Relevant bibliographies by topics / Flux-balance analysi

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
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Academic literature on the topic 'Flux-balance analysi'

Author: Grafiati
Published: 21 February 2023
Last updated: 22 February 2023

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Journal articles on the topic "Flux-balance analysi"

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Rashid, Ana Haziqah, Yee Wen Choon, Mohd Saberi Mohamad, Lian En Chai, Chuii Khim Chong, Safaai Deris, and Rosli Illias. "Producing Succinic Acid in Yeast using A Hybrid of Differential Evolution and Flux Balance Analysis." International Journal of Bio-Science and Bio-Technology 5, no. 6 (December 31, 2013): 91–100. http://dx.doi.org/10.14257/ijbsbt.2013.5.6.10.

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Orth, Jeffrey D., Ines Thiele, and Bernhard Ø. Palsson. "What is flux balance analysis?" Nature Biotechnology 28, no. 3 (March 2010): 245–48. http://dx.doi.org/10.1038/nbt.1614.

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Mori, Matteo, Terence Hwa, Olivier C. Martin, Andrea De Martino, and Enzo Marinari. "Constrained Allocation Flux Balance Analysis." PLOS Computational Biology 12, no. 6 (June 29, 2016): e1004913. http://dx.doi.org/10.1371/journal.pcbi.1004913.

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Kauffman, Kenneth J., Purusharth Prakash, and Jeremy S. Edwards. "Advances in flux balance analysis." Current Opinion in Biotechnology 14, no. 5 (October 2003): 491–96. http://dx.doi.org/10.1016/j.copbio.2003.08.001.

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Ambroso, Annalisa, Christophe Chalons, Frédéric Coquel, and Thomas Galié. "Interface model couplingviaprescribed local flux balance." ESAIM: Mathematical Modelling and Numerical Analysis 48, no. 3 (April 24, 2014): 895–918. http://dx.doi.org/10.1051/m2an/2013125.

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Shastri, A. A., and J. A. Morgan. "Flux Balance Analysis of Photoautotrophic Metabolism." Biotechnology Progress 21, no. 6 (December 2, 2005): 1617–26. http://dx.doi.org/10.1021/bp050246d.

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Lakshmanan, M., G. Koh, B. K. S. Chung, and D. Y. Lee. "Software applications for flux balance analysis." Briefings in Bioinformatics 15, no. 1 (November 5, 2012): 108–22. http://dx.doi.org/10.1093/bib/bbs069.

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Smallbone, Kieran, and Evangelos Simeonidis. "Flux balance analysis: A geometric perspective." Journal of Theoretical Biology 258, no. 2 (May 2009): 311–15. http://dx.doi.org/10.1016/j.jtbi.2009.01.027.

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Benyamini, Tomer, Ori Folger, Eytan Ruppin, and Tomer Shlomi. "Flux balance analysis accounting for metabolite dilution." Genome Biology 11, no. 4 (2010): R43. http://dx.doi.org/10.1186/gb-2010-11-4-r43.

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Zhang, Yixing, Fan Zeng, Keith Hohn, and Praveen V. Vadlani. "Metabolic flux analysis of carbon balance inLactobacillusstrains." Biotechnology Progress 32, no. 6 (September 21, 2016): 1397–403. http://dx.doi.org/10.1002/btpr.2361.

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Dissertations / Theses on the topic "Flux-balance analysi"

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Favero, Francesco. "Development of two new approaches for NGS data analysis of DNA and RNA molecules and their application in clinical and research fields." Doctoral thesis, Università del Piemonte Orientale, 2019. http://hdl.handle.net/11579/102446.

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The aim of this study is focused on two main areas of NGS analysis data: RNA-seq(with a specific interest in meta-transcriptomics) and DNA somatic mutations detection. We developed a simple and efficient pipeline for the analysis of NGS data derived from gene panels to identify DNA somatic point mutations. In particular we optimized a somatic variant calling procedure that was tested on simulated datasets and on real data. The performance of our system has been compared with currently available tools for variant calling reviewed in literature. For RNA-seq analysis, in this work we tested and optimized STAble, an algorithm developed originally in our laboratory for the de novo reconstruction of transcripts from non reference based RNA-seq data. At the beginning of this study, the first module of STAble was already been written. The first module is the one which reconstructs a list of transcripts starting from RNA-seq data. The aim of this study, particularly, consisted in adding a new module to STAble, developed in collaboration with Cambridge University, based on the flux-balance analysis in order to link the metatranscriptomic analysis to a metabolic approach. This goal has been achieved in order to study the metabolic fluxes of microbiota starting from metatranscriptomic data.
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Gomez, Jose Alberto Ph D. Massachusetts Institute of Technology. "Simulation, sensitivity analysis, and optimization of bioprocesses using dynamic flux balance analysis." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/117325.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Chemical Engineering, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 301-312).
Microbial communities are a critical component of natural ecosystems and industrial bioprocesses. In natural ecosystems, these communities can present abrupt and surprising responses to perturbations, which can have important consequences. For example, climate change can influence drastically the composition of microbial communities in the oceans, which in turn affects the entirety of the food chain, and changes in diet can affect drastically the composition of the human gut microbiome, making it stronger or more vulnerable to infection by pathogens. In industrial bioprocesses, engineers work with these communities to obtain desirable products such as biofuels, pharmaceuticals, and alcoholic beverages, or to achieve relevant environmental objectives such as wastewater treatment or carbon capture. Mathematical models of microbial communities are critical for the study of natural ecosystems and for the design and control of bioprocesses. Good mathematical models of microbial communities allow scientists to predict how robust an ecosystem is, how perturbed ecosystems can be remediated, how sensitive an ecosystem is with respect to specific perturbations, and in what ways and how fast it would react to environmental changes. Good mathematical models allow engineers to design better bioprocesses and control them to produce high-quality products that meet tight specifications. Despite the importance of microbial communities, mathematical models describing their behavior remain simplistic and only applicable to very simple and controlled bioprocesses. Therefore, the study of natural ecosystems and the design of complex bioprocesses is very challenging. As a result, the design of bioprocesses remains experiment-based, which is slow, expensive, and labor-intensive. With high throughput experiments large datasets are generated, but without reliable mathematical models critical links between the species in the community are often missed. The design of novel bioprocesses rely on informed guesses by scientists that can only be tested experimentally. The expenses incurred by these experiments can be difficult to justify. Predictive mathematical models of microbial communities can provide insights about the possible outcomes of novel bioprocesses and guide the experimental design, resulting in cheaper and faster bioprocess development. Most mathematical models describing microbial communities do not take into account the internal structure of the microorganisms. In recent years, new knowledge of the internal structures of these microorganisms has been generated using highthroughput DNA sequencing. Flux balance analysis (FBA) is a modeling framework that incorporates this new information into mathematical models of microbial communities. With FBA, growth and exchange flux predictions are made by solving linear programs (LPs) that are constructed based on the metabolic networks of the microorganisms. FBA can be combined with the mathematical models of dynamical biosystems, resulting in dynamic FBA (DFBA) models. DFBA models are difficult to simulate, sensitivity information is challenging to obtain, and reliable strategies to solve optimization problems with DFBA models embedded are lacking. Therefore, the use of DFBA models in science and industry remains very limited. This thesis makes DFBA simulation more accessible to scientists and engineers with DFBAlab, a fast, reliable, and efficient Matlab-based DFBA simulator. This simulator is used by more than a 100 academic users to simulate various processes such as chronic wound biofilms, gas fermentation in bubble column bioreactors, and beta-carotene production in microalgae. Also, novel combinations of microbial communities in raceway ponds have been studied. The performance of algal-yeast cocultures and more complex communities for biolipids production has been evaluated, gaining relevant insights that will soon be tested experimentally. These combinations could enable the production of lipids-rich biomass in locations far away from power plants and other concentrated CO 2 sources by utilizing lignocellulosic waste instead. Following reliable DFBA simulation, the mathematical theory required for sensitivity analysis of DFBA models, which happen to be nonsmooth, was developed. Methods to compute generalized derivative information for special compositions of functions, hierarchical LPs, and DFBA models were generated. Significant numerical challenges appeared during the sensitivity computation of DFBA models, some of which were resolved. Despite the challenges, sensitivity information for DFBA models was used to solve for the steady-state of a high-fidelity model of a bubble column bioreactor using nonsmooth equation-solving algorithms. Finally, local optimization strategies for different classes of problems with DFBA models embedded were generated. The classes of problems considered include parameter estimation and optimal batch, continuous steady-state, and continuous cyclic steady-state process design. These strategies were illustrated using toy metabolic networks as well as genome-scale metabolic networks. These optimization problems demonstrate the superior performance of optimizers when reliable sensitivity information is used, as opposed to approximate information obtained from finite differences. Future work includes the development of global optimization strategies, as well as increasing the robustness of the computation of sensitivities of DFBA models. Nevertheless, the application of DFBA models of microbial communities for the study of natural ecosystems and bioprocess design and control is closer to reality.
by Jose Alberto Gomez.
Ph. D.
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Jaques, Colin Mark. "Modelling of metabolic pathways for Saccharopolyspora erythraea using flux balance analysis." Thesis, University College London (University of London), 2004. http://discovery.ucl.ac.uk/1446668/.

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The objective of this thesis is to use metabolic modelling techniques to investigate primary and secondary metabolism in S. erythraea and from this to identify key factors controlling flux distribution during secondary metabolism. S. erythraea is a member of the actinomycetes a group of bacteria responsible for the production of a number of commercially important small molecules. Actinomycete physiology is considerably more complicated than that seen in "simple" bacteria such as E. coli. The conjecture investigated in this thesis is that metabolic modelling techniques that take into account this extra complexity should be more useful in designing strategies for overproduction of desired metabolites than simpler models. The thesis gives the first detailed description of the dynamic changes in biomass composition seen during the batch cultivation of S. erythraea. It further shows that incorporation of this information into a flux balance model of the organism's metabolism significantly improves the flux distributions generated especially in the stationary phase. Using this improved technique growth phase and stationary phase metabolism are investigated. Some of the unusual stationary phase behaviour is shown to be the result of glucose uptake being independent of demand. Rigid control of branch points in the metabolic network is not found suggesting that the organism's metabolism is flexible. A reverse metabolic engineering strategy is applied, two variants of the wild type organism are compared with an industrial strain. The industrial strain is found to have a considerably lower glucose uptake rate than the parental strain. The relationship between TCA cycle flux, oxidative phosphorylation and organic acid secretion is investigated using an uncoupler. This project demonstrates that applied correctly flux balance analysis is a powerful tool for investigating actinomycete physiology. The insights gained are of direct relevance to the commercial production of secondary metabolites in S. erythraea.
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Desouki, Abdelmoneim [Verfasser]. "Algorithms for Improving the Predictive Power of Flux Balance Analysis / Abdelmoneim Desouki." Düsseldorf : Universitäts- und Landesbibliothek der Heinrich-Heine-Universität Düsseldorf, 2016. http://d-nb.info/1125658738/34.

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Guidi, Lionel. "Particle flux transformation in the mesopelagic water column: process analysis and global balance." Diss., Texas A&M University, 2008. http://hdl.handle.net/1969.1/85946.

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Marine aggregates are an important means of carbon transfers downwards to the deep ocean as well as an important nutritional source for benthic organism communities that are the ultimate recipients of the flux. During these last 10 years, data on size distribution of particulate matter have been collected in different oceanic provinces using an Underwater Video Profiler. The cruise data include simultaneous analyses of particle size distributions as well as additional physical and biological measurements of water properties through the water column. First, size distributions of large aggregates have been compared to simultaneous measurements of particle flux observed in sediment traps. We related sediment trap compositional data to particle size (d) distributions to estimate their vertical fluxes (F) using simple power relationships (F=Ad^b). The spatial resolution of sedimentation processes allowed by the use of in situ particle sizing instruments lead to a more detailed study of the role of physical processes in vertical flux. Second, evolution of the aggregate size distributions with depth was related to overlying primary production and phytoplankton size-distributions on a global scale. A new clustering technique was developed to partition the profiles of aggregate size distributions. Six clusters were isolated. Profiles with a high proportion of large aggregates were found in high-productivity waters while profiles with a high proportion of small aggregates were located in low-productivity waters. The aggregate size and mass flux in the mesopelagic layer were correlated to the nature of primary producers (micro-, nano-, picophytoplankton fractions) and to the amount of integrated chlorophyll a in the euphotic layer using a multiple regression technique on principal components. Finally, a mesoscale area in the North Atlantic Ocean was studied to emphasize the importance of the physical structure of the water column on the horizontal and vertical distribution of particulate matter. The seasonal change in the abundance of aggregates in the upper 1000 m was consistent with changes in the composition and intensity of the particulate flux recorded in sediment traps. In an area dominated by eddies, surface accumulation of aggregates and export down to 1000 m occured at mesoscale distances (<100 km).
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Coze, Fabien. "Régulation du métabolisme primaire et biosynthèse d’antibiotiques par la souche d’intérêt industriel Streptomyces." Thesis, Paris 11, 2011. http://www.theses.fr/2011PA112323.

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Ce travail décrit l’analyse de la distribution des flux de carbones au sein de deux souches de Streptomyces coelicolor A3(2) : la souche sauvage nommée M145 et son mutant M1146 incapable de produire les antibiotiques actinorhodine, undecylprodigiosine, et l’antibiotique dépendant du calcium. Metabolite Balance Analysis et Isotopomer Balance Analysis sont mis en œuvre pour proposer un modèle de distribution des flux de carbones de S. coelicolor en phase exponentielle de croissance. Les souches M145 et M1146 sont cultivées dans un milieu minimum limitant en azote et leurs comportements métaboliques sont comparés. Dans la souche non productrice M1146, un taux de croissance plus élévé, un flux plus important dans la voie des pentoses phosphates, un flux plus faible au niveau du cycle de Krebs ainsi qu’une activité respiratoire plus faible sont mis en évidence. Cela traduit le coût énergétique important associé à la production d’actinorhodine par M145. De plus, ce travail propose un rôle important de la nicotinamide nucléotide transhydrogénase pour le maintien de l’homéostasie du NADPH lors de la production d’actinorhodine par M145. Comme il existe de bonnes corrélations entre les données expérimentales et celles issues de la modélisation au niveau des bilans carbones, des bilans de pouvoir réducteur et des échanges gazeux, il sera intéressant d’utiliser cette modélisation avec la technique de Flux Balance Analysis pour prédire les variations de la distribution des flux de carbones dans des mutants de S. coelicolor pour lesquels des gènes auraient été sur-exprimés ou délétés
This work describes an analysis of carbon flux distribution in two strains of Streptomyces coelicolor A3(2), namely the wild type strain M145 and its derivative M1146 that is no longer able to produce the antibiotics actinorhodin, undecylprodigiosin and the calcium dependent antibiotic. Metabolite Balance Analysis and Isotopomer Balance Analysis were used to propose a model for carbon flux distribution in S. coelicolor during the exponential phase of growth. Strains M145 and M1146 were grown under nitrogen limitation in minimal medium and their metabolic behaviour were compared. In the non-producing strain M1146, a higher growth rate, a higher flux via the pentose phosphate pathway, a decreased flux through the TCA cycle and a decreased respiratory activity were evidenced. This highlighted the high energetic cost for actinorhodin production in M145. In this paper, we also propose a key role for the nicotinamide nucleotide transhydrogenase in NADPH homeostasis in M145 during actinorhodin production. As there are good correlations between experimental data and the model in terms of carbon balance, reducing power balance and gas exchanges, this model will be of great interest for Flux Balance Analysis to predict carbon-flux distribution changes in S. coelicolor strains in which gene are deleted or overexpressed
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Shabestery, Kiyan. "Metabolisk modellering av butanol produktion i cyanobakterie." Thesis, KTH, Skolan för bioteknologi (BIO), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-172095.

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Engineering microorganisms at the systems level is recognized to be the future of metabolic engineering. Thanks to the development of genome annotation, mcroorganisms can be understood, as never before, and be reconstructed in the form of computational models. Flux balance analysis provides a deep insight intocellular metabolism and can guide metabolic engineering strategies. In particular, algorithms can assess the cellular complexity of the metabolism and hint at genetic interventions to improve product productivity. In this work, Synechosystis PCC6803 metabolism was invesetigated in silico. Genetic interventions could besuggested to couple butanol synthesis to growth as a way to improve currentproductivities. Cofactor recycling and, in particular, buffering mechanisms were shown to be important targets. Creating a cofacor imbalance and removing thesebuffering mechanisms is an important driving force. This forces a carbon flux through butanol synthesis to maintain cofactor balance and sustain growth.
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Chongcharoentaweesuk, Pasika. "Hydrogen production by Rhodobacter sphaeroides and its analysis by metabolic flux balancing." Thesis, University of Manchester, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.603211.

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There is a global need for sustainable, renewable and clean energy sources. Microbial production of hydrogen from renewable carbon sources, biorefinery compounds such as succinic acid or from food and drinks industry waste meets all these criteria. Although it has been studied for several decades, there is still no large scale bio-hydrogen production because the rate and yield of hydrogen production are not high enough to render the process economical. The dependency of biological hydrogen production of incipient light energy is also an important factor affecting economics. In order to improve the prospects of biohydrogen as a renewable and sustainable energy alternative, the genetic and process engineering approaches should be helped and targeted by metabolic engineering tools such as metabolic flux balance analysis. The overall aim of this research was the development of computational metabolic flux balance analysis for the study of growth and hydrogen production in Rhodobacter sphaeroides. The research reported in this thesis had two approaches; experimental and computational. Batch culture experiments for growth and hydrogen production by Rhodobacter sphaeroides were performed with either malate or succinate as carbon source and with glutamate as the nitrogen source. Other conditions investigated included; i) aerobic and anaerobic growth, ii) light and dark fermentation for growth, and iii) continuous light and cycled light/dark conditions for hydrogen production. The best growth was obtained with succinate under anaerobic photoheterotrophic conditions with the maximum specific growth rate of 0.0467 h– 1, which was accompanied with the maximum specific hydrogen production rate of 1.249 mmol(gDW.h)– 1. The range of the photon flux used was 5.457 - 0.080 mmol(gDW.h)– 1. The metabolic flux balance model involved 218 reactions and 176 metabolites. As expected the optimised specific rates of growth and hydrogen production were higher than those of the experimental values. The best prediction was for hydrogen production on succinate with computed specific hydrogen production rates in the range of 2.314 - 1.322 mmol(gDW.h)– 1. Sensitivity analyses indicated that the specific growth rate was affected by the nitrogen source uptake rate under aerobic dark condition whereas the flux of protein formation had the largest effect on the specific growth rate under anaerobic light condition.
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Yen, Jiun Yang. "Systems metabolic engineering of Arabidopsis for increased cellulose production." Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/54589.

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Computational biology enabled us to manage vast amount of experimental data and make inferences on observations that we had not made. Among the many methods, predicting metabolic functions with genome-scale models had shown promising results in the recent years. Using sophisticated algorithms, such as flux balance analysis, OptKnock, and OptForce, we can predict flux distributions and design metabolic engineering strategies at a greater efficiency. The caveat of these current methods is the accuracy of the predictions. We proposed using flux balance analysis with flux ratios as a possible solution to improving the accuracy of the conventional methods. To examine the accuracy of our approach, we implemented flux balance analyses with flux ratios in five publicly available genome-scale models of five different organisms, including Arabidopsis thaliana, yeast, cyanobacteria, Escherichia coli, and Clostridium acetobutylicum, using published metabolic engineering strategies for improving product yields in these organisms. We examined the limitations of the published strategies, searched for possible improvements, and evaluated the impact of these strategies on growth and product yields. The flux balance analysis with flux ratio method requires a prior knowledge on the critical regions of the metabolic network where altering flux ratios can have significant impact on flux redistribution. Thus, we further developed the reverse flux balance analysis with flux ratio algorithm as a possible solution to automatically identify these critical regions and suggest metabolic engineering strategies. We examined the accuracy of this algorithm using an Arabidopsis genome-scale model and found consistency in the prediction with our experimental data.
Master of Science
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Iizuka, Kazuki. "A novel approach to dynamic flux balance analysis that accounts for the dynamic transfer of information by internal metabolites." Thesis, University of York, 2016. http://etheses.whiterose.ac.uk/21661/.

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Understanding the dynamics of information feedback amongst components of complex biological systems is crucial to the success of engineering desirable metabolic phenotypes. Flux Balance Analysis (FBA) is a structural metabolic modelling procedure that allows for local topological constraints to be related to steady-state global behaviors of metabolic systems. A vast majority of biological systems of interest, such as microbial communities, however do not exist under steady-state conditions. Therefore, extending FBA methods to the dynamical setting has been a major challenge to metabolic modelling. In dynamic FBA (dFBA), the representation of feedback dynamics is made possible by combining the methods of FBA with those of Ordinary Differential Equations (ODE). Although numerous dFBA models have been constructed to date, very little effort has gone into the theoretical analysis of how static FBA models and dynamic ODE models should be combined in dFBA. To develop a better understanding of the mathematical structure of dFBA, we investigate the properties of FBA. In order to predict time-derivatives of population growth, every dFBA model must make the assumption that the underlying metabolic network modeled via FBA optimizes a phenotypic function of growth rate. We show however, that under certain circumstances, this requirement introduces a rigid correspondence between growth rate, and a related quantity, the growth yield. The consequence of this is that the dFBA models become rigid in its predictions, effectively becoming a near-static representation of metabolism. In this thesis, we show that this tight correspondence between yield and rate may be broken by combining two inversely related approaches to formulating the FBA problem.
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Books on the topic "Flux-balance analysi"

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van der Hoeven, Frank, and Alexander Wandl. Hotterdam: How space is making Rotterdam warmer, how this affects the health of its inhabitants, and what can be done about it. TU Delft Open, 2015. http://dx.doi.org/10.47982/bookrxiv.1.

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Heat waves will occur in Rotterdam with greater frequency in the future. Those affected most will be the elderly – a group that is growing in size. In the light of the Paris heat wave of August 2003 and the one in Rotterdam in July 2006, mortality rates among the elderly in particular are likely to rise in the summer. METHOD The aim of the Hotterdam research project was to gain a better understanding of urban heat. The heat was measured and the surface energy balance modelled from that perspective. Social and physical features of the city we identified in detail with the help of satellite images, GIS and 3D models. We determined the links between urban heat/surface energy balance and the social/physical features of Rotterdam by multivariable regression analysis. The crucial elements of the heat problem were then clustered and illustrated on a social and a physical heat map. RESULTS The research project produced two heat maps, an atlas of underlying data and a set of adaptation measures which, when combined, will make the city of Rotterdam and its inhabitants more aware and less vulnerable to heat wave-related health effects. CONCLUSION In different ways, the pre-war districts of the city (North, South, and West) are warmer and more vulnerable to urban heat than are other areas of Rotterdam. The temperature readings that we carried out confirm these findings as far as outdoor temperatures are concerned. Indoor temperatures vary widely. Homes seem to have their particular dynamics, in which the house’s age plays a role. The above-average mortality of those aged 75 and over during the July 2006 heat wave in Rotterdam can be explained by a) the concentration of people in this age group, b) the age of the homes they live in, and c) the sum of sensible heat and ground heat flux. A diverse mix of impervious surfaces, surface water, foliage, building envelopes and shade make one area or district warmer than another. Adaptation measures are in the hands of residents, homeowners and the local council alike, and relate to changing behaviour, physical measures for homes, and urban design respectively.
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Book chapters on the topic "Flux-balance analysi"

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Rajvanshi, Meghna, and Kareenhalli V. Venkatesh. "Flux Balance Analysis." In Encyclopedia of Systems Biology, 749–52. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_1085.

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Matsuoka, Yu, and Kazuyuki Shimizu. "Metabolic Flux Analysis for Escherichia coli by Flux Balance Analysis." In Methods in Molecular Biology, 237–60. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-1170-7_15.

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Norsigian, Charles J., Xin Fang, Bernhard O. Palsson, and Jonathan M. Monk. "Pangenome Flux Balance Analysis Toward Panphenomes." In The Pangenome, 219–32. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38281-0_10.

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Gomez, Jose Alberto, and Paul I. Barton. "Dynamic Flux Balance Analysis Using DFBAlab." In Methods in Molecular Biology, 353–70. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-7528-0_16.

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Oberhardt, Matthew A., Arvind K. Chavali, and Jason A. Papin. "Flux Balance Analysis: Interrogating Genome-Scale Metabolic Networks." In Methods in Molecular Biology, 61–80. Totowa, NJ: Humana Press, 2009. http://dx.doi.org/10.1007/978-1-59745-525-1_3.

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St. John, Peter C., and Yannick J. Bomble. "Software and Methods for Computational Flux Balance Analysis." In Methods in Molecular Biology, 165–77. New York, NY: Springer US, 2020. http://dx.doi.org/10.1007/978-1-0716-0195-2_13.

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Lotz, Katrin, Anja Hartmann, Eva Grafahrend-Belau, Falk Schreiber, and Björn H. Junker. "Elementary Flux Modes, Flux Balance Analysis, and Their Application to Plant Metabolism." In Methods in Molecular Biology, 231–52. Totowa, NJ: Humana Press, 2013. http://dx.doi.org/10.1007/978-1-62703-661-0_14.

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Curran, Kathleen A., Nathan C. Crook, and Hal S. Alper. "Using Flux Balance Analysis to Guide Microbial Metabolic Engineering." In Methods in Molecular Biology, 197–216. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-61779-483-4_13.

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Grafahrend-Belau, Eva, Astrid Junker, Falk Schreiber, and Björn H. Junker. "Flux Balance Analysis as an Alternative Method to Estimate Fluxes Without Labeling." In Plant Metabolic Flux Analysis, 281–99. Totowa, NJ: Humana Press, 2013. http://dx.doi.org/10.1007/978-1-62703-688-7_17.

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Rocha, Miguel. "Large Scale Metabolic Characterization Using Flux Balance Analysis and Data Mining." In Adaptive and Natural Computing Algorithms, 336–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37213-1_35.

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Conference papers on the topic "Flux-balance analysi"

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Zheng, Haoran, Hong Zhou, Tie Shen, and Bin Rui. "Flux Balance Analysis Within Physiologically Feasible Region." In 2009 3rd International Conference on Bioinformatics and Biomedical Engineering (iCBBE). IEEE, 2009. http://dx.doi.org/10.1109/icbbe.2009.5162863.

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Zavlanos, Michael M., and A. Agung Julius. "Robust flux balance analysis of metabolic networks." In 2011 American Control Conference. IEEE, 2011. http://dx.doi.org/10.1109/acc.2011.5991248.

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Nair, Nishanth Ulhas, Navin Goyal, and Nagasuma R. Chandra. "Enhanced flux balance analysis to model metabolic networks." In the First ACM International Conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1854776.1854829.

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Luo, Ruoyu, Sha Liao, Bifeng Liu, Manxi Liu, Hongming Zhang, and Qingming Luo. "Flux balance analysis of myocardial mitochondrial metabolic network." In Biomedical Optics 2005, edited by Valery V. Tuchin. SPIE, 2005. http://dx.doi.org/10.1117/12.589567.

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Metri, Rahul, Shikhar Saxena, Madhulika Mishra, and Nagasuma Chandra. "Modelling metabolic rewiring during melanoma progression using flux balance analysis." In 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2017. http://dx.doi.org/10.1109/bibm.2017.8217638.

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Zou, Xiaoling, Danny X. Xiao, and Boming Tang. "Analysis of Road Surface Heat Flux Based on Energy Balance Theory." In International Symposium of Climatic Effects on Pavement and Geotechnical Infrastructure 2013. Reston, VA: American Society of Civil Engineers, 2014. http://dx.doi.org/10.1061/9780784413326.004.

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Qinghua Zhou, Dan Wang, and Momiao Xiong. "Dynamic flux balance analysis of metabolic networks using the penalty function methods." In 2007 IEEE International Conference on Systems, Man and Cybernetics. IEEE, 2007. http://dx.doi.org/10.1109/icsmc.2007.4413786.

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Jiang, Biaobin, David F. Gleich, and Michael Gribskov. "Differential flux balance analysis of quantitative proteomic data on protein interaction networks." In 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP). IEEE, 2015. http://dx.doi.org/10.1109/globalsip.2015.7418343.

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Johari, Surabhi, Priyanka Dey, Ashwani Sharma, Subrata Sinha, Kanwar Narain, and N. C. Barua. "Flux Balance Analysis: An Insilico Analysis of Staphylococcus aureus Cell Wall Biosynthesis Pathway Metabolism." In 2013 International Conference on Machine Intelligence and Research Advancement (ICMIRA). IEEE, 2013. http://dx.doi.org/10.1109/icmira.2013.132.

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Malik, Murniyanti, and Afnizanfaizal Abdullah. "A comparative study between flux balance analysis and kinetic model for C. acetobutylicum." In 2014 8th Malaysian Software Engineering Conference (MySEC). IEEE, 2014. http://dx.doi.org/10.1109/mysec.2014.6986026.

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Reports on the topic "Flux-balance analysi"

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Russell, H. A. J., and S. K. Frey. Canada One Water: integrated groundwater-surface-water-climate modelling for climate change adaptation. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/329092.

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Canada 1 Water is a 3-year governmental multi-department-private-sector-academic collaboration to model the groundwater-surface-water of Canada coupled with historic climate and climate scenario input. To address this challenge continental Canada has been allocated to one of 6 large watershed basins of approximately two million km2. The model domains are based on natural watershed boundaries and include approximately 1 million km2 of the United States. In year one (2020-2021) data assembly and validation of some 20 datasets (layers) is the focus of work along with conceptual model development. To support analysis of the entire water balance the modelling framework consists of three distinct components and modelling software. Land Surface modelling with the Community Land Model will support information needed for both the regional climate modelling using the Weather Research &amp; Forecasting model (WRF), and input to HydroGeoSphere for groundwater-surface-water modelling. The inclusion of the transboundary watersheds will provide a first time assessment of water resources in this critical international domain. Modelling is also being integrated with Remote Sensing datasets, notably the Gravity Recovery and Climate Experiment (GRACE). GRACE supports regional scale watershed analysis of total water flux. GRACE along with terrestrial time-series data will serve provide validation datasets for model results to ensure that the final project outputs are representative and reliable. The project has an active engagement and collaborative effort underway to try and maximize the long-term benefit of the framework. Much of the supporting model datasets will be published under open access licence to support broad usage and integration.
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Tanny, Josef, Gabriel Katul, Shabtai Cohen, and Meir Teitel. Micrometeorological methods for inferring whole canopy evapotranspiration in large agricultural structures: measurements and modeling. United States Department of Agriculture, October 2015. http://dx.doi.org/10.32747/2015.7594402.bard.

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Original objectives and revisions The original objectives as stated in the approved proposal were: (1) To establish guidelines for the use of micrometeorological techniques as accurate, reliable and low-cost tools for continuous monitoring of whole canopy ET of common crops grown in large agricultural structures. (2) To adapt existing methods for protected cultivation environments. (3) To combine previously derived theoretical models of air flow and scalar fluxes in large agricultural structures (an outcome of our previous BARD project) with ET data derived from application of turbulent transport techniques for different crops and structure types. All the objectives have been successfully addressed. The study was focused on both screenhouses and naturally ventilated greenhouses, and all proposed methods were examined. Background to the topic Our previous BARD project established that the eddy covariance (EC) technique is suitable for whole canopy evapotranspiration measurements in large agricultural screenhouses. Nevertheless, the eddy covariance technique remains difficult to apply in the farm due to costs, operational complexity, and post-processing of data – thereby inviting alternative techniques to be developed. The subject of this project was: 1) the evaluation of four turbulent transport (TT) techniques, namely, Surface Renewal (SR), Flux-Variance (FV), Half-order Time Derivative (HTD) and Bowen Ratio (BR), whose instrumentation needs and operational demands are not as elaborate as the EC, to estimate evapotranspiration within large agricultural structures; and 2) the development of mathematical models able to predict water savings and account for the external environmental conditions, physiological properties of the plant, and structure properties as well as to evaluate the necessary micrometeorological conditions for utilizing the above turbulent transfer methods in such protected environments. Major conclusions and achievements The major conclusions are: (i) the SR and FV techniques were suitable for reliable estimates of ET in shading and insect-proof screenhouses; (ii) The BR technique was reliable in shading screenhouses; (iii) HTD provided reasonable results in the shading and insect proof screenhouses; (iv) Quality control analysis of the EC method showed that conditions in the shading and insect proof screenhouses were reasonable for flux measurements. However, in the plastic covered greenhouse energy balance closure was poor. Therefore, the alternative methods could not be analyzed in the greenhouse; (v) A multi-layered flux footprint model was developed for a ‘generic’ crop canopy situated within a protected environment such as a large screenhouse. The new model accounts for the vertically distributed sources and sinks within the canopy volume as well as for modifications introduced by the screen on the flow field and microenvironment. The effect of the screen on fetch as a function of its relative height above the canopy is then studied for the first time and compared to the case where the screen is absent. The model calculations agreed with field experiments based on EC measurements from two screenhouse experiments. Implications, both scientific and agricultural The study established for the first time, both experimentally and theoretically, the use of four simple TT techniques for ET estimates within large agricultural screenhouses. Such measurements, along with reliable theoretical models, will enable the future development of lowcost ET monitoring system which will be attainable for day-to-day use by growers in improving irrigation management.
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