM (Fused Deposition Modeling) was used to manufacture samples used in tests, in where the orientation of deposition wires in layers were varying depending on manufacturing placement. Mechanical tests were performed to verify the stiffness of the final pieces obtained. The Classical Theory of Laminates (TCL) will be used to predict the mechanical behavior of the parts in different orientations of manufacturing. Thus, this study aims to evaluate the influence of the strategies in the deposition of construction material on the mechanical properties of parts obtained by the FDM and analyzes manufacturing factors for a future generation of a finite elements analytic model that could be used to obtain the structural behavior of parts made by rapid prototyping with FDM technology.

  4. Analysis of boron carbides' electronic structure

    Science.gov (United States)

    Howard, Iris A.; Beckel, Charles L.

    1986-01-01

    The electronic properties of boron-rich icosahedral clusters were studied as a means of understanding the electronic structure of the icosahedral borides such as boron carbide. A lower bound was estimated on bipolaron formation energies in B12 and B11C icosahedra, and the associated distortions. While the magnitude of the distortion associated with bipolaron formation is similar in both cases, the calculated formation energies differ greatly, formation being much more favorable on B11C icosahedra. The stable positions of a divalent atom relative to an icosahedral borane was also investigated, with the result that a stable energy minimum was found when the atom is at the center of the borane, internal to the B12 cage. If incorporation of dopant atoms into B12 cages in icosahedral boride solids is feasible, novel materials might result. In addition, the normal modes of a B12H12 cluster, of the C2B10 cage in para-carborane, and of a B12 icosahedron of reduced (D sub 3d) symmetry, such as is found in the icosahedral borides, were calculated. The nature of these vibrational modes will be important in determining, for instance, the character of the electron-lattice coupling in the borides, and in analyzing the lattice contribution to the thermal conductivity.

  5. STRUCTURAL ANALYSIS OF CONDITIONAL PREPARATION IN JUDO

    Directory of Open Access Journals (Sweden)

    Slavko Obadov

    2006-06-01

    Full Text Available Conditional preparation is a constituent part of overall sports preparation. Conditional training might be defined as a process of improvement of a sportsman’s functional and motor abilities, morphological characteristics, health, as well as the required motor knowledge. Conditional preparation can be might be classified as: general, basic and situational conditional preparation. Programs of the conditional training might be classified as: developing, resuming, recovering, preventive and recovering ones. High level of the general physical preparation enables maximum demonstration of the physical abilities of a sportsman during the stage of improvement of the specific motor abilities. Good general preparation of a sportsman enables him to push beyond his functional limits in order to cope with heavy loads easier, which subsequently enables him to achieve top performance level. Basic conditional preparation assumes the development of the most important judo abilities. Specific conditional preparation is related directly to the execution of different structural elements under the conditional requirements. Situational conditional preparation enables integration of the tactical and conditional training.

  6. Structure analysis of active components of traditional Chinese medicines

    DEFF Research Database (Denmark)

    Zhang, Wei; Sun, Qinglei; Liu, Jianhua

    2013-01-01

    Traditional Chinese Medicines (TCMs) have been widely used for healing of different health problems for thousands of years. They have been used as therapeutic, complementary and alternative medicines. TCMs usually consist of dozens to hundreds of various compounds, which are extracted from raw...... samples. NMR, on the other hand, provides not only information of primary structures but also information of higher order structures, complementing the components structure analysis by HPLC-MS. The most recent progress in the analysis of the commonly used TCMs will be summarized...

  7. Structural mode significance using INCA. [Interactive Controls Analysis computer program

    Science.gov (United States)

    Bauer, Frank H.; Downing, John P.; Thorpe, Christopher J.

    1990-01-01

    Structural finite element models are often too large to be used in the design and analysis of control systems. Model reduction techniques must be applied to reduce the structural model to manageable size. In the past, engineers either performed the model order reduction by hand or used distinct computer programs to retrieve the data, to perform the significance analysis and to reduce the order of the model. To expedite this process, the latest version of INCA has been expanded to include an interactive graphical structural mode significance and model order reduction capability.

  8. Structural mode significance using INCA. [Interactive Controls Analysis computer program

    Science.gov (United States)

    Bauer, Frank H.; Downing, John P.; Thorpe, Christopher J.

    1990-01-01

    Structural finite element models are often too large to be used in the design and analysis of control systems. Model reduction techniques must be applied to reduce the structural model to manageable size. In the past, engineers either performed the model order reduction by hand or used distinct computer programs to retrieve the data, to perform the significance analysis and to reduce the order of the model. To expedite this process, the latest version of INCA has been expanded to include an interactive graphical structural mode significance and model order reduction capability.

  9. Structural analysis of cell wall polysaccharides using PACE

    Energy Technology Data Exchange (ETDEWEB)

    Mortimer, Jennifer C. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Joint BioEnergy Institute

    2017-01-01

    The plant cell wall is composed of many complex polysaccharides. The composition and structure of the polysaccharides affect various cell properties including cell shape, cell function and cell adhesion. Many techniques to characterize polysaccharide structure are complicated, requiring expensive equipment and specialized operators e.g. NMR, MALDI-MS. PACE (Polysaccharide Analysis using Carbohydrate gel Electrophoresis) uses a simple, rapid technique to analyze polysaccharide quantity and structure (Goubet et al. 2002). Whilst the method here describes xylan analysis, it can be applied (by use of the appropriate glycosyl hydrolase) to any cell wall polysaccharide.

  10. Structural analysis of Aircraft fuselage splice joint

    Science.gov (United States)

    Udaya Prakash, R.; Kumar, G. Raj; Vijayanandh, R.; Senthil Kumar, M.; Ramganesh, T.

    2016-09-01

    In Aviation sector, composite materials and its application to each component are one of the prime factors of consideration due to the high strength to weight ratio, design flexibility and non-corrosive so that the composite materials are widely used in the low weight constructions and also it can be treated as a suitable alternative to metals. The objective of this paper is to estimate and compare the suitability of a composite skin joint in an aircraft fuselage with different joints by simulating the displacement, normal stress, vonmises stress and shear stress with the help of numerical solution methods. The reference Z-stringer component of this paper is modeled by CATIA and numerical simulation is carried out by ANSYS has been used for splice joint presents in the aircraft fuselage with three combinations of joints such as riveted joint, bonded joint and hybrid joint. Nowadays the stringers are using to avoid buckling of fuselage skin, it has joined together by rivets and they are connected end to end by splice joint. Design and static analysis of three-dimensional models of joints such as bonded, riveted and hybrid are carried out and results are compared.

  11. Neighborhood structure effects on the Dynamic response of soil-structure interaction by harmonic analysis

    Directory of Open Access Journals (Sweden)

    Pan Dan-guang

    2015-01-01

    Full Text Available For realizing the variation of structural dynamic characteristics due to neighbor structure in buildings group, the surface structure is idealized as an equivalent single degree of freedom system with rigid base whose site consists of a single homogeneous layer. Based on the model, a equivalent method on the equivalent seismic excitation is proposed. Then, the differences of seismic response and equivalent seismic input between soil - structure interaction (SSI system and structure -soil-structure interaction (SSSI system are investigated by harmonic analysis. The numerical results show that dynamic responses would be underestimated in SSSI system when the forcing frequencies are close to the Natural frequency if the effects of neighborhood structure were ignored. Neighborhood structure would make the translational displacement increase and rocking vibration decrease. When establishing an effective seismic input, it is necessary to consider the impact of inertia interaction.

  12. Advanced analysis and design for fire safety of steel structures

    CERN Document Server

    Li, Guoqiang

    2013-01-01

    Advanced Analysis and Design for Fire Safety of Steel Structures systematically presents the latest findings on behaviours of steel structural components in a fire, such as the catenary actions of restrained steel beams, the design methods for restrained steel columns, and the membrane actions of concrete floor slabs with steel decks. Using a systematic description of structural fire safety engineering principles, the authors illustrate the important difference between behaviours of an isolated structural element and the restrained component in a complete structure under fire conditions. The book will be an essential resource for structural engineers who wish to improve their understanding of steel buildings exposed to fires. It is also an ideal textbook for introductory courses in fire safety for master’s degree programs in structural engineering, and is excellent reading material for final-year undergraduate students in civil engineering and fire safety engineering. Furthermore, it successfully bridges th...

  13. Structural analysis for diagnosis with application to ship propulsion problem

    DEFF Research Database (Denmark)

    Izadi-Zamanabadi, Roozbeh; Blanke, Mogens

    2002-01-01

    Aiming at design of algorithms for fault diagnosis, structural analysis of systems offers concise yet easy overall analysis. Graph-based matching, which is the essential tech-nique to obtain redundant information for diagnosis, is reconsidered in this paper. Matching is reformulated as a problem ...

  14. Structural analysis for diagnosis with application to ship propulsion problem

    DEFF Research Database (Denmark)

    Izadi-Zamanabadi, Roozbeh; Blanke, Mogens

    2002-01-01

    Aiming at design of algorithms for fault diagnosis, structural analysis of systems offers concise yet easy overall analysis. Graph-based matching, which is the essential tech-nique to obtain redundant information for diagnosis, is reconsidered in this paper. Matching is reformulated as a problem...

  15. 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

  16. 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

  17. Fluid-structure coupled analysis of underwater cylindrical shells

    Institute of Scientific and Technical Information of China (English)

    AI Shang-mao; SUN Li-ping

    2008-01-01

    Underwater cylindrical shell structures have been found a wide of application in many engineering fields,such as the element of marine,oil platforms,etc.The coupled vibration analysis is a hot issue for these underwater structures.The vibration characteristics of underwater structures are influenced not only by hydrodynamic pressure but also by hydrostatic pressure corresponding to different water depths.In this study,an acoustic finite element method was used to evaluate the underwater structures.Taken the hydrostatic pressure into account in terms of initial stress stiffness,an acoustical fluid-structure coupled analysis of underwater cylindrical shells has been made to study the effect of hydrodynamic pressures on natural frequency and sound radiation.By comparing with the frequencies obtained by the acoustic finite element method and by the added mass method based on the Bessel function,the validity of present analysis was checked.Finally,test samples of the sound radiation of stiffened cylindrical shells were acquired by a harmonic acoustic analysis.The results showed that hydrostatic pressure plays an important role in determining a large submerged body motion,and the characteristics of sound radiation change with water depth. Furthermore,the analysis methods and the results are of significant reference value for studies of other complicated submarine structures.

  18. Structure optimization and simulation analysis of the quartz micromachined gyroscope

    Science.gov (United States)

    Wu, Xuezhong; Wang, Haoxu; Xie, Liqiang; Dong, Peitao

    2014-03-01

    Structure optimization and simulation analysis of the quartz micromachined gyroscope are reported in this paper. The relationships between the structure parameters and the frequencies of work mode were analysed by finite element analysis. The structure parameters of the quartz micromachined gyroscope were optimized to reduce the difference between the frequencies of the drive mode and the sense mode. The simulation results were proved by testing the prototype gyroscope, which was fabricated by micro-electromechanical systems (MEMS) technology. Therefore, the frequencies of the drive mode and the sense mode can match each other by the structure optimization and simulation analysis of the quartz micromachined gyroscope, which is helpful in the design of the high sensitivity quartz micromachined gyroscope.

  19. Rapid structural analysis of nanomaterials in aqueous solutions

    Science.gov (United States)

    Ryuzaki, Sou; Tsutsui, Makusu; He, Yuhui; Yokota, Kazumichi; Arima, Akihide; Morikawa, Takanori; Taniguchi, Masateru; Kawai, Tomoji

    2017-04-01

    Rapid structural analysis of nanoscale matter in a liquid environment represents innovative technologies that reveal the identities and functions of biologically important molecules. However, there is currently no method with high spatio-temporal resolution that can scan individual particles in solutions to gain structural information. Here we report the development of a nanopore platform realizing quantitative structural analysis for suspended nanomaterials in solutions with a high z-axis and xy-plane spatial resolution of 35.8 ± 1.1 and 12 nm, respectively. We used a low thickness-to-diameter aspect ratio pore architecture for achieving cross sectional areas of analyte (i.e. tomograms). Combining this with multiphysics simulation methods to translate ionic current data into tomograms, we demonstrated rapid structural analysis of single polystyrene (Pst) beads and single dumbbell-like Pst beads in aqueous solutions.

  20. Structure optimization and simulation analysis of the quartz micromachined gyroscope

    Directory of Open Access Journals (Sweden)

    Xuezhong Wu

    2014-02-01

    Full Text Available Structure optimization and simulation analysis of the quartz micromachined gyroscope are reported in this paper. The relationships between the structure parameters and the frequencies of work mode were analysed by finite element analysis. The structure parameters of the quartz micromachined gyroscope were optimized to reduce the difference between the frequencies of the drive mode and the sense mode. The simulation results were proved by testing the prototype gyroscope, which was fabricated by micro-electromechanical systems (MEMS technology. Therefore, the frequencies of the drive mode and the sense mode can match each other by the structure optimization and simulation analysis of the quartz micromachined gyroscope, which is helpful in the design of the high sensitivity quartz micromachined gyroscope.