Relevant bibliographies by topics / Genome-Scale Metabolic Network (GSMN)

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Academic literature on the topic 'Genome-Scale Metabolic Network (GSMN)'

Author: Grafiati
Published: 25 January 2025
Last updated: 31 July 2025

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Journal articles on the topic "Genome-Scale Metabolic Network (GSMN)"

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Moretti, Sébastien, Van Du T. Tran, Florence Mehl, Mark Ibberson, and Marco Pagni. "MetaNetX/MNXref: unified namespace for metabolites and biochemical reactions in the context of metabolic models." Nucleic Acids Research 49, no. D1 (2020): D570—D574. http://dx.doi.org/10.1093/nar/gkaa992.

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Abstract MetaNetX/MNXref is a reconciliation of metabolites and biochemical reactions providing cross-links between major public biochemistry and Genome-Scale Metabolic Network (GSMN) databases. The new release brings several improvements with respect to the quality of the reconciliation, with particular attention dedicated to preserving the intrinsic properties of GSMN models. The MetaNetX website (https://www.metanetx.org/) provides access to the full database and online services. A major improvement is for mapping of user-provided GSMNs to MXNref, which now provides diagnostic messages abou
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Nègre, Delphine, Abdelhalim Larhlimi, and Samuel Bertrand. "Reconciliation and evolution of Penicillium rubens genome-scale metabolic networks–What about specialised metabolism?" PLOS ONE 18, no. 8 (2023): e0289757. http://dx.doi.org/10.1371/journal.pone.0289757.

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In recent years, genome sequencing of filamentous fungi has revealed a high proportion of specialised metabolites with growing pharmaceutical interest. However, detecting such metabolites through in silico genome analysis does not necessarily guarantee their expression under laboratory conditions. However, one plausible strategy for enabling their production lies in modifying the growth conditions. Devising a comprehensive experimental design testing in different culture environments is time-consuming and expensive. Therefore, using in silico modelling as a preliminary step, such as Genome-Sca
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Nègre, Aite, Belcour, et al. "Genome–Scale Metabolic Networks Shed Light on the Carotenoid Biosynthesis Pathway in the Brown Algae Saccharina japonica and Cladosiphon okamuranus." Antioxidants 8, no. 11 (2019): 564. http://dx.doi.org/10.3390/antiox8110564.

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Understanding growth mechanisms in brown algae is a current scientific and economic challenge that can benefit from the modeling of their metabolic networks. The sequencing of the genomes of Saccharina japonica and Cladosiphon okamuranus has provided the necessary data for the reconstruction of Genome–Scale Metabolic Networks (GSMNs). The same in silico method deployed for the GSMN reconstruction of Ectocarpus siliculosus to investigate the metabolic capabilities of these two algae, was used. Integrating metabolic profiling data from the literature, we provided functional GSMNs composed of an
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Thananusak, Roypim, Kobkul Laoteng, Nachon Raethong, Yu Zhang, and Wanwipa Vongsangnak. "Metabolic Responses of Carotenoid and Cordycepin Biosynthetic Pathways in Cordyceps militaris under Light-Programming Exposure through Genome-Wide Transcriptional Analysis." Biology 9, no. 9 (2020): 242. http://dx.doi.org/10.3390/biology9090242.

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Cordyceps militaris is currently exploited for commercial production of specialty products as its biomass constituents are enriched in bioactive compounds, such as cordycepin. The rational process development is important for economically feasible production of high quality bioproducts. Light is an abiotic factor affecting the cultivation process of this entomopathogenic fungus, particularly in its carotenoid formation. To uncover the cell response to light exposure, this study aimed to systematically investigate the metabolic responses of C. militaris strain TBRC6039 using integrative genome-
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Rodríguez-Mier, Pablo, Nathalie Poupin, Carlo de Blasio, Laurent Le Cam, and Fabien Jourdan. "DEXOM: Diversity-based enumeration of optimal context-specific metabolic networks." PLOS Computational Biology 17, no. 2 (2021): e1008730. http://dx.doi.org/10.1371/journal.pcbi.1008730.

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The correct identification of metabolic activity in tissues or cells under different conditions can be extremely elusive due to mechanisms such as post-transcriptional modification of enzymes or different rates in protein degradation, making difficult to perform predictions on the basis of gene expression alone. Context-specific metabolic network reconstruction can overcome some of these limitations by leveraging the integration of multi-omics data into genome-scale metabolic networks (GSMN). Using the experimental information, context-specific models are reconstructed by extracting from the g
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Borah, Khushboo, Jacque-Lucca Kearney, Ruma Banerjee, et al. "GSMN-ML- a genome scale metabolic network reconstruction of the obligate human pathogen Mycobacterium leprae." PLOS Neglected Tropical Diseases 14, no. 7 (2020): e0007871. http://dx.doi.org/10.1371/journal.pntd.0007871.

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Zhang, Lingrui, Bin Wang, Ruiqi Zhang, et al. "Screening of Potential Drug Targets Based on the Genome-Scale Metabolic Network Model of Vibrio parahaemolyticus." Current Issues in Molecular Biology 47, no. 7 (2025): 575. https://doi.org/10.3390/cimb47070575.

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Vibrio parahaemolyticus is a pathogenic bacterium widely distributed in marine environments, posing significant threats to aquatic organisms and human health. The overuse and misuse of antibiotics has led to the development of multidrug- and pan-resistant V. parahaemolyticus strains. There is an urgent need for novel antibacterial therapies with innovative mechanisms of action. In this work, a genome-scale metabolic network model (GMSN) of V. parahaemolyticus, named VPA2061, was reconstructed to predict the metabolites that can be explored as potential drug targets for eliminating V. parahaemo
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Liu, Lili, Qian Mei, Zhenning Yu, Tianhao Sun, Zijun Zhang, and Ming Chen. "An Integrative Bioinformatics Framework for Genome-scale Multiple Level Network Reconstruction of Rice." Journal of Integrative Bioinformatics 10, no. 2 (2013): 94–102. http://dx.doi.org/10.1515/jib-2013-223.

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Summary Understanding how metabolic reactions translate the genome of an organism into its phenotype is a grand challenge in biology. Genome-wide association studies (GWAS) statistically connect genotypes to phenotypes, without any recourse to known molecular interactions, whereas a molecular mechanistic description ties gene function to phenotype through gene regulatory networks (GRNs), protein-protein interactions (PPIs) and molecular pathways. Integration of different regulatory information levels of an organism is expected to provide a good way for mapping genotypes to phenotypes. However,
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Gupta, Ankit, Ahmad Ahmad, Dipesh Chothwe, Midhun K. Madhu, Shireesh Srivastava, and Vineet K. Sharma. "Genome-scale metabolic reconstruction and metabolic versatility of an obligate methanotrophMethylococcus capsulatusstr. Bath." PeerJ 7 (June 14, 2019): e6685. http://dx.doi.org/10.7717/peerj.6685.

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The increase in greenhouse gases with high global warming potential such as methane is a matter of concern and requires multifaceted efforts to reduce its emission and increase its mitigation from the environment. Microbes such as methanotrophs can assist in methane mitigation. To understand the metabolic capabilities of methanotrophs, a complete genome-scale metabolic model (GSMM) of an obligate methanotroph,Methylococcus capsulatusstr. Bath was reconstructed. The model contains 535 genes, 899 reactions and 865 metabolites and is namediMC535. The predictive potential of the model was validate
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Brunner, James D., Laverne A. Gallegos-Graves, and Marie E. Kroeger. "Inferring microbial interactions with their environment from genomic and metagenomic data." PLOS Computational Biology 19, no. 11 (2023): e1011661. http://dx.doi.org/10.1371/journal.pcbi.1011661.

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Microbial communities assemble through a complex set of interactions between microbes and their environment, and the resulting metabolic impact on the host ecosystem can be profound. Microbial activity is known to impact human health, plant growth, water quality, and soil carbon storage which has lead to the development of many approaches and products meant to manipulate the microbiome. In order to understand, predict, and improve microbial community engineering, genome-scale modeling techniques have been developed to translate genomic data into inferred microbial dynamics. However, these tech
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Dissertations / Theses on the topic "Genome-Scale Metabolic Network (GSMN)"

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Negre, Delphine. "Rationalisation de l’Accès aux Produits Naturels Fongiques par une Approche OSMAC in silico : Cas d’étude avec la modélisation du métabolisme de Penicillium rubens." Electronic Thesis or Diss., Nantes Université, 2024. http://www.theses.fr/2024NANU4038.

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Face à la résistance accrue aux antibiotiques menaçant la santé publique, la prospection de nouvelles molécules biologiquement actives est pressante. Les champignons filamenteux se distinguent par leur capacité à synthétiser une large gamme de produits naturels, sous l’influence de clusters de gènes biosynthétiques (BGC) qui orchestrent la production de métabolites spécialisés. Toutefois, de nombreux produits issus de ces BGCs n’ont pas encore été caractérisés et leur chimiodiversité demeure sous-explorée en raison de l’incapacité à activer l’ensemble de leur potentiel en laboratoire. L’approc
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Gautam, Jyotshana. "Genome-Scale Metabolic Network Reconstruction of Thermotoga sp.Strain RQ7." Bowling Green State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1605228158638208.

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xinjian, qi. "COMPUTATIONAL ANALYSIS, VISUALIZATION AND TEXT MINING OF METABOLIC NETWORKS." Case Western Reserve University School of Graduate Studies / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=case1378479338.

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Loira, Nicolas. "Scaffold-based reconstruction method of genome-scale metabolic models." Thesis, Bordeaux 1, 2012. http://www.theses.fr/2012BOR14484/document.

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La compréhension des organismes vivant a été une quête pendant longtemps. Depuisles premiers progrès des derniers siècles, nous sommes arrivés jusqu’au point où desquantités massives de données et d’information sont constamment générées. Bien que,jusqu’au présent la plupart du travail a été concentré sur la génération d’un catalogued’éléments biologiques, ce n’est pas que récemment qu’un effort coordonné pour découvrirles réseaux de relations entre ces parties a été constaté. Nous nous sommes intéressésà comprendre non pas seulement ces réseaux, mais aussi la façon dont, à partir de sesconnexi
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Kalapanulak, Saowalak. "High quality genome-scale metabolic network reconstruction of Mycobacterium tuberculosis and comparison with human metabolic network : application for drug targets identification." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/3925.

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Mycobacterium tuberculosis (Mtb), a pathogenic bacterium, is the causative agent in the vast majority of human tuberculosis (TB) cases. Nearly one-third of the world’s population has been affected by TB and annually two million deaths result from the disease. Because of the high cost of medication for a long term treatment with multiple drugs and the increase of multidrug-resistant Mtb strains, faster-acting drugs and more effective vaccines are urgently demanded. Several metabolic pathways of Mtb are attractive for identifying novel drug targets against TB. Hence, a high quality genome-scale
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Vieira, Milreu Paulo. "Enumerating functional substructures of genome-scale metabolic networks : stories, precursors and organisations." Phd thesis, Université Claude Bernard - Lyon I, 2012. http://tel.archives-ouvertes.fr/tel-00850704.

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In this thesis, we presented three different methods for enumerating special subnetworks containedin a metabolic network: metabolic stories, minimal precursor sets and chemical organisations. Foreach of the three methods, we gave theoretical results, and for the two first ones, we further providedan illustration on how to apply them in order to study the metabolic behaviour of living organisms.Metabolic stories are defined as maximal directed acyclic graphs whose sets of sources and targets arerestricted to a subset of the nodes. The initial motivation of this definition was to analyse metabol
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Griffin, Daniel C. "Investigating the Clostridium botulinum neurotoxin production process using a genome-scale metabolic network enhanced surrogate system." Thesis, University of Surrey, 2016. http://epubs.surrey.ac.uk/809809/.

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Clostridium botulinum (C. botulinum) produces a neurotoxin which can be used in a clinical environment to treat diseases and disorders characterised by muscle hypertension or spasm. However, previous research has mostly focused on the biochemical mode of action of the toxin and the disease it manifests. In order to increase our understanding of the process further, this study aimed to investigate the metabolism of various biomarkers, thought to be correlated with neurotoxin biosynthesis. The objective was to increase our understanding of the metabolism which drives the production of C. botulin
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Triana, Dopico Julián. "Model-based analysis and metabolic design of a cyanobacterium for bio-products synthesis." Doctoral thesis, Universitat Politècnica de València, 2014. http://hdl.handle.net/10251/39351.

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The current investigation is aimed at the reconstruction and analysis of genome-scale metabolic models. Specifically, it is focused on the use of mathematical-computational simulations to predict the cellular metabolism behavior towards bio-products production. The photosynthetic cyanobacterium Synechococcus elongatus PCC7942 was studied as biological system. This prokaryotic has been used in several studies as a biological platform for the synthesis of several substances for industrial interest. These studies are based on the advantage of autotrophic systems, which basically requires light a
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TAI, HSIAO-HSIEN, and 戴筱銜. "Metabolic Reprogramming of the Genome-scale Metabolic Network of Liver Deficient." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/73na5f.

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碩士<br>國立中正大學<br>化學工程研究所<br>106<br>This study used the liver as the main axis to exploit the significant flux distribution differences between normal cells and cancer cells to find biomarkers or oncogenes under the case of cancer. Based on the human metabolic network model Recon2.2, and use tissue-specific data from the Human Protein Atlas (HPA), the Virtual Metabolic Human (VMH) to provide the nutrients and Cost Optimization Reaction Dependency Assessment (CORDA) algorithm to generate the model reconstructs of liver health and cancer. Through the use of the Nested Hybrid Differential Evolution
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Dias, Oscar. "Reconstruction of the genome-scale metabolic network of Kluyveromyces lactis." Doctoral thesis, 2013. http://hdl.handle.net/1822/24859.

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System Biology proposes to study biological components, as well as the interactions between them, to understand and predict systems’ behaviour through the use of mathematical models. Under this scope, Genome-Scale Metabolic Models (GSMMs) can be regarded as mathematical representations of the intrinsic metabolic capabilities of a given organism, encoded in its genome, and can be used in a variety of applications like predicting the phenotypical behaviour of a given organism in different environmental and genetic perturbations. The reconstruction of these models comprehends four fundament
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Books on the topic "Genome-Scale Metabolic Network (GSMN)"

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Structure-Based Genome Scale Function Prediction and Reconstruction of the Mycobacterium tuberculosis Metabolic Network. [publisher not identified], 2014.

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Book chapters on the topic "Genome-Scale Metabolic Network (GSMN)"

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Lee, Sang Yup, Seung Bum Sohn, Hyun Uk Kim, et al. "Genome-Scale Network Modeling." In Systems Metabolic Engineering. Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-4534-6_1.

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Kierzek, Andrzej M. "Genome-Scale Metabolic Network." In Encyclopedia of Systems Biology. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_1486.

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Ebenhöh, Oliver, and Stefan Kempa. "Genome-Scale Metabolic Network Inference." In Encyclopedia of Systems Biology. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_1146.

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Fondi, Marco, and Pietro Liò. "Genome-Scale Metabolic Network Reconstruction." In Methods in Molecular Biology. Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-1720-4_15.

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Theorell, Axel, and Jörg Stelling. "Microbial Community Decision Making Models in Batch and Chemostat Cultures." In Computational Methods in Systems Biology. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-85633-5_9.

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AbstractMicrobial community simulations using genome scale metabolic networks (GSMs) are relevant for many application areas, such as the analysis of the human microbiome. Such simulations rely on assumptions about the culturing environment, affecting if the culture may reach a metabolically stationary state with constant microbial concentrations. They also require assumptions on decision making by the microbes: metabolic strategies can be in the interest of individual community members or of the whole community. However, the impact of such common assumptions on community simulation results ha
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Dougherty, Bonnie V., Thomas J. Moutinho, and Jason Papin. "Accelerating the Drug Development Pipeline with Genome-Scale Metabolic Network Reconstructions." In Systems Biology. Wiley-VCH Verlag GmbH & Co. KGaA, 2017. http://dx.doi.org/10.1002/9783527696130.ch5.

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Feist, Adam M., Ines Thiele, and Bernhard Ø. Palsson. "Genome-Scale Reconstruction, Modeling, and Simulation of E. coli℉s Metabolic Network." In Systems Biology and Biotechnology of Escherichia coli. Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-1-4020-9394-4_9.

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Mal, Chittabrata, Ayushman Kumar Banerjee, and Joyabrata Mal. "Genome Scale Pathway-Pathway Co-functional Synergistic Network (PcFSN) in Oryza Sativa." In Proceedings of the Conference BioSangam 2022: Emerging Trends in Biotechnology (BIOSANGAM 2022). Atlantis Press International BV, 2022. http://dx.doi.org/10.2991/978-94-6463-020-6_6.

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AbstractCohesive network modelling and systems biology have emerged as extremely potent tools which helps understanding the combinatorial effects of biomolecules. Synergistic modulation among biomolecules (e.g., enzymes, transcription factors, microRNAs, drugs, etc.) are significant in finding out complex regulatory mechanisms in biological networks and pathways. In some cases, although combinatorial interactions among some biomolecules in specific biological networks is available, our knowledge in that particular domain is very limited with context to a genomic scale. Here we explore the path
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Sadhukhan, Priyanka P., and Anu Raghunathan. "Investigating Host–Pathogen Behavior and Their Interaction Using Genome-Scale Metabolic Network Models." In Methods in Molecular Biology. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-1115-8_29.

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Chandrasekaran, Sriram. "A Protocol for the Construction and Curation of Genome-Scale Integrated Metabolic and Regulatory Network Models." In Methods in Molecular Biology. Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9142-6_14.

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Conference papers on the topic "Genome-Scale Metabolic Network (GSMN)"

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Bautista, Eddy J., and Ranjan Srivastava. "Enhancing genetic algorithm-based genome-scale metabolic network curation efficiency." In GECCO '14: Genetic and Evolutionary Computation Conference. ACM, 2014. http://dx.doi.org/10.1145/2576768.2598218.

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QUEK, LAKE-EE, and LARS K. NIELSEN. "ON THE RECONSTRUCTION OF THE MUS MUSCULUS GENOME-SCALE METABOLIC NETWORK MODEL." In Proceedings of the 19th International Conference. IMPERIAL COLLEGE PRESS, 2008. http://dx.doi.org/10.1142/9781848163324_0008.

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Aggarwal, Shilpi, Iftekhar A. Karimi, and Dong-Yup Lee. "Reconstruction and Analysis of Genome Scale Metabolic Network of Rhodococcus Erythropolis for Improved Desulfurization." In 14th Asia Pacific Confederation of Chemical Engineering Congress. Research Publishing Services, 2012. http://dx.doi.org/10.3850/978-981-07-1445-1_470.

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Shimizu, Hiroshi, Yohei Shinfuku, Masahiro Sono, Chikara Furusawa, and Takashi Hirasawa. "Metabolic flux balance analysis of an industrially useful microorganism Corynebacerium glutamicum by a genome-scale reconstructed model." In 3d International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems. ICST, 2008. http://dx.doi.org/10.4108/icst.bionetics2008.4704.

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