The Experts below are selected from a list of 3534 Experts worldwide ranked by ideXlab platform
Doraiswami Ramkrishna - One of the best experts on this subject based on the ideXlab platform.
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dynamic Modeling of aerobic growth of shewanella oneidensis predicting triauxic growth flux distributions and energy requirement for growth
Metabolic Engineering, 2013Co-Authors: Hyunseob Song, Doraiswami Ramkrishna, Grigoriy E Pinchuk, Alexander S Beliaev, Allan Konopka, James K FredricksonAbstract:Abstract A Model-based analysis is conducted to investigate metabolism of Shewanella oneidensis MR-1 strain in aerobic batch culture, which exhibits an intriguing growth pattern by sequentially consuming substrate (i.e., lactate) and by-products (i.e., pyruvate and acetate). A general protocol is presented for developing a detailed network-based dynamic Model for S. oneidensis based on the Lumped Hybrid Cybernetic Model (L-HCM) framework. The L-HCM, although developed from only limited data, is shown to accurately reproduce exacting dynamic metabolic shifts, and provide reasonable estimates of energy requirement for growth. Flux distributions in S. oneidensis predicted by the L-HCM compare very favorably with 13 C-metabolic flux analysis results reported in the literature. Predictive accuracy is enhanced by incorporating measurements of only a few intracellular fluxes, in addition to extracellular metabolites. The L-HCM developed here for S. oneidensis is consequently a promising tool for the analysis of intracellular flux distribution and metabolic engineering.
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exacting predictions by Cybernetic Model confirmed experimentally steady state multiplicity in the chemostat
Biotechnology Progress, 2012Co-Authors: Jin Il Kim, Hyunseob Song, Sunil R Sunkara, Arvind M Lali, Doraiswami RamkrishnaAbstract:We demonstrate strong experimental support for the Cybernetic Model based on maximizing carbon uptake rate in describing the microorganism's regulatory behavior by verifying exacting predictions of steady state multiplicity in a chemostat. Experiments with a feed mixture of glucose and pyruvate show multiple steady state behavior as predicted by the Cybernetic Model. When multiplicity occurs at a dilution (growth) rate, it results in hysteretic behavior following switches in dilution rate from above and below. This phenomenon is caused by transient paths leading to different steady states through dynamic maximization of the carbon uptake rate. Thus steady state multiplicity is a manifestation of the nonlinearity arising from Cybernetic mechanisms rather than of the nonlinear kinetics. The predicted metabolic multiplicity would extend to intracellular states such as enzyme levels and fluxes to be verified in future experiments. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 2012
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prediction of dynamic metabolic behavior of pediococcus pentosaceus producing lactic acid from lignocellulosic sugars
Biotechnology Progress, 2012Co-Authors: Philipp Adler, Hyunseob Song, Katharina Kastner, Doraiswami Ramkrishna, Benno KunzAbstract:A dynamic metabolic Model is presented for Pediococcus pentosaceus producing lactic acid from lignocellulose-derived mixed sugars including glucose, mannose, galactose, arabinose, and xylose. Depending on the pairs of mixed sugars, P. pentosaceus exhibits diverse (i.e., sequential, simultaneous or mixed) consumption patterns. This regulatory behavior of P. pentosaceus is portrayed using the hybrid Cybernetic Model (HCM) framework which views elementary modes of the network as metabolic options dynamically modulated. Comprehensive data are collected for Model identification and validation through fermentation experiments involving single substrates and various combinations of mixed sugars. Most sugars are metabolized rather sequentially while co-consumption of galactose and arabinose is observed. It is demonstrated that the developed HCM successfully predicts mixed sugar data based on the parameters identified mostly from single substrate data only. Further, we discuss the potential of HCMs as a tool for predicting intracellular flux distribution with comparison with flux balance analysis. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 2012
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hybrid Cybernetic Model based simulation of continuous production of lignocellulosic ethanol rejecting abruptly changing feed conditions
International Symposium on Advanced Control of Industrial Processes, 2010Co-Authors: Wee Chin Wong, Hyunseob Song, Jay H Lee, Doraiswami RamkrishnaAbstract:Fermenting various sugars derived from lignocellulosic biomass promises to be attractive for producing ethanol, an important alternative fuel. Diversity of lignocellulosic biomass sources and pre-processing variations mean entering sugars are expected to experience large, though infrequent, changes. Recent developments in hybrid Cybernetic Modeling allow efficient in silico studies. This enables studying sequential linearization-based Model predictive control for ensuring high productivity and conversion, for a chemostat seeded with yeast capable of co-fermentation. An appropriate controlled variable (conversion) and control formulation are ascertained. Also, a recently proposed hidden-Markov disturbance Model, capable of describing the aforesaid changes, results in closed-loop performance superior to the typical integrated white-noise assumption.
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dynamic analysis of the Cybernetic Model for diauxic growth
Chemical Engineering Science, 1997Co-Authors: Atul Narang, Allan Konopka, Doraiswami RamkrishnaAbstract:Abstract The Cybernetic framework is a mathematical formalism developed by Ramkrishna and coworkers for Modelling microbial systems. In this work, we analyze the dynamics of the Cybernetic Model for diauxic growth (Kompala et al. , 1986, Biotechnol. Bioengng . 28 1044–1055). Recent data shows, however, that microbial growth on binary mixtures is frequently nondiauxic. The goal of this work is to: 1. (1) Understand why the Model captures the diauxie. 2. (2) Determine if the Model can embrace the nondiauxic growth patterns. The analysis shows that the global dynamics of the Cybernetic Model agree with diauxic behavior, and the autocatalytic nature of enzyme synthesis plays a key role in ensuring this agreement. But there exists no set of parameter values for which the Model embraces the nondiauxic growth patterns; this observation is specific to the Model of Kompala et al. (1986) and does not apply to the more recent Cybernetic Model of Ramakrishna et al. (1997, Biotechnol. Bioengng 52 , 141–151).
Michele K Kacma - One of the best experts on this subject based on the ideXlab platform.
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a Cybernetic Model of impression management processes in organizations
Organizational Behavior and Human Decision Processes, 1997Co-Authors: Dennis P Ozema, Michele K KacmaAbstract:Recent theory and research have suggested that a significant portion of human behavior in organizations is motivated by impression management concerns, that is, by the desire to be perceived by others in certain ways. However, the complex interpersonal dynamics of impression management in organizations remain largely unexplored. This paper synthesizes theory and research across several disciplines and literatures to present an integrative, process-oriented Model of impression management in organizations. Potential applications and implications of the Model for management research and practice are discussed and directions for future research are provided.
Hyunseob Song - One of the best experts on this subject based on the ideXlab platform.
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dynamic Modeling of aerobic growth of shewanella oneidensis predicting triauxic growth flux distributions and energy requirement for growth
Metabolic Engineering, 2013Co-Authors: Hyunseob Song, Doraiswami Ramkrishna, Grigoriy E Pinchuk, Alexander S Beliaev, Allan Konopka, James K FredricksonAbstract:Abstract A Model-based analysis is conducted to investigate metabolism of Shewanella oneidensis MR-1 strain in aerobic batch culture, which exhibits an intriguing growth pattern by sequentially consuming substrate (i.e., lactate) and by-products (i.e., pyruvate and acetate). A general protocol is presented for developing a detailed network-based dynamic Model for S. oneidensis based on the Lumped Hybrid Cybernetic Model (L-HCM) framework. The L-HCM, although developed from only limited data, is shown to accurately reproduce exacting dynamic metabolic shifts, and provide reasonable estimates of energy requirement for growth. Flux distributions in S. oneidensis predicted by the L-HCM compare very favorably with 13 C-metabolic flux analysis results reported in the literature. Predictive accuracy is enhanced by incorporating measurements of only a few intracellular fluxes, in addition to extracellular metabolites. The L-HCM developed here for S. oneidensis is consequently a promising tool for the analysis of intracellular flux distribution and metabolic engineering.
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exacting predictions by Cybernetic Model confirmed experimentally steady state multiplicity in the chemostat
Biotechnology Progress, 2012Co-Authors: Jin Il Kim, Hyunseob Song, Sunil R Sunkara, Arvind M Lali, Doraiswami RamkrishnaAbstract:We demonstrate strong experimental support for the Cybernetic Model based on maximizing carbon uptake rate in describing the microorganism's regulatory behavior by verifying exacting predictions of steady state multiplicity in a chemostat. Experiments with a feed mixture of glucose and pyruvate show multiple steady state behavior as predicted by the Cybernetic Model. When multiplicity occurs at a dilution (growth) rate, it results in hysteretic behavior following switches in dilution rate from above and below. This phenomenon is caused by transient paths leading to different steady states through dynamic maximization of the carbon uptake rate. Thus steady state multiplicity is a manifestation of the nonlinearity arising from Cybernetic mechanisms rather than of the nonlinear kinetics. The predicted metabolic multiplicity would extend to intracellular states such as enzyme levels and fluxes to be verified in future experiments. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 2012
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prediction of dynamic metabolic behavior of pediococcus pentosaceus producing lactic acid from lignocellulosic sugars
Biotechnology Progress, 2012Co-Authors: Philipp Adler, Hyunseob Song, Katharina Kastner, Doraiswami Ramkrishna, Benno KunzAbstract:A dynamic metabolic Model is presented for Pediococcus pentosaceus producing lactic acid from lignocellulose-derived mixed sugars including glucose, mannose, galactose, arabinose, and xylose. Depending on the pairs of mixed sugars, P. pentosaceus exhibits diverse (i.e., sequential, simultaneous or mixed) consumption patterns. This regulatory behavior of P. pentosaceus is portrayed using the hybrid Cybernetic Model (HCM) framework which views elementary modes of the network as metabolic options dynamically modulated. Comprehensive data are collected for Model identification and validation through fermentation experiments involving single substrates and various combinations of mixed sugars. Most sugars are metabolized rather sequentially while co-consumption of galactose and arabinose is observed. It is demonstrated that the developed HCM successfully predicts mixed sugar data based on the parameters identified mostly from single substrate data only. Further, we discuss the potential of HCMs as a tool for predicting intracellular flux distribution with comparison with flux balance analysis. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 2012
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hybrid Cybernetic Model based simulation of continuous production of lignocellulosic ethanol rejecting abruptly changing feed conditions
International Symposium on Advanced Control of Industrial Processes, 2010Co-Authors: Wee Chin Wong, Hyunseob Song, Jay H Lee, Doraiswami RamkrishnaAbstract:Fermenting various sugars derived from lignocellulosic biomass promises to be attractive for producing ethanol, an important alternative fuel. Diversity of lignocellulosic biomass sources and pre-processing variations mean entering sugars are expected to experience large, though infrequent, changes. Recent developments in hybrid Cybernetic Modeling allow efficient in silico studies. This enables studying sequential linearization-based Model predictive control for ensuring high productivity and conversion, for a chemostat seeded with yeast capable of co-fermentation. An appropriate controlled variable (conversion) and control formulation are ascertained. Also, a recently proposed hidden-Markov disturbance Model, capable of describing the aforesaid changes, results in closed-loop performance superior to the typical integrated white-noise assumption.
Jingqi Yuan - One of the best experts on this subject based on the ideXlab platform.
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application of hybrid Cybernetic Model in simulating myeloma cell culture co consuming glucose and glutamine with mixed consumption patterns
Process Biochemistry, 2013Co-Authors: Jun Geng, Jingxiu Bi, Anping Zeng, Jingqi YuanAbstract:A dynamic Model called hybrid Cybernetic Model (HCM) based on structured metabolic network is established for simulating mammalian cell metabolism featured with partially substitutable and partially complementary consumption patterns of two substrates, glucose and glutamine. Benefiting from the application of elementary mode analysis (EMA), the complicated metabolic network is decomposed into elementary modes (EMs) facilitating the employment of the hybrid Cybernetic framework to investigate the external and internal flux distribution and the regulation mechanism among them. According to different substrate combination, two groups of EMs are obtained, i.e., EMs associated with glucose uptake and simultaneous uptake of glucose and glutamine. Uptake fluxes through various EMs are coupled together via Cybernetic variables to maximize substrate uptake. External fluxes and internal fluxes could be calculated and estimated respectively, by the combination of the stoichiometrics of metabolic networks and fluxes through regulated EMs. The Model performance is well validated via three sets of experimental data. Through parameter identification of limited number of experimental data, other external metabolites are precisely predicted. The obtained kinetic parameters of three experimental cultures have similar values, which indicates the robustness of the Model. Furthermore, the prediction performance of the Model is successfully validated based on identified parameters.
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a Cybernetic Model to describe the dynamics of myeloma cell cultivations
Applied Mathematics and Computation, 2008Co-Authors: Yuanhua Liu, Anping Zeng, Jingqi YuanAbstract:A Cybernetic Model is developed to Model the dynamics of mammalian cell growth and metabolism. Especially, the formation of the byproducts such as ammonia and alanine are taken into account in the Model. The production of these byproducts is mainly regulated by the competition between transamination and deamination. In addition, amino acids utilization for protein formation and energy supply is also involved due to lysine limitation found in our experiments. The Model is able to simulate the transients of the substrate and byproduct concentrations, the viable and dead biomass as well as the intracellular concentrations of the intermediates and enzymes. Myeloma cell cultivations are applied to validate the Model.
Monica Gil - One of the best experts on this subject based on the ideXlab platform.
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social physiological compliance as a determinant of team performance
International Journal of Psychophysiology, 2001Co-Authors: Robert Henning, Wolfram Boucsein, Monica GilAbstract:Abstract A Cybernetic Model of behavior predicts that team performance may depend on physiological compliance among participants. This laboratory study tested if compliance in electrodermal activity (EDA), heart rate or breathing in two-person teams ( N =16) was predictive of team performance or coordination in a continuous tracking task simulating teleoperation. Visual contact among participants was manipulated. Physiological compliance was scored with weighted coherence and cross correlation. Separate multiple regression analyses revealed that the task completion time was predicted by coherence measures for EDA and heart, but only at a trend level for breathing. Task completion time was also predicted by heart cross correlation. Team tracking error was predicted by coherence measures for EDA, heart and breathing, and also heart cross correlation. While social–visual contact did not have an impact, physiological compliance was predictive of improved performance, with coherence robust over all three physiological measures. Heart cross correlation showed the strongest predictive relationships. These results provide evidence that physiological compliance among team members may benefit team performance. While further study is needed, physiological compliance may someday provide a needed tool for the study of team work, and an objective means to guide the ergonomic design of complex sociotechnical systems requiring a high degree of team proficiency.
