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  2020 (8)
Metabolic model guided strain design of cyanobacteria. Hendry, J. I; Bandyopadhyay, A.; Srinivasan, S.; Pakrasi, H. B; and Maranas, C. D Current opinion in biotechnology, 64: 17–23. 2020.
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From directed evolution to computational enzyme engineering—A review. Chowdhury, R.; and Maranas, C. D AIChE Journal, 66(3): e16847. 2020.
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K-FIT: An accelerated kinetic parameterization algorithm using steady-state fluxomic data. Gopalakrishnan, S.; Dash, S.; and Maranas, C. Metabolic Engineering. 2020.
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Artificial water channels enable fast and selective water permeation through water-wire networks. Song, W.; Joshi, H.; Chowdhury, R.; Najem, J. S; Shen, Y.; Lang, C.; Henderson, C. B; Tu, Y.; Farell, M.; Pitz, M. E; and others Nature Nanotechnology, 15(1): 73–79. 2020.
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Author Correction: Artificial water channels enable fast and selective water permeation through water-wire networks. Song, W.; Joshi, H.; Chowdhury, R.; Najem, J. S; Shen, Y.; Lang, C.; Henderson, C. B; Tu, Y.; Farell, M.; Pitz, M. E; and others Nature nanotechnology, 15(2): 162–162. 2020.
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SNPeffect: Identifying Functional Roles of SNPs using Metabolic Networks. Sarkar, D.; and Maranas, C. D The Plant Journal. 2020.
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In Vivo Thermodynamic Analysis of Glycolysis in Clostridium thermocellum and Thermoanaerobacterium saccharolyticum Using 13C and 2H Tracers. Jacobson, T. B; Korosh, T. K; Stevenson, D. M; Foster, C.; Maranas, C.; Olson, D. G; Lynd, L. R; and Amador-Noguez, D. mSystems, 5(2). 2020.
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Challenges of cultivated meat production and applications of genome-scale metabolic modeling. Suthers, P. F; and Maranas, C. D AIChE Journal. 2020.
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  2019 (22)
Reply to Zhou and Li: Plasticity of the genomic haplotype of Synechococcus elongatus leads to rapid strain adaptation under laboratory conditions. Ungerer, J.; Wendt, K. E; Hendry, J. I; Maranas, C. D; and Pakrasi, H. B Proceedings of the National Academy of Sciences, 116(10): 3946–3947. 2019.
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Thermodynamic analysis of the pathway for ethanol production from cellobiose in Clostridium thermocellum. Dash, S.; Olson, D. G; Chan, S. H. J.; Amador-Noguez, D.; Lynd, L. R; and Maranas, C. D Metabolic engineering, 55: 161–169. 2019.
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From 13 c Labeling Data to a Core Metabolism Kinetic Model: A Kinetic Model Parameterization Pipeline. Foster, C.; Gopalakrishnan, S.; Srinivasan, S.; Dash, S.; Antoniewicz, M. R; and Maranas, C. D In 2019 AIChE Annual Meeting, 2019. AIChE
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From Escherichia coli mutant 13C labeling data to a core kinetic model: A kinetic model parameterization pipeline. Foster, C. J; Gopalakrishnan, S.; Antoniewicz, M. R; and Maranas, C. D PLoS computational biology, 15(9): e1007319. 2019.
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Looking Beyond GWAS: Identifying Functional Roles of SNPs Using Metabolic Networks in Arabidopsis and Populus. Sarkar, D.; and Maranas, C. In 2019 AIChE Annual Meeting, 2019. AIChE
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Directed evolution reveals the functional sequence space of an adenylation domain specificity code. Throckmorton, K.; Vinnik, V.; Chowdhury, R.; Cook, T.; Chevrette, M. G; Maranas, C.; Pfleger, B.; and Thomas, M. G. ACS chemical biology, 14(9): 2044–2054. 2019.
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Poredesigner: A Computational Tool for the Design of Membrane Pores for Separations. Chowdhury, R.; and Maranas, C. In 2019 AIChE Annual Meeting, 2019. AIChE
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pareto optimality explanation of the Glycolytic Alternatives in Nature. Ng, C. Y.; Wang, L.; Chowdhury, A.; and Maranas, C. D Scientific reports, 9(1): 1–15. 2019.
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Angstrom-scale separations by design using precision biomimetic membrane. Maranas, C. D; Kumar, M.; Chowdhury, R.; and Ren, T. October~31 2019. US Patent App. 16/397,416
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EcoFABs: advancing microbiome science through standardized fabricated ecosystems. Zengler, K.; Hofmockel, K.; Baliga, N. S; Behie, S. W; Bernstein, H. C; Brown, J. B; Dinneny, J. R; Floge, S. A; Forry, S. P; Hess, M.; and others Nature methods, 16(7): 567–571. 2019.
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Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v. 3.0. Heirendt, L.; Arreckx, S.; Pfau, T.; Mendoza, S. N; Richelle, A.; Heinken, A.; Haraldsdóttir, H. S; Wachowiak, J.; Keating, S. M; Vlasov, V.; and others Nature protocols, 14(3): 639–702. 2019.
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Gene construct encoding mutant thioesterase, mutant thioesterase encoded thereby, transformed host cell containing the gene construct, and method of using them to produce medium-chain fatty acids. Pfleger, B. F; Hernandez-Lozada, N. J.; Maranas, C.; and Grisewood, M. December~26 2019. US Patent App. 16/535,305
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Genome-scale fluxome of Synechococcus elongatus UTEX 2973 using transient 13C-labeling data. Hendry, J. I; Gopalakrishnan, S.; Ungerer, J.; Pakrasi, H. B; Tang, Y. J; and Maranas, C. D Plant physiology, 179(2): 761–769. 2019.
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Enhanced Virus Removal in a Practical Sand Filter. Pei, A.; Samineni, L.; Kuehster, L.; Dickey, R.; Wang, H.; Espinoza, P.; Chowdhury, R.; Maranas, C.; Kumar, M.; and Velegol, S. B In 2019 AIChE Annual Meeting, 2019. AIChE
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Predicting the longitudinally and radially varying gut microbiota composition using multi-scale microbial metabolic modeling. Chan, S. H.; Friedman, E. S; Wu, G. D; and Maranas, C. D Processes, 7(7): 394. 2019.
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Computational optimization of a thioesterase for selective chain-length product distribution. Jindra, M.; Chowdhury, R.; Pfleger, B.; and Maranas, C. In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 257, 2019. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Engineering microbial chemical factories using metabolic models. Sarkar, D.; and Maranas, C. D BMC Chemical Engineering, 1(1): 1–11. 2019.
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A diurnal flux balance model of Synechocystis sp. PCC 6803 metabolism. Sarkar, D.; Mueller, T. J; Liu, D.; Pakrasi, H. B; and Maranas, C. D PLoS computational biology, 15(1): e1006692. 2019.
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Identifying functional roles of SNPs using metabolic networks for improved plant breeding. Maranas, C.; and Sarkar, D. . 2019.
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7 Log Virus Removal in a Simple Functionalized Sand Filter. Samineni, L.; Xiong, B.; Chowdhury, R.; Pei, A.; Kuehster, L.; Wang, H.; Dickey, R.; Soto, P. E.; Massenburg, L.; Nguyen, T. H; and others Environmental science & technology, 53(21): 12706–12714. 2019.
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PoreDesigner: A computational tool for the design of membrane pores for separations. Maranas, C.; Chowdhury, R.; and Kumar, M. . 2019.
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A comprehensive genome-scale model for Rhodosporidium toruloides IFO0880 accounting for functional genomics and phenotypic data. Dinh, H. V; Suthers, P. F; Chan, S. H. J.; Shen, Y.; Xiao, T.; Deewan, A.; Jagtap, S. S; Zhao, H.; Rao, C. V; Rabinowitz, J. D; and others Metabolic engineering communications, 9: e00101. 2019.
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  2018 (17)
Ensemble cell-wide kinetic modeling of anaerobic organisms to support fuels and chemicals production. Maranas, C. D Technical Report Pennsylvania State Univ., University Park, PA (United States), 2018.
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Engineering of E. coli inherent fatty acid biosynthesis capacity to increase octanoic acid production. Tan, Z.; Yoon, J. M.; Chowdhury, A.; Burdick, K.; Jarboe, L. R; Maranas, C. D; and Shanks, J. V Biotechnology for biofuels, 11(1): 87. 2018.
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PoreDesigner for tuning solute selectivity in a robust and highly permeable outer membrane pore. Chowdhury, R.; Ren, T.; Shankla, M.; Decker, K.; Grisewood, M.; Prabhakar, J.; Baker, C.; Golbeck, J. H; Aksimentiev, A.; Kumar, M.; and others Nature communications, 9(1): 1–10. 2018.
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Computationally exploring and alleviating the kinetic bottlenecks of anaerobic methane oxidation. Grisewood, M. J; Ferry, J. G; and Maranas, C. D Frontiers in Environmental Science, 6: 84. 2018.
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Biomimetic Membrane Design Principles for Angstrom Scale Separation. Ren, T.; Chowdhury, R.; Butler, P.; Maranas, C.; and Kumar, M. Biophysical Journal, 114(3): 361a. 2018.
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Elucidation of photoautotrophic carbon flux topology in Synechocystis PCC 6803 using genome-scale carbon mapping models. Gopalakrishnan, S.; Pakrasi, H. B; and Maranas, C. D Metabolic engineering, 47: 190–199. 2018.
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The biochemistry and physiology of respiratory-driven reversed methanogenesis. Nazem-Bokaee, H.; Yan, Z.; Maranas, C. D; and Ferry, J. G In Methane Biocatalysis: Paving the Way to Sustainability, pages 183–197. Springer, 2018.
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Pathway design using de novo steps through uncharted biochemical spaces. Kumar, A.; Wang, L.; Ng, C. Y.; and Maranas, C. D Nature communications, 9(1): 1–15. 2018.
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MinGenome: an in silico top-down approach for the synthesis of minimized genomes. Wang, L.; and Maranas, C. D ACS synthetic biology, 7(2): 462–473. 2018.
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OptMAVEn-2.0: de novo design of variable antibody regions against targeted antigen epitopes. Chowdhury, R.; Allan, M. F; and Maranas, C. D Antibodies, 7(3): 23. 2018.
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Metabolic modeling of microbial communities. Chan, S. H. J.; and Maranas, C. In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 255, 2018. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Modeling plant metabolism: advancements and future capabilities. Simons-Senftle, M. N; Sarkar, D.; and Maranas, C. D In Engineering Nitrogen Utilization in Crop Plants, pages 57–76. Springer, 2018.
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Accelerating flux balance calculations in genome-scale metabolic models by localizing the application of loopless constraints. Chan, S. H.; Wang, L.; Dash, S.; and Maranas, C. D Bioinformatics, 34(24): 4248–4255. 2018.
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A prospective study on the fermentation landscape of gaseous substrates to biorenewables using Methanosarcina acetivorans metabolic model. Nazem-Bokaee, H.; and Maranas, C. D Frontiers in microbiology, 9: 1855. 2018.
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CORRECTION: Exploiting the Genetic Diversity of Maize Using a Combined Metabolomic, Enzyme Activity Profiling, and Metabolic Modelling Approach to Link Leaf Physiology to Kernel Yield. Cañas, R. A; Yesbergenova-Cuny, Z.; Simons, M.; Chardon, F.; Armengaud, P.; Quilleré, I.; Cukier, C.; Gibon, Y.; Limami, A. M; Nicolas, S. D; and others The Plant Cell,tpc–00273. 2018.
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Comparative genomics reveals the molecular determinants of rapid growth of the cyanobacterium Synechococcus elongatus UTEX 2973. Ungerer, J.; Wendt, K. E; Hendry, J. I; Maranas, C. D; and Pakrasi, H. B Proceedings of the National Academy of Sciences, 115(50): E11761–E11770. 2018.
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Exploring the combinatorial space of complete pathways to chemicals. Wang, L.; Ng, C. Y.; Dash, S.; and Maranas, C. D Biochemical Society Transactions, 46(3): 513–522. 2018.
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  2017 (28)
Identifying the metabolic differences of a fast-growth phenotype in Synechococcus UTEX 2973. Mueller, T. J; Ungerer, J. L; Pakrasi, H. B; and Maranas, C. D Scientific reports, 7(1): 1–8. 2017.
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Development of a core Clostridium thermocellum kinetic metabolic model consistent with multiple genetic perturbations. Dash, S.; Khodayari, A.; Zhou, J.; Holwerda, E. K; Olson, D. G; Lynd, L. R; and Maranas, C. D Biotechnology for biofuels, 10(1): 108. 2017.
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Multilevel engineering of the upstream aromatic module in Saccharomyces cerevisiae for high production of polymer and drug precursors. Suastegui, M.; Shao, Z.; Ng, C.; and Maranas, C. In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 253, 2017. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Nature inspired antibody design and optimization. Tessier, P.; Tiller, K.; Rabia, L.; Julian, M.; Li, L.; Ludwig, S.; Garde, S.; Chowdhury, R.; Maranas, C.; and Kumar, S. . 2017.
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Cyanobacterial genome-scale carbon mapping models for genome-scale 13C-metabolic flux elucidation. Gopalakrishnan, S.; and Maranas, C. In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 253, 2017. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Systematic Redesigning of E. coli water Channel Porin, Ompf, for Desired Pore Size Using Iterative Protein Redesign and Optimization (IPRO) Suite. Chowdhury, R.; Ren, T.; Decker, K.; Aksimentiev, A.; Kumar, M.; and Maranas, C. In 2017 AIChE Annual Meeting, 2017. AIChE
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A review of computational tools for design and reconstruction of metabolic pathways. Wang, L.; Dash, S.; Ng, C. Y.; and Maranas, C. D Synthetic and systems biotechnology, 2(4): 243–252. 2017.
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SteadyCom: Predicting microbial abundances while ensuring community stability. Chan, S. H. J.; Simons, M. N; and Maranas, C. D PLoS computational biology, 13(5): e1005539. 2017.
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Optimization Driven Top-Down Synthesis of Genome Minimized Strains for Bioproduction. Wang, L.; and Maranas, C. D In 2017 AIChE Annual Meeting, 2017. AIChE
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Computational redesign of acyl-ACP thioesterase with improved selectivity towards medium chain fatty acids at high production levels. Maranas, C. D; Grisewood, M. J; Hernandez Lozada, N. J; and Pfleger, B. F . 2017.
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Clostridium butyricum maximizes growth while minimizing enzyme usage and ATP production: metabolic flux distribution of a strain cultured in glycerol. Serrano-Bermúdez, L. M.; Barrios, A. F. G.; Maranas, C. D; and Montoya, D. BMC systems biology, 11(1): 58. 2017.
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Method for designing overall stoichiometric conversions and intervening metabolic reactions. Chowdhury, A.; and Maranas, C. D April~27 2017. US Patent App. 15/146,602
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Constructing Predictive Kinetic Models of Metabolism with Transcriptional Regulation. Dash, S.; Gopalakrishnan, S.; Foster, C.; and Maranas, C. D In 2017 AIChE Annual Meeting, 2017. AIChE
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Metabolic Modeling of Microbial Communities. Maranas, C. D In 2017 AIChE Annual Meeting, 2017. AIChE
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Exploiting the Genetic Diversity of Maize Using a Combined Metabolomic, Enzyme Activity Profiling, and Metabolic Modeling Approach to Link Leaf Physiology to Kernel Yield. Canas-Pendon, R.; Yesbergenova-Cuny, Z.; Simons, M.; Chardon, F.; Armengaud, P.; Quillere, I.; Cukier, C.; Gibon, Y.; Limami, A.; Nicolas, S.; and others . 2017.
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De novo design of antibody complementarity determining regions binding a FLAG tetra-peptide. Entzminger, K. C; Hyun, J.; Pantazes, R. J; Patterson-Orazem, A. C; Qerqez, A. N; Frye, Z. P; Hughes, R. A; Ellington, A. D; Lieberman, R. L; Maranas, C. D; and others Scientific reports, 7(1): 1–11. 2017.
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Uncovering and Correcting the Effect of Biomass Molecular Weight Discrepancies in FBA Calculations. Chan, S. H. J.; Cai, J.; Wang, L.; Simons-Senftle, M.; and Maranas, C. D In 2017 AIChE Annual Meeting, 2017. AIChE
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Development of a Knowledgebase (MetRxn) of Metabolites, Reactions and Atom Mappings to Accelerate Discovery and Redesign. Maranas, C. D Technical Report Pennsylvania State Univ., University Park, PA (United States), 2017.
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Computational redesign of acyl-ACP thioesterase with improved selectivity toward medium-chain-length fatty acids. Grisewood, M. J; Hernández-Lozada, N. J; Thoden, J. B; Gifford, N. P; Mendez-Perez, D.; Schoenberger, H. A; Allan, M. F; Floy, M. E; Lai, R.; Holden, H. M; and others ACS catalysis, 7(6): 3837–3849. 2017.
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Metabolic engineering of bacteria for production of oleochemicals. Hernandez, N.; Grisewood, M.; Maranas, C.; and Pfleger, B. In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 253, 2017. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Standardizing biomass reactions and ensuring complete mass balance in genome-scale metabolic models. Chan, S. H.; Cai, J.; Wang, L.; Simons-Senftle, M. N; and Maranas, C. D Bioinformatics, 33(22): 3603–3609. 2017.
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Deciphering cyanobacterial phenotypes for fast photoautotrophic growth via isotopically nonstationary metabolic flux analysis. Abernathy, M. H; Yu, J.; Ma, F.; Liberton, M.; Ungerer, J.; Hollinshead, W. D; Gopalakrishnan, S.; He, L.; Maranas, C. D; Pakrasi, H. B; and others Biotechnology for biofuels, 10(1): 273. 2017.
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Elucidation of Carbon Flux Topology Representing Photoautotrophic Growth in Synechocystis PCC 6803 Using Genome-Scale Isotopic Instationary Metabolic Flux Analysis. Gopalakrishnan, S.; Pakrasi, H. B; and Maranas, C. D In 2017 AIChE Annual Meeting, 2017. AIChE
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Facile affinity maturation of antibody variable domains using natural diversity mutagenesis. Tiller, K. E; Chowdhury, R.; Li, T.; Ludwig, S. D; Sen, S.; Maranas, C. D; and Tessier, P. M Frontiers in immunology, 8: 986. 2017.
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Genome-scale mapping models and algorithms for stationary and instationary MFA-based metabolic flux elucidation. Gopalakrishnan, S.; and Maranas, C. D . 2017.
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Computational modeling of microbial communities. Chan, S. H.; Simons, M.; and Maranas, C. D Systems Biology,163–189. 2017.
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Computational de novo design of antibodies binding to a peptide with high affinity. Poosarla, V. G.; Li, T.; Goh, B. C.; Schulten, K.; Wood, T. K; and Maranas, C. D Biotechnology and bioengineering, 114(6): 1331–1342. 2017.
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Kinetic modeling of metabolism in clostridia. Dash, S.; Khodayari, A.; Stephanopoulos, G.; Lynd, L.; and Maranas, C. In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 253, 2017. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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  2016 (14)
Computational redesign of acyl-ACP thioesterase for medium-chain fatty acid production. Grisewood, M.; Hernandez-Lozada, N.; Pfleger, B.; and Maranas, C. In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 251, 2016. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Metabolic modeling of clostridia: current developments and applications. Dash, S.; Ng, C. Y.; and Maranas, C. D FEMS Microbiology Letters, 363(4). 2016.
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A microbial factory for diverse chemicals. Ng, C. Y.; Chowdhury, A.; and Maranas, C. D Nature biotechnology, 34(5): 513. 2016.
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Reversing methanogenesis to capture methane for liquid biofuel precursors. Soo, V. W.; McAnulty, M. J; Tripathi, A.; Zhu, F.; Zhang, L.; Hatzakis, E.; Smith, P. B; Agrawal, S.; Nazem-Bokaee, H.; Gopalakrishnan, S.; and others Microbial cell factories, 15(1): 11. 2016.
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de novo Design and in silico Optimization of Antibody-Like Binders Targeting Ebola Viral Antigen. Lihan, M.; Goh, B. C.; Li, T.; Maranas, C. D; and Shulten, K. Biophysical Journal, 110(3): 537a. 2016.
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Optimization methods in metabolic networks. Maranas, C. D; and Zomorrodi, A. R John Wiley & Sons, 2016.
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Kinetic modeling of metabolism in obligatory anaerobes. Dash, S; Khodayari, A; Holwerda, E.; Olson, P; Theisen, M; Liao, J.; Stephanopoulos, G; Lynd, L.; and Maranas, C. D In 11th Metabolic Engineering Conference 2016, pages 600–601, 2016. AIChE
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Identifying regulatory changes to facilitate nitrogen fixation in the nondiazotroph Synechocystis sp. PCC 6803. Mueller, T. J; Welsh, E. A; Pakrasi, H. B; and Maranas, C. D ACS synthetic biology, 5(3): 250–258. 2016.
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Assessing methanotrophy and carbon fixation for biofuel production by Methanosarcina acetivorans. Nazem-Bokaee, H.; Gopalakrishnan, S.; Ferry, J. G; Wood, T. K; and Maranas, C. D Microbial cell factories, 15(1): 10. 2016.
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Diurnal regulation of cellular processes in the cyanobacterium Synechocystis sp. strain PCC 6803: Insights from transcriptomic, fluxomic, and physiological analyses. Saha, R.; Liu, D.; Hoynes-O’Connor, A.; Liberton, M.; Yu, J.; Bhattacharyya-Pakrasi, M.; Balassy, A.; Zhang, F.; Moon, T. S.; Maranas, C. D; and others MBio, 7(3): e00464–16. 2016.
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Development and validation of computational methods for de novo design of antibody variable regions. Li, T.; Poosarla, V.; Wood, T.; and Maranas, C. In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 251, 2016. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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A genome-scale Escherichia coli kinetic metabolic model k-ecoli457 satisfying flux data for multiple mutant strains. Khodayari, A.; and Maranas, C. D Nature communications, 7(1): 1–12. 2016.
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A hierarchy of modeling frameworks for cyanobacterial metabolism: From gsms to ME models. Mueller, T; Gopalakrishnan, S; Simons, M; Pakrasi, H.; and Maranas, C. D In 11th Metabolic Engineering Conference 2016, pages 549–550, 2016. AIChE
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Farnesoid X receptor signaling shapes the gut microbiota and controls hepatic lipid metabolism. Zhang, L.; Xie, C.; Nichols, R. G; Chan, S. H.; Jiang, C.; Hao, R.; Smith, P. B; Cai, J.; Simons, M. N; Hatzakis, E.; and others MSystems, 1(5): e00070–16. 2016.
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  2015 (20)
Development of regulated metabolic models for anaerobic organisms. Dash, S.; and Maranas, C. In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 249, 2015. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Achieving metabolic flux analysis for S. cerevisiae at a genome-scale: challenges, requirements, and considerations. Gopalakrishnan, S.; and Maranas, C. D Metabolites, 5(3): 521–535. 2015.
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Succinate overproduction: a case study of computational strain design using a comprehensive Escherichia coli kinetic model. Khodayari, A.; Chowdhury, A.; and Maranas, C. D Frontiers in bioengineering and biotechnology, 2: 76. 2015.
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Methane-to-acetate pathway for producing liquid biofuels and biorenewables. Ferry, J. G.; Maranas, C. D; and Wood, T. K. May~28 2015. US Patent App. 14/550,547
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Advances in de novo strain design using integrated systems and synthetic biology tools. Ng, C. Y.; Khodayari, A.; Chowdhury, A.; and Maranas, C. D Current opinion in chemical biology, 28: 105–114. 2015.
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Transferring nitrogen fixing capabilities to an oxygenic photosynthetic organism. Balassy, A.; Bhattacharyya, M.; Hoynes-O'Connor, A.; Immethun, C.; Liberton, M.; Liu, D.; Mueller, T.; Xiao, Y.; Yu, J.; Moon, T. S.; and others In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 249, 2015. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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13C metabolic flux analysis at a genome-scale. Gopalakrishnan, S.; and Maranas, C. D Metabolic engineering, 32: 12–22. 2015.
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The iterative protein redesign and optimization (IPRO) suite of programs. Pantazes, R. J; Grisewood, M. J; Li, T.; Gifford, N. P; and Maranas, C. D Journal of computational chemistry, 36(4): 251–263. 2015.
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160. Improving computational strain design strategies by incorporation of kinetic information. Khodayari, A.; Chowdhury, A.; and Maranas, C. D In Genomic Science Contractors–Grantees Meeting XIII, pages 228, 2015.
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Rational design of a synthetic Entner–Doudoroff pathway for improved and controllable NADPH regeneration. Ng, C. Y.; Farasat, I.; Maranas, C. D; and Salis, H. M Metabolic engineering, 29: 86–96. 2015.
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Cyanobacterial alkanes modulate photosynthetic cyclic electron flow to assist growth under cold stress. Berla, B. M; Saha, R.; Maranas, C. D; and Pakrasi, H. B Scientific reports, 5(1): 1–12. 2015.
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Bilevel optimization techniques in computational strain design. Chowdhury, A.; Zomorrodi, A. R; and Maranas, C. D Computers & Chemical Engineering, 72: 363–372. 2015.
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Do genome-scale models need exact solvers or clearer standards?. Ebrahim, A.; Almaas, E.; Bauer, E.; Bordbar, A.; Burgard, A. P; Chang, R. L; Dräger, A.; Famili, I.; Feist, A. M; Fleming, R. M.; and others Molecular systems biology, 11(10). 2015.
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Using gene essentiality and synthetic lethality information to correct yeast and CHO cell genome-scale models. Chowdhury, R.; Chowdhury, A.; and Maranas, C. D Metabolites, 5(4): 536–570. 2015.
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Editorial overview: Systems biology advances diseases understanding and metabolic engineering. Fendt, S.; and Maranas, C. D Current opinion in biotechnology, 34: V–VI. 2015.
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Designing overall stoichiometric conversions and intervening metabolic reactions. Chowdhury, A.; and Maranas, C. D Scientific reports, 5: 16009. 2015.
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Methane oxidation by anaerobic archaea for conversion to liquid fuels. Mueller, T. J; Grisewood, M. J; Nazem-Bokaee, H.; Gopalakrishnan, S.; Ferry, J. G; Wood, T. K; and Maranas, C. D Journal of industrial microbiology & biotechnology, 42(3): 391–401. 2015.
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Personalized Kinetic Models for Predictive Healthcare. Chowdhury, A.; and Maranas, C. D Cell systems, 1(4): 250–251. 2015.
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Development of a comprehensive Escherichia coli kinetic metabolic model consistent with multiple genetic and environmental perturbations. Khodayari, A.; and Maranas, C. In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 249, 2015. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Improving prediction fidelity of cellular metabolism with kinetic descriptions. Chowdhury, A.; Khodayari, A.; and Maranas, C. D Current opinion in biotechnology, 36: 57–64. 2015.
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  2014 (13)
Capturing the response of Clostridium acetobutylicumto chemical stressors using a regulated genome-scale metabolic model. Dash, S.; Mueller, T. J; Venkataramanan, K. P; Papoutsakis, E. T; and Maranas, C. D Biotechnology for biofuels, 7(1): 144. 2014.
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OptMAVEn–a new framework for the de novo design of antibody variable region models targeting specific antigen epitopes. Li, T.; Pantazes, R. J; and Maranas, C. D PloS one, 9(8). 2014.
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Systems metabolic engineering design: fatty acid production as an emerging case study. Tee, T. W.; Chowdhury, A.; Maranas, C. D; and Shanks, J. V Biotechnology and bioengineering, 111(5): 849–857. 2014.
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Nitrogen-use efficiency in maize (Zea mays L.): from ‘omics’ studies to metabolic modelling. Simons, M.; Saha, R.; Guillard, L.; Clément, G.; Armengaud, P.; Cañas, R.; Maranas, C. D; Lea, P. J; and Hirel, B. Journal of experimental botany, 65(19): 5657–5671. 2014.
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A kinetic model of Escherichia coli core metabolism satisfying multiple sets of mutant flux data. Khodayari, A.; Zomorrodi, A. R; Liao, J. C; and Maranas, C. D Metabolic engineering, 25: 50–62. 2014.
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CLCA: maximum common molecular substructure queries within the MetRxn database. Kumar, A.; and Maranas, C. D Journal of chemical information and modeling, 54(12): 3417–3438. 2014.
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Coarse-grained optimization-driven design and piecewise linear modeling of synthetic genetic circuits. Zomorrodi, A. R; and Maranas, C. D European Journal of Operational Research, 237(2): 665–676. 2014.
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Recent advances in the reconstruction of metabolic models and integration of omics data. Saha, R.; Chowdhury, A.; and Maranas, C. D Current opinion in biotechnology, 29: 39–45. 2014.
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d-OptCom: dynamic multi-level and multi-objective metabolic modeling of microbial communities. Zomorrodi, A. R; Islam, M. M.; and Maranas, C. D ACS synthetic biology, 3(4): 247–257. 2014.
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Coupled enzyme reactions performed in heterogeneous reaction media: experiments and modeling for glucose oxidase and horseradish peroxidase in a PEG/citrate aqueous two-phase system. Aumiller Jr, W. M; Davis, B. W; Hashemian, N.; Maranas, C.; Armaou, A.; and Keating, C. D The Journal of Physical Chemistry B, 118(9): 2506–2517. 2014.
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Assessing the Metabolic Impact of Nitrogen Availability Using a Compartmentalized Maize Leaf Genome-Scale Model1 [C][W][OPEN]. Simons, M.; Saha, R.; Amiour, N.; Kumar, A.; Guillard, L.; Clément, G.; Miquel, M.; Li, Z.; Mouille, G.; Lea, P. J; and others . 2014.
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k-OptForce: integrating kinetics with flux balance analysis for strain design. Chowdhury, A.; Zomorrodi, A. R; and Maranas, C. D PLoS computational biology, 10(2). 2014.
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De novo antibody design by complementarity determining region modeling. Entzminger, K. C; Pantazes, R. J; Maranas, C. D; and Maynard, J. A In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 247, 2014. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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  2013 (7)
OptZyme: computational enzyme redesign using transition state analogues. Grisewood, M. J; Gifford, N. P; Pantazes, R. J; Li, Y.; Cirino, P. C; Janik, M. J; and Maranas, C. D PloS one, 8(10). 2013.
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Synthetic biology of cyanobacteria: unique challenges and opportunities. Berla, B. M; Saha, R.; Immethun, C. M; Maranas, C. D; Moon, T. S.; and Pakrasi, H. Frontiers in microbiology, 4: 246. 2013.
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MAPs: a database of modular antibody parts for predicting tertiary structures and designing affinity matured antibodies. Pantazes, R. J; and Maranas, C. D BMC bioinformatics, 14(1): 168. 2013.
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Transition state analogue-based computational enzyme design. Grisewood, M; Gifford, N; Janik, M. J.; and Maranas, C. D In Food, Pharmaceutical and Bioengineering Division 2013-Core Programming Area at the 2013 AIChE Annual Meeting: Global Challenges for Engineering a Sustainable Future, pages 127, 2013. AIChE
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Rapid construction of metabolic models for a family of Cyanobacteria using a multiple source annotation workflow. Mueller, T. J; Berla, B. M; Pakrasi, H. B; and Maranas, C. D BMC systems biology, 7(1): 142. 2013.
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Method for determining gene knockouts. Maranas, C. D; Burgard, A. R; and Pharkya, P. June~4 2013. US Patent 8,457,941
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Optimization-driven identification of genetic perturbations accelerates the convergence of model parameters in ensemble modeling of metabolic networks. Zomorrodi, A. R; Lafontaine Rivera, J. G; Liao, J. C; and Maranas, C. D Biotechnology journal, 8(9): 1090–1104. 2013.
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  2012 (14)
Reconstruction and comparison of the metabolic potential of cyanobacteria Cyanothece sp. ATCC 51142 and Synechocystis sp. PCC 6803. Saha, R.; Verseput, A. T; Berla, B. M; Mueller, T. J; Pakrasi, H. B; and Maranas, C. D PloS one, 7(10). 2012.
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OptCom: a multi-level optimization framework for the metabolic modeling and analysis of microbial communities. Zomorrodi, A. R; and Maranas, C. D PLoS computational biology, 8(2). 2012.
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Development of Computational Tools for Metabolic Model Curation, Flux Elucidation and Strain Design. Maranas, C. D Technical Report The Pennsylvania State University, 2012.
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Method for redesign of microbial production systems. Maranas, C. D; Burgard, A. P; and Pharkya, P. January~31 2012. US Patent 8,108,152
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Mathematical optimization applications in metabolic networks. Zomorrodi, A. R; Suthers, P. F; Ranganathan, S.; and Maranas, C. D Metabolic engineering, 14(6): 672–686. 2012.
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MetRxn: a knowledgebase of metabolites and reactions spanning metabolic models and databases. Kumar, A.; Suthers, P. F; and Maranas, C. D BMC bioinformatics, 13(1): 6. 2012.
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Detail View-Data AccessID 67. Ranganathan, S.; Teeb, T. W.; Chowdhuryc, A.; Zomorrodic, A. R; Yoon, J. M.; Fu, Y.; Shanksb, J. V; and Maranas, C. D Metabolic Engineering. 2012.
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Computational tools for metabolic engineering. Copeland, W. B; Bartley, B. A; Chandran, D.; Galdzicki, M.; Kim, K. H; Sleight, S. C; Maranas, C. D; and Sauro, H. M Metabolic engineering, 14(3): 270–280. 2012.
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Computational model of VDJ recombination for antibody design. Pantazes, R. J; and Maranas, C. D In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 243, 2012. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Impact of stoichiometry representation on simulation of genotype-phenotype relationships in metabolic networks. Brochado, A. R.; Andrejev, S.; Maranas, C. D; and Patil, K. R PLoS computational biology, 8(11). 2012.
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Enzymes: Orchestrating hi-fi annotations. Suthers, P. F; and Maranas, C. D Nature chemical biology, 8(10): 810. 2012.
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Using OptForce to customize metabolic interventions for the overproduction of fatty acids C6 through C16 in Escherichia coli. Ranganathan, S.; Wang, T. W.; Welsh, J.; Yoon, J. M.; Shanks, J. V; San, K.; and Maranas, C. D In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 243, 2012. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Contrasting the metabolic capabilities of cyanobacterial species for assessing bio-production platform selection. Saha, R.; Berla, B. M; Mueller, T.; Elvitigala, T.; Page, L. E; Pakrasi, H. B; and Maranas, C. D In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 243, 2012. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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An integrated computational and experimental study for overproducing fatty acids in Escherichia coli. Ranganathan, S.; Tee, T. W.; Chowdhury, A.; Zomorrodi, A. R; Yoon, J. M.; Fu, Y.; Shanks, J. V; and Maranas, C. D Metabolic engineering, 14(6): 687–704. 2012.
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  2011 (11)
Recent advances in computational protein design. Pantazes, R. J; Grisewood, M. J; and Maranas, C. D Current opinion in structural biology, 21(4): 467–472. 2011.
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Modeling the effect of temozolomide treatment on orthotopic models of glioma. Vital-Lopez, F. G; Maranas, C. D; and Armaou, A. In Proceedings of the 2011 American Control Conference, pages 2969–2974, 2011. IEEE
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Genome-scale metabolic network modeling results in minimal interventions that cooperatively force carbon flux towards malonyl-CoA. Xu, P.; Ranganathan, S.; Fowler, Z. L; Maranas, C. D; and Koffas, M. A. Metabolic engineering, 13(5): 578–587. 2011.
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Metabolic reconstruction of the archaeon methanogen Methanosarcina Acetivorans. Kumar, V. S.; Ferry, J. G; and Maranas, C. D BMC systems biology, 5(1): 28. 2011.
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MetRxn&: reaction and metabolite standardization and congruency across databases and genome-scale metabolic models. Kumar, A.; Suthers, P; and Maranas, C. In GTL Conference, pages 1–2, 2011.
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Rational design of recombinant phytochemical microbial producers. Koffas, M.; and Maranas, C. In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 241, 2011. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Zea mays iRS1563: a comprehensive genome-scale metabolic reconstruction of maize metabolism. Saha, R.; Suthers, P. F; and Maranas, C. D PloS one, 6(7). 2011.
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An integrated computational and experimental study to increase the intra-cellular malonyl-CoA: application to flavanone synthesis. Xu, P.; Ranganathan, S.; Maranas, C. D; and Koffas, M. In 2011 IEEE 37th Annual Northeast Bioengineering Conference (NEBEC), pages 1–2, 2011. IEEE
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Method and system for modeling cellular metabolism. Maranas, C. D; and Burgard, A. P December~27 2011. US Patent 8,086,414
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Model simulations reveal VCAM-1 augment PAK activation rates to amplify p38 MAPK and VE-cadherin phosphorylation. Khanna, P.; Weidert, E.; Vital-Lopez, F.; Armaou, A.; Maranas, C. D; and Dong, C. Cellular and Molecular Bioengineering, 4(4): 656–669. 2011.
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Construction of an E. Coli genome-scale atom mapping model for MFA calculations. Ravikirthi, P.; Suthers, P. F; and Maranas, C. D Biotechnology and bioengineering, 108(6): 1372–1382. 2011.
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  2010 (8)
Method for redesign of microbial production systems. Maranas, C. D; Burgard, A. P; and Pharkya, P. November~2 2010. US Patent 7,826,975
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Ensemble cell-wide kinetic modeling of anaerobic organisms to support fuels and chemicals production. Dash, S.; Khodayari, A.; Islam, A.; Zheng, Y.; Lin, P.; Liao, J. C; Stephanopoulos, G.; and Maranas, C. D Proceedings of the National Academy of Sciences of the United States of America, 107(29): 13087–92. 2010.
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Improved computational performance of MFA using elementary metabolite units and flux coupling. Suthers, P. F; Chang, Y. J; and Maranas, C. D Metabolic engineering, 12(2): 123–128. 2010.
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OptForce: an optimization procedure for identifying all genetic manipulations leading to targeted overproductions. Ranganathan, S.; Suthers, P. F; and Maranas, C. D PLoS computational biology, 6(4). 2010.
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Identification of non-native routes and engineering interventions for the microbial production of long-chain alcohols. Ranganathan, S.; Suthers, P. F; and Maranas, C. D In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 239, 2010. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Improving the iMM904 S. cerevisiae metabolic model using essentiality and synthetic lethality data. Zomorrodi, A. R; and Maranas, C. D BMC systems biology, 4(1): 178. 2010.
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Microbial 1-butanol production: Identification of non-native production routes and in silico engineering interventions. Ranganathan, S.; and Maranas, C. D Biotechnology journal, 5(7): 716–725. 2010.
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OptCDR: a general computational method for the design of antibody complementarity determining regions for targeted epitope binding. Pantazes, R.; and Maranas, C. D Protein Engineering, Design & Selection, 23(11): 849–858. 2010.
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  2009 (11)
Modeling Tools for Metabolic Engineering. Maranas, C. D The Metabolic Pathway Engineering Handbook: Fundamentals, 1. 2009.
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BIOT 200-Using computations to reconstruct, analyze, and redesign metabolism. Suthers, P. F; Zomorrodi, A.; Ranganathan, S.; and Maranas, C. D In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 238, 2009. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Genome-scale gene/reaction essentiality and synthetic lethality analysis. Suthers, P. F; Zomorrodi, A.; and Maranas, C. D Molecular systems biology, 5(1). 2009.
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GrowMatch: an automated method for reconciling in silico/in vivo growth predictions. Kumar, V. S.; and Maranas, C. D PLoS computational biology, 5(3). 2009.
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Genome scale reconstruction of a salmonella metabolic model comparison of similarity and differences with a commensal escherichia coli strain. AbuOun, M.; Suthers, P. F; Jones, G. I; Carter, B. R; Saunders, M. P; Maranas, C. D; Woodward, M. J; and Anjum, M. F Journal of Biological Chemistry, 284(43): 29480–29488. 2009.
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OptGraft: A computational procedure for transferring a binding site onto an existing protein scaffold. Fazelinia, H.; Cirino, P. C; and Maranas, C. D Protein Science, 18(1): 180–195. 2009.
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Computational design of Candida boidinii xylose reductase for altered cofactor specificity. Khoury, G. A; Fazelinia, H.; Chin, J. W; Pantazes, R. J; Cirino, P. C; and Maranas, C. D Protein Science, 18(10): 2125–2138. 2009.
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BIOT 94-Computational enzyme redesign for cofactor/substrate specificity. Fazelinia, H.; Khoury, G. A; Cirino, P. C; and Maranas, C. D In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 238, 2009. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Analysis of NADPH supply during xylitol production by engineered Escherichia coli. Chin, J. W; Khankal, R.; Monroe, C. A; Maranas, C. D; and Cirino, P. C Biotechnology and bioengineering, 102(1): 209–220. 2009.
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Using Systems Engineering to Reconstruct, Analyze and Redesign Metabolism. Suthers, P. F; Kumar, V. S.; Zomorrodi, A.; Ranganathan, S.; and Maranas, C. D In Computer Aided Chemical Engineering, volume 27, pages 113–115. Elsevier, 2009.
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Designing the substrate specificity of d-hydantoinase using a rational approach. Lee, S.; Chang, Y.; Shin, D.; Han, J.; Seo, M.; Fazelinia, H.; Maranas, C. D; and Kim, H. Enzyme and Microbial Technology, 44(3): 170–175. 2009.
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  2008 (14)
BIOT 73-Experimental characterization of a de novo designed calcium binding site. Fazelinia, H.; Cinno, P. C; and Maranas, C. D In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 236, 2008. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Using Computations to Reconstruct, Analyze and Redesign Metabolic Systems. Maranas, C. In The 2008 Annual Meeting, 2008.
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Identification of Optimal Measurement Sets for Isotopically Non-Stationary Mfa Experiments. Chang, Y. J.; Suthers, P. F; and Maranas, C. D In 2008 AIChE Annual Meeting, AIChE 100, 2008.
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Complete Flux Elucidation Using Metabolic Flux Analysis. Chang, Y. J.; Suthers, P. F; and Maranas, C. D In 2008 AIChE Annual Meeting, AIChE 100, 2008.
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Modeling the Effect of a Crowding Agent on the Activity of Enzyme-Au Bioconjugates. Vital-Lopez, F. G; Keighron, J.; Keating, C. D.; Maranas, C. D; and Armaou, A. In 2008 AIChE Annual Meeting, AIChE 100, 2008.
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BIOT 293-Genome-scale model of a minimal organism: Mycoplasma genitalium. Suthers, P. F; Dasika, M. S; Kumar, V. S.; and Maranas, C. D In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 236, 2008. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Exhaustive Identification of All Engineering Interventions Leading to Targeted Overproductions. Ranganathan, S.; Suthers, P. F; and Maranas, C. D In The 2008 Annual Meeting, 2008.
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Computational Analysis and Design for Altered Cofactor Specificity. Khoury, G. A; Fazelinia, H. Z; and Maranas, C. D In 2008 AIChE Annual Meeting, AIChE 100, 2008.
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BIOT 12-AraC regulatory protein mutants with altered effector specificity. Tang, S.; Fazelinia, H.; Maranas, C. D; and Cirino, P. C In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 236, 2008. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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OptCircuit: an optimization based method for computational design of genetic circuits. Dasika, M. S; and Maranas, C. D BMC systems biology, 2(1): 24. 2008.
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Implication of dynamics in signal transduction and targeted disruption analyses of signaling networks. Vital-Lopez, F. G; Varshney, A.; Maranas, C. D; and Armaou, A. Computers & Chemical Engineering, 32(9): 2065–2071. 2008.
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Hybrid multi-scale modeling of brain tumor progression. Vital-Lopez, F. G; Maranas, C. D; and Armaou, A. . 2008.
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Computational Analysis of Synthetic Gene/reaction Lethality In E. coli. Zomorrodi, A.; Suthers, P. F; and Maranas, C. D In The 2008 Annual Meeting, 2008.
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Predicting biological system objectives de novo from internal state measurements. Gianchandani, E. P; Oberhardt, M. A; Burgard, A. P; Maranas, C. D; and Papin, J. A BMC bioinformatics, 9(1): 43. 2008.
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  2007 (14)
Metabolic Flux Elucidation For Large-Scale Models: 13 C Labeled Isotope Analysis Of A Strain Of Escherichia coli Producing Amorphadiene. Suthers, P. F; Burgard, A.; Nowroozi, F.; Van Dien, S.; Keasling, J. D; and Maranas, C. D In The 2007 Annual Meeting, 2007.
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BIOT 429-Computational procedure for transferring new binding sites into existing protein scaffolds. Fazelinia, H.; Cirino, P. C; and Maranas, C. D In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 234, 2007. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Computational procedure for transferring binding site into a protein scaffold. Fazelinia, H.; and Maranas, C. D In BIOPHYSICAL JOURNAL, pages 203A–203A, 2007. BIOPHYSICAL SOCIETY 9650 ROCKVILLE PIKE, BETHESDA, MD 20814-3998 USA
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An Integer Programming Approach For The Measurement Set Identifiability Problem In Metabolic Flux Analysis. Chang, Y.; Suthers, P. F; and Maranas, C. D In The 2007 Annual Meeting, 2007.
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An Optimization Based Method To Automatically Reconcile In Silico/in Vivo Growth Predictions. Kumar, V. S; and Maranas, C. D In The 2007 Annual Meeting, 2007.
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BIOT 181-Elucidating and filling gaps in genome-scale metabolic networks. Kumar, V. S.; Dasika, M. S; and Maranas, C. D In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 234, 2007. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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BIOT 343-Designing AraC effector specificity through modeling and dual selection. Cirino, P. C; Tang, S.; Fazelinia, H.; and Maranas, C. D In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 234, 2007. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Extending Iterative Protein Redesign and Optimization (IPRO) in protein library design for ligand specificity. Fazelinia, H.; Cirino, P. C; and Maranas, C. D Biophysical journal, 92(6): 2120–2130. 2007.
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Introducing A Systematic Computational Approach To Graft A Novel Binding Site Into A Protein With A Known Scaffold. Fazelinia, H.; Cirino, P. C; and Maranas, C. D In The 2007 Annual Meeting, 2007.
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BIOT 172-Metabolic flux elucidation for large-scale models: 13C labeled isotope experiments and experimental design. Suthers, P. F; Burgard, A. P; Dasika, M. S; Nowroozi, F.; Van Dien, S.; Keasling, J. D; and Maranas, C. D In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 234, 2007. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Computational Protein Engineering. Maranas, C. 한국생물공학회 학술대회,515–515. 2007.
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Optimal protein library design using recombination or point mutations based on sequence-based scoring functions. Pantazes, R. J; Saraf, M. C; and Maranas, C. D Protein Engineering, Design & Selection, 20(8): 361–373. 2007.
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Large-scale inference and graph-theoretical analysis of gene-regulatory networks in B. Subtilis. Christensen, C.; Gupta, A.; Maranas, C. D; and Albert, R. Physica A: Statistical Mechanics and its Applications, 373: 796–810. 2007.
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Signal Transduction and Targeted Disruption Analyses Using Kinetic Models of Signaling Networks. Vital-Lopez, F. G; Varshney, A.; Maranas, C. D; and Armaou, A. In The 2007 Annual Meeting, 2007.
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  2006 (16)
This un-edited manuscript has been accepted for publication in Biophysical Journal and is freely available on BioFast at http://www. biophysj. org. The final copyedited version of the paper may be found at http://www. biophysj. org. Dasika, M. S; Burgard, A.; and Maranas, C. D . 2006.
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An optimization framework for identifying reaction activation/inhibition or elimination candidates for overproduction in microbial systems. Pharkya, P.; and Maranas, C. D Metabolic engineering, 8(1): 1–13. 2006.
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Metabolic Flux Elucidation for Genome-Scale Models Using 13 C Labeled Isotopes. Suthers, P. F; Burgard, A.; Dasika, M. S; Nowroozi, F.; Van Dien, S.; Keasling, J. D; and Maranas, C. D In The 2006 Annual Meeting, 2006.
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A computational procedure for optimal engineering interventions using kinetic models of metabolism. Vital-Lopez, F. G; Armaou, A.; Nikolaev, E. V; and Maranas, C. D Biotechnology progress, 22(6): 1507–1517. 2006.
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Computation-Guided Design of Arac Regulatory Protein Effector Specificity. Fazelinia, H.; Cirino, P. C; and Maranas, C. D In The 2006 Annual Meeting, 2006.
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Bifurcation analysis of the metabolism of E. coli at optimal enzyme levels. Vital-Lopez, F. G; Maranas, C. D; and Armaou, A. In 2006 American Control Conference, pages 6–pp, 2006. IEEE
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BIOT 93-Computational design of synthetic biological circuits. Dasika, M. S; and Maranas, C. D In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 232, 2006. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Understanding Cofactor Partitioning in Xylitol-Producing Escherichia Coli Expressing Xylose Reductase. Chin, J. W; Maranas, C. D; and Cirino, P. C In The 2006 Annual Meeting, 2006.
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Inference and analysis of gene-regulatory networks in the bacterium B. subtilis. Christensen, C.; Gupta, A.; Albert, R.; and Maranas, C. In APS Meeting Abstracts, 2006.
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Elucidation of directionality for co-expressed genes: predicting intra-operon termination sites. Gupta, A.; Maranas, C. D; and Albert, R. Bioinformatics, 22(2): 209–214. 2006.
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BIOT 50-Computational design and experimental characterization of AraC regulatory protein with novel effector specificity. Fazelinia, H.; Cirino, P. C; and Maranas, C. D In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 232, 2006. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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IPRO: an iterative computational protein library redesign and optimization procedure. Saraf, M. C; Moore, G. L; Goodey, N. M; Cao, V. Y; Benkovic, S. J; and Maranas, C. D Biophysical journal, 90(11): 4167–4180. 2006.
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A computational framework for the topological analysis and targeted disruption of signal transduction networks. Dasika, M. S; Burgard, A.; and Maranas, C. D Biophysical journal, 91(1): 382–398. 2006.
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BIOT 185-Understanding cofactor partitioning in xylitol-producing Escherichia coli expressing xylose reductase. Chin, J. W; Maranas, C. D; and Cirino, P. C In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 232, 2006. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Development of Computational tools for Analyzing and Redesigning Biological Networks. Pharkya, P.; Dasika, M.; Kumar, V. S.; Veeraghavan, N.; Suthers, P.; Burgard, A.; and Maranas, C. D In Proc. of Genomics: GTL Contractor-Grantee Workshop IV, pages 125–126, 2006.
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BIOT 7-Metabolic flux elucidation using 13C labeled isotopes for genome-scale models. Suthers, P. F; Burgard, A. P; Dasika, M. S; Nowroozi, F.; Van Dien, S.; Keasling, J. D; and Maranas, C. D In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 232, 2006. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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  2005 (20)
Large-scale inference of the transcriptional regulation of Bacillus subtilis. Gupta, A.; Varner, J. D; and Maranas, C. D Computers & chemical engineering, 29(3): 565–576. 2005.
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In silico design and adaptive evolution of Escherichia coli for production of lactic acid. Fong, S. S; Burgard, A. P; Herring, C. D; Knight, E. M; Blattner, F. R; Maranas, C. D; and Palsson, B. O Biotechnology and bioengineering, 91(5): 643–648. 2005.
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Hierarchical" top-down" and" bottom-up" framework for regulatory network elucidation and verification. Maranas, C.; Dasika, M.; and Gupta, A In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 229, pages U195–U195, 2005. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Frewen, TA, 713 Friehs, K., 1113 Froment, G., 2265. Gabbar, H.; Gallivan, M.; Gesthuisen, R; Ghaeli, M; Ghosh, S; Gill, R.; Gilles, E.; Glasser, D; Gombert, A.; Gonye, G.; and others Computers and Chemical Engineering, 29: 2494–2496. 2005.
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Metabolic engineering of Escherichia coli through in silico design and experimental evolution. Fong, S. S; Burgard, A.; Maranas, C. D; and Palsson, B. O In 05AIChE: 2005 AIChE Annual Meeting and Fall Showcase, pages 9167, 2005.
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Sensitivity and bifurcation analysis of the metabolism of escherichia coli at optimal enzyme levels. Vital-Lopez, F. G; Maranas, C. D; and Armaou, A. In 05AIChE: 2005 AIChE Annual Meeting and Fall Showcase, pages 7203–7204, 2005.
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A general hybrid optimization framework for the optimal modulation of enzyme levels using large-scale kinetic models of bacterial metabolism. Nikolaev, E.; Pharkya, P.; Armaou, A.; and Maranas, C. D In 05AIChE: 2005 AIChE Annual Meeting and Fall Showcase, pages 8253, 2005.
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Valuation and design of pharmaceutical R&D licensing deals. Rogers, M. J; Maranas, C. D; and Ding, M. AIChE Journal, 51(1): 198–209. 2005.
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Ipro: Iterative Protein Redesign and Optimization Procedure: Application to Three Case-Studies. Saraf, M. C; Brian, A; and Maranas, C. D In The 2005 Annual Meeting, 2005.
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DEMSIM: a discrete event based mechanistic simulation platform for gene expression and regulation dynamics. Dasika, M. S; Gupta, A.; and Maranas, C. D Journal of theoretical biology, 232(1): 55–69. 2005.
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Optimization-based strategies for the systematic analysis and therapeutic disruption of signal transduction networks. Dasika, M. S; Burgard, A. P; and Maranas, C. D In 05AIChE: 2005 AIChE Annual Meeting and Fall Showcase, pages 6775, 2005.
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Systems Engineering Challenges and Opportunities in Biology-Preface. Maranas, C; and Hatzimanikatis, V Computers & Chemical Engineering, 29(3): 405–406. 2005.
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Computers and Chemical Engineering: Preface. Maranas, C. D; and Hatzimanikatis, V Computers and Chemical Engineering, 29(3): 405–406. 2005.
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Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, USA. Gupta, A.; Varner, J. D; and Maranas, C. D Computers and Chemical Engineering, 29(3): 565–576. 2005.
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Design of combinatorial protein libraries of optimal size. Saraf, M. C; Gupta, A.; and Maranas, C. D Proteins: Structure, function, and bioinformatics, 60(4): 769–777. 2005.
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Optimal selection of enzyme levels using large-scale kinetic models. Nikolaev, E. V; Pharkya, P.; Maranas, C. D; and Armaou, A. IFAC Proceedings Volumes, 38(1): 25–30. 2005.
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An optimization framework for elucidating maximization hypotheses in metabolic network flux distribution. Pharkya, P.; Burgard, A. P; and Maranas, C. D In 05AIChE: 2005 AIChE Annual Meeting and Fall Showcase, pages 11781, 2005.
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Elucidation and structural analysis of conserved pools for genome-scale metabolic reconstructions. Nikolaev, E. V; Burgard, A. P; and Maranas, C. D Biophysical journal, 88(1): 37–49. 2005.
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Computational approaches to combinatorial protein library design. Maranas, C.; Saraf, M.; and Moore, G. In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 229, pages U213–U213, 2005. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Computational design of arac protein with novel effector specificity. Fazelinia, H.; Cirino, P. C; and Maranas, C. D In 05AIChE: 2005 AIChE Annual Meeting and Fall Showcase, pages 9270, 2005.
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  2004 (6)
OptStrain: a computational framework for redesign of microbial production systems. Pharkya, P.; Burgard, A. P; and Maranas, C. D Genome research, 14(11): 2367–2376. 2004.
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FamClash: a method for ranking the activity of engineered enzymes. Saraf, M. C; Horswill, A. R; Benkovic, S. J; and Maranas, C. D Proceedings of the National Academy of Sciences, 101(12): 4142–4147. 2004.
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Flux coupling analysis of genome-scale metabolic network reconstructions. Burgard, A. P; Nikolaev, E. V; Schilling, C. H; and Maranas, C. D Genome research, 14(2): 301–312. 2004.
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Molecular design using quantum chemical calculations for property estimation. Lehmann, A.; and Maranas, C. D Industrial & engineering chemistry research, 43(13): 3419–3432. 2004.
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Computational challenges in combinatorial library design for protein engineering. Moore, G. L; and Maranas, C. D AIChE journal, 50(2): 262–272. 2004.
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Real-options-based planning strategies under uncertainty. Gupta, A.; and Maranas, C. D Industrial & engineering chemistry research, 43(14): 3870–3878. 2004.
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  2003 (17)
Optknock: a bilevel programming framework for identifying gene knockout strategies for microbial strain optimization. Burgard, A. P; Pharkya, P.; and Maranas, C. D Biotechnology and bioengineering, 84(6): 647–657. 2003.
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Risk management in real options based pharmaceutical portfolio planning. Rogers, M. J; Gupta, A.; and Maranas, C. D Proceeding Foundations of Computer-Aided Process Operation (FOCAPO),12–15. 2003.
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A mixed integer linear programming (MILP) framework for inferring time delay in gene regulatory networks. Dasika, M. S; Gupta, A.; and Maranas, C. D In Biocomputing 2004, pages 474–485. World Scientific, 2003.
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Identifying residue–residue clashes in protein hybrids by using a second-order mean-field approach. Moore, G. L; and Maranas, C. D Proceedings of the National Academy of Sciences, 100(9): 5091–5096. 2003.
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Systems engineering challenges and opportunities in computational biology. Maranas, C. D; Moore, G. L; Burgard, A. P; and Gupta, A. In Proceedings FOCAPO, pages 13–26, 2003.
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Review of the BRENDA Database. Pharkya, P.; Nikolaev, E. V; and Maranas, C. D Metabolic engineering, 5(2): 71–73. 2003.
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Exploring the overproduction of amino acids using the bilevel optimization framework OptKnock. Pharkya, P.; Burgard, A. P; and Maranas, C. D Biotechnology and bioengineering, 84(7): 887–899. 2003.
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Using a residue clash map to functionally characterize protein recombination hybrids. Saraf, M. C; and Maranas, C. D Protein engineering, 16(12): 1025–1034. 2003.
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Market-based pollution abatement strategies: Risk management using emission option contracts. Gupta, A.; and Maranas, C. D Industrial & engineering chemistry research, 42(4): 802–810. 2003.
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Computational approaches for combinatorial protein library prescreening and optimization. Maranas, C.; Moore, G.; Saraf, M.; and Lee, S In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 226, pages U275–U275, 2003. AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
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Real options based approaches to decision making under uncertainty. Rogers, M. J; Gupta, A.; and Maranas, C. D In Computer Aided Chemical Engineering, volume 15, pages 310–315. Elsevier, 2003.
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METABOL. Pharkya, P.; Nikolaev, E. V; Maranas, C. D; Zhu, T; Phalakornkule, C; Ghosh, S; Grossmann, I.; Koepsel, R.; Ataai, M.; Domach, M.; and others Metabolic Engineering, 5(2). 2003.