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You searched for +publisher:"Virginia Tech" +contributor:("Tyson, John J."). Showing records 1 – 30 of 49 total matches.

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Virginia Tech

1. Zhang, Hang. Theoretical and Computational Studies on the Dynamics and Regulation of Cell Phenotypic Transitions.

Degree: PhD, Genetics, Bioinformatics, and Computational Biology, 2016, Virginia Tech

 Cell phenotypic transitions, or cell fate decision making processes, are regulated by complex regulatory networks composed of genes, RNAs, proteins and metabolites. The regulation can… (more)

Subjects/Keywords: Mathematical Modeling; Epigenetics; Cell Differentiation; Mono-allelic expression; Epithelial-to-Mesenchymal-Transition

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APA (6th Edition):

Zhang, H. (2016). Theoretical and Computational Studies on the Dynamics and Regulation of Cell Phenotypic Transitions. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/65159

Chicago Manual of Style (16th Edition):

Zhang, Hang. “Theoretical and Computational Studies on the Dynamics and Regulation of Cell Phenotypic Transitions.” 2016. Doctoral Dissertation, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/65159.

MLA Handbook (7th Edition):

Zhang, Hang. “Theoretical and Computational Studies on the Dynamics and Regulation of Cell Phenotypic Transitions.” 2016. Web. 22 Jan 2021.

Vancouver:

Zhang H. Theoretical and Computational Studies on the Dynamics and Regulation of Cell Phenotypic Transitions. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/65159.

Council of Science Editors:

Zhang H. Theoretical and Computational Studies on the Dynamics and Regulation of Cell Phenotypic Transitions. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/65159


Virginia Tech

2. Subramanian, Kartik. Spatiotemporal Model of the Asymmetric Division Cycle of Caulobacter crescentus.

Degree: PhD, Genetics, Bioinformatics, and Computational Biology, 2014, Virginia Tech

 The life cycle of Caulobacter crescentus is of interest because of the asymmetric nature of cell division that gives rise to progeny that have distinct… (more)

Subjects/Keywords: Mathematical modeling; Caulobacter cell cycle; protein regulatory networks; reaction-diffusion models

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APA (6th Edition):

Subramanian, K. (2014). Spatiotemporal Model of the Asymmetric Division Cycle of Caulobacter crescentus. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/65156

Chicago Manual of Style (16th Edition):

Subramanian, Kartik. “Spatiotemporal Model of the Asymmetric Division Cycle of Caulobacter crescentus.” 2014. Doctoral Dissertation, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/65156.

MLA Handbook (7th Edition):

Subramanian, Kartik. “Spatiotemporal Model of the Asymmetric Division Cycle of Caulobacter crescentus.” 2014. Web. 22 Jan 2021.

Vancouver:

Subramanian K. Spatiotemporal Model of the Asymmetric Division Cycle of Caulobacter crescentus. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/65156.

Council of Science Editors:

Subramanian K. Spatiotemporal Model of the Asymmetric Division Cycle of Caulobacter crescentus. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/65156


Virginia Tech

3. Mobassera, Umme Juka. Extending Regulatory Network Modeling with Multistate Species.

Degree: MS, Computer Science, 2011, Virginia Tech

 By increasing the level of abstraction in the representation of regulatory network models, we can hope to allow modelers to create models that are beyond… (more)

Subjects/Keywords: Modeling Tool; Software; JigCell; Computational Systems Biology; Multistate Species; SBML; Rule Based Modeling

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APA (6th Edition):

Mobassera, U. J. (2011). Extending Regulatory Network Modeling with Multistate Species. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/35594

Chicago Manual of Style (16th Edition):

Mobassera, Umme Juka. “Extending Regulatory Network Modeling with Multistate Species.” 2011. Masters Thesis, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/35594.

MLA Handbook (7th Edition):

Mobassera, Umme Juka. “Extending Regulatory Network Modeling with Multistate Species.” 2011. Web. 22 Jan 2021.

Vancouver:

Mobassera UJ. Extending Regulatory Network Modeling with Multistate Species. [Internet] [Masters thesis]. Virginia Tech; 2011. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/35594.

Council of Science Editors:

Mobassera UJ. Extending Regulatory Network Modeling with Multistate Species. [Masters Thesis]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/35594


Virginia Tech

4. Morris, Matthew. Molecular mechanisms responsible for the dynamic modulation of macrophage responses to varying dosages of lipopolysaccharide.

Degree: PhD, Genetics, Bioinformatics, and Computational Biology, 2014, Virginia Tech

 The innate immune system depends for its effectiveness on the function of specialized pattern recognition receptors which enable it to target pathogens for destruction on… (more)

Subjects/Keywords: Immunology; lipopolysaccharide; signaling; monocyte; macrophage

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APA (6th Edition):

Morris, M. (2014). Molecular mechanisms responsible for the dynamic modulation of macrophage responses to varying dosages of lipopolysaccharide. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/64253

Chicago Manual of Style (16th Edition):

Morris, Matthew. “Molecular mechanisms responsible for the dynamic modulation of macrophage responses to varying dosages of lipopolysaccharide.” 2014. Doctoral Dissertation, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/64253.

MLA Handbook (7th Edition):

Morris, Matthew. “Molecular mechanisms responsible for the dynamic modulation of macrophage responses to varying dosages of lipopolysaccharide.” 2014. Web. 22 Jan 2021.

Vancouver:

Morris M. Molecular mechanisms responsible for the dynamic modulation of macrophage responses to varying dosages of lipopolysaccharide. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/64253.

Council of Science Editors:

Morris M. Molecular mechanisms responsible for the dynamic modulation of macrophage responses to varying dosages of lipopolysaccharide. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/64253


Virginia Tech

5. Fu, Yan. Computational Systems Biology Analysis of Cell Reprogramming and Activation Dynamics.

Degree: PhD, Genetics, Bioinformatics, and Computational Biology, 2012, Virginia Tech

 In the past two decades, molecular cell biology has transitioned from a traditional descriptive science into a quantitative science that systematically measures cellular dynamics on… (more)

Subjects/Keywords: computational modeling; network motifs; LPS priming and tolerance; bacterial phenotypic transition

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APA (6th Edition):

Fu, Y. (2012). Computational Systems Biology Analysis of Cell Reprogramming and Activation Dynamics. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/28414

Chicago Manual of Style (16th Edition):

Fu, Yan. “Computational Systems Biology Analysis of Cell Reprogramming and Activation Dynamics.” 2012. Doctoral Dissertation, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/28414.

MLA Handbook (7th Edition):

Fu, Yan. “Computational Systems Biology Analysis of Cell Reprogramming and Activation Dynamics.” 2012. Web. 22 Jan 2021.

Vancouver:

Fu Y. Computational Systems Biology Analysis of Cell Reprogramming and Activation Dynamics. [Internet] [Doctoral dissertation]. Virginia Tech; 2012. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/28414.

Council of Science Editors:

Fu Y. Computational Systems Biology Analysis of Cell Reprogramming and Activation Dynamics. [Doctoral Dissertation]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/28414


Virginia Tech

6. Poirel, Christopher L. Bridging Methodological Gaps in Network-Based Systems Biology.

Degree: PhD, Computer Science and Applications, 2013, Virginia Tech

 Functioning of the living cell is controlled by a complex network of interactions among genes, proteins, and other molecules. A major goal of systems biology… (more)

Subjects/Keywords: Computational Biology; Functional Enrichment; Graph Theory; Network; Random Walk; Signaling Pathways; Top-Down Analysis

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APA (6th Edition):

Poirel, C. L. (2013). Bridging Methodological Gaps in Network-Based Systems Biology. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/23899

Chicago Manual of Style (16th Edition):

Poirel, Christopher L. “Bridging Methodological Gaps in Network-Based Systems Biology.” 2013. Doctoral Dissertation, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/23899.

MLA Handbook (7th Edition):

Poirel, Christopher L. “Bridging Methodological Gaps in Network-Based Systems Biology.” 2013. Web. 22 Jan 2021.

Vancouver:

Poirel CL. Bridging Methodological Gaps in Network-Based Systems Biology. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/23899.

Council of Science Editors:

Poirel CL. Bridging Methodological Gaps in Network-Based Systems Biology. [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/23899


Virginia Tech

7. Jiang, Liang. Insights on the Regulation of the PERIOD 2 Gene in the Cellular Response to DNA Damage.

Degree: MS, Biological Sciences, 2019, Virginia Tech

 Circadian rhythm is a ~24-h mechanism that keeps our physiology and behavior in synchrony with environmental changes. PERIOD2 (PER2) is a core component of the… (more)

Subjects/Keywords: Circadian rhythm; PER2; DNA damage; p53; radiation; MDM2

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APA (6th Edition):

Jiang, L. (2019). Insights on the Regulation of the PERIOD 2 Gene in the Cellular Response to DNA Damage. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/100865

Chicago Manual of Style (16th Edition):

Jiang, Liang. “Insights on the Regulation of the PERIOD 2 Gene in the Cellular Response to DNA Damage.” 2019. Masters Thesis, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/100865.

MLA Handbook (7th Edition):

Jiang, Liang. “Insights on the Regulation of the PERIOD 2 Gene in the Cellular Response to DNA Damage.” 2019. Web. 22 Jan 2021.

Vancouver:

Jiang L. Insights on the Regulation of the PERIOD 2 Gene in the Cellular Response to DNA Damage. [Internet] [Masters thesis]. Virginia Tech; 2019. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/100865.

Council of Science Editors:

Jiang L. Insights on the Regulation of the PERIOD 2 Gene in the Cellular Response to DNA Damage. [Masters Thesis]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/100865


Virginia Tech

8. Laomettachit, Teeraphan. Mathematical modeling approaches for dynamical analysis of protein regulatory networks with applications to the budding yeast cell cycle and the circadian rhythm in cyanobacteria.

Degree: PhD, Genetics, Bioinformatics, and Computational Biology, 2011, Virginia Tech

 Mathematical modeling has become increasingly popular as a tool to study regulatory interactions within gene-protein networks. From the modelerâ s perspective, two challenges arise in… (more)

Subjects/Keywords: Cyanobacteria; Mathematical Modeling; Protein Regulatory Networks; Budding Yeast Cell Cycle; Circadian Rhythm

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APA (6th Edition):

Laomettachit, T. (2011). Mathematical modeling approaches for dynamical analysis of protein regulatory networks with applications to the budding yeast cell cycle and the circadian rhythm in cyanobacteria. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/29492

Chicago Manual of Style (16th Edition):

Laomettachit, Teeraphan. “Mathematical modeling approaches for dynamical analysis of protein regulatory networks with applications to the budding yeast cell cycle and the circadian rhythm in cyanobacteria.” 2011. Doctoral Dissertation, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/29492.

MLA Handbook (7th Edition):

Laomettachit, Teeraphan. “Mathematical modeling approaches for dynamical analysis of protein regulatory networks with applications to the budding yeast cell cycle and the circadian rhythm in cyanobacteria.” 2011. Web. 22 Jan 2021.

Vancouver:

Laomettachit T. Mathematical modeling approaches for dynamical analysis of protein regulatory networks with applications to the budding yeast cell cycle and the circadian rhythm in cyanobacteria. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/29492.

Council of Science Editors:

Laomettachit T. Mathematical modeling approaches for dynamical analysis of protein regulatory networks with applications to the budding yeast cell cycle and the circadian rhythm in cyanobacteria. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/29492


Virginia Tech

9. Chen, Minghan. Stochastic Modeling and Simulation of Multiscale Biochemical Systems.

Degree: PhD, Computer Science and Applications, 2019, Virginia Tech

 Modeling and simulation of biochemical networks faces numerous challenges as biochemical networks are discovered with increased complexity and unknown mechanisms. With improvement in experimental techniques,… (more)

Subjects/Keywords: Caulobacter cell cycle model; hybrid stochastic simulation algorithm; stochastic parameter optimization

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APA (6th Edition):

Chen, M. (2019). Stochastic Modeling and Simulation of Multiscale Biochemical Systems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/90898

Chicago Manual of Style (16th Edition):

Chen, Minghan. “Stochastic Modeling and Simulation of Multiscale Biochemical Systems.” 2019. Doctoral Dissertation, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/90898.

MLA Handbook (7th Edition):

Chen, Minghan. “Stochastic Modeling and Simulation of Multiscale Biochemical Systems.” 2019. Web. 22 Jan 2021.

Vancouver:

Chen M. Stochastic Modeling and Simulation of Multiscale Biochemical Systems. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/90898.

Council of Science Editors:

Chen M. Stochastic Modeling and Simulation of Multiscale Biochemical Systems. [Doctoral Dissertation]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/90898


Virginia Tech

10. Jalihal, Amogh Prabhav. Mathematical modeling of macronutrient signaling in Saccharomyces cerevisiae.

Degree: PhD, Genetics, Bioinformatics, and Computational Biology, 2020, Virginia Tech

 An important problem in biology is how organisms sense and adapt to ever changing environments. A good example of an environmental cue that affects animal… (more)

Subjects/Keywords: Yeast; Signaling; Mathematical Modeling; Boolean Models; RNAseq

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APA (6th Edition):

Jalihal, A. P. (2020). Mathematical modeling of macronutrient signaling in Saccharomyces cerevisiae. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/99306

Chicago Manual of Style (16th Edition):

Jalihal, Amogh Prabhav. “Mathematical modeling of macronutrient signaling in Saccharomyces cerevisiae.” 2020. Doctoral Dissertation, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/99306.

MLA Handbook (7th Edition):

Jalihal, Amogh Prabhav. “Mathematical modeling of macronutrient signaling in Saccharomyces cerevisiae.” 2020. Web. 22 Jan 2021.

Vancouver:

Jalihal AP. Mathematical modeling of macronutrient signaling in Saccharomyces cerevisiae. [Internet] [Doctoral dissertation]. Virginia Tech; 2020. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/99306.

Council of Science Editors:

Jalihal AP. Mathematical modeling of macronutrient signaling in Saccharomyces cerevisiae. [Doctoral Dissertation]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/99306


Virginia Tech

11. Glaros, Trevor Griffiths. Molecular Mechanisms Governing Persistent Induction of Pro-Inflammatory Genes by Lipopolysaccharide.

Degree: PhD, Biology, 2011, Virginia Tech

 Low dose endotoxemia is caused by several health conditions including smoking, alcohol abuse, high fat diets, and aging. Several studies have correlated low dose endotoxemia… (more)

Subjects/Keywords: Endotoxemia; Inflammation; Interleukin-1 Receptor-Associated Kinase 1; Lipopolysaccharide; Low Dose; Macrophage; Priming

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APA (6th Edition):

Glaros, T. G. (2011). Molecular Mechanisms Governing Persistent Induction of Pro-Inflammatory Genes by Lipopolysaccharide. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/73001

Chicago Manual of Style (16th Edition):

Glaros, Trevor Griffiths. “Molecular Mechanisms Governing Persistent Induction of Pro-Inflammatory Genes by Lipopolysaccharide.” 2011. Doctoral Dissertation, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/73001.

MLA Handbook (7th Edition):

Glaros, Trevor Griffiths. “Molecular Mechanisms Governing Persistent Induction of Pro-Inflammatory Genes by Lipopolysaccharide.” 2011. Web. 22 Jan 2021.

Vancouver:

Glaros TG. Molecular Mechanisms Governing Persistent Induction of Pro-Inflammatory Genes by Lipopolysaccharide. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/73001.

Council of Science Editors:

Glaros TG. Molecular Mechanisms Governing Persistent Induction of Pro-Inflammatory Genes by Lipopolysaccharide. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/73001


Virginia Tech

12. Singhania, Rajat. Modeling Protein Regulatory Networks that Control Mammalian Cell Cycle Progression and that Exhibit Near-Perfect Adaptive Responses.

Degree: PhD, Genetics, Bioinformatics, and Computational Biology, 2011, Virginia Tech

 Protein regulatory networks are the hallmark of many important biological functionalities. Two of these functionalities are mammalian cell cycle progression and near-perfect adaptive responses. Modeling… (more)

Subjects/Keywords: adaptation; motifs; cell cycle regulation; mathematical modeling

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APA (6th Edition):

Singhania, R. (2011). Modeling Protein Regulatory Networks that Control Mammalian Cell Cycle Progression and that Exhibit Near-Perfect Adaptive Responses. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/37722

Chicago Manual of Style (16th Edition):

Singhania, Rajat. “Modeling Protein Regulatory Networks that Control Mammalian Cell Cycle Progression and that Exhibit Near-Perfect Adaptive Responses.” 2011. Doctoral Dissertation, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/37722.

MLA Handbook (7th Edition):

Singhania, Rajat. “Modeling Protein Regulatory Networks that Control Mammalian Cell Cycle Progression and that Exhibit Near-Perfect Adaptive Responses.” 2011. Web. 22 Jan 2021.

Vancouver:

Singhania R. Modeling Protein Regulatory Networks that Control Mammalian Cell Cycle Progression and that Exhibit Near-Perfect Adaptive Responses. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/37722.

Council of Science Editors:

Singhania R. Modeling Protein Regulatory Networks that Control Mammalian Cell Cycle Progression and that Exhibit Near-Perfect Adaptive Responses. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/37722


Virginia Tech

13. Chen, Chun. Systems Biology Study of Breast Cancer Endocrine Response and Resistance.

Degree: PhD, Genetics, Bioinformatics, and Computational Biology, 2013, Virginia Tech

 As a robust system, cells can wisely choose and switch between different signaling programs according to their differentiation stages and external environments. Cancer cells can… (more)

Subjects/Keywords: Mathematical modeling; breast cancer; endocrine resistance; signaling switch; breast cancer landscape

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APA (6th Edition):

Chen, C. (2013). Systems Biology Study of Breast Cancer Endocrine Response and Resistance. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/51965

Chicago Manual of Style (16th Edition):

Chen, Chun. “Systems Biology Study of Breast Cancer Endocrine Response and Resistance.” 2013. Doctoral Dissertation, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/51965.

MLA Handbook (7th Edition):

Chen, Chun. “Systems Biology Study of Breast Cancer Endocrine Response and Resistance.” 2013. Web. 22 Jan 2021.

Vancouver:

Chen C. Systems Biology Study of Breast Cancer Endocrine Response and Resistance. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/51965.

Council of Science Editors:

Chen C. Systems Biology Study of Breast Cancer Endocrine Response and Resistance. [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/51965


Virginia Tech

14. Tavassoly, Iman. Dynamics of Cell Fate Decisions Mediated by the Interplay of Autophagy and Apoptosis in Cancer Cells:  Mathematical Modeling and Experimental Observations    .

Degree: PhD, Genetics, Bioinformatics, and Computational Biology, 2013, Virginia Tech

 Autophagy is a conserved biological stress response in mammalian cells that is responsible for clearing damaged proteins and organelles from the cytoplasm and recycling their… (more)

Subjects/Keywords: Apoptosis; Autophagy; Cancer; Cell Death; Dynamic Modeling; Live Cell Imaging; Quantitative Fluorescence Microscopy; Single-Cell

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APA (6th Edition):

Tavassoly, I. (2013). Dynamics of Cell Fate Decisions Mediated by the Interplay of Autophagy and Apoptosis in Cancer Cells:  Mathematical Modeling and Experimental Observations    . (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/79557

Chicago Manual of Style (16th Edition):

Tavassoly, Iman. “Dynamics of Cell Fate Decisions Mediated by the Interplay of Autophagy and Apoptosis in Cancer Cells:  Mathematical Modeling and Experimental Observations    .” 2013. Doctoral Dissertation, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/79557.

MLA Handbook (7th Edition):

Tavassoly, Iman. “Dynamics of Cell Fate Decisions Mediated by the Interplay of Autophagy and Apoptosis in Cancer Cells:  Mathematical Modeling and Experimental Observations    .” 2013. Web. 22 Jan 2021.

Vancouver:

Tavassoly I. Dynamics of Cell Fate Decisions Mediated by the Interplay of Autophagy and Apoptosis in Cancer Cells:  Mathematical Modeling and Experimental Observations    . [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/79557.

Council of Science Editors:

Tavassoly I. Dynamics of Cell Fate Decisions Mediated by the Interplay of Autophagy and Apoptosis in Cancer Cells:  Mathematical Modeling and Experimental Observations    . [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/79557


Virginia Tech

15. Liu, Jingjing. Identification and Regulatory Role of E3 Ligases in the Time-Dependent Degradation of the Circadian Factor Period 2.

Degree: PhD, Biological Sciences, 2016, Virginia Tech

 Circadian rhythms are self-sustained, 24h, biological oscillatory processes that are present in organisms ranging from bacteria to human. Circadian rhythms, which can be synchronized by… (more)

Subjects/Keywords: Circadian rhythm; Period 2; ubiquitination; Mdm2; Protein stability; p53

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APA (6th Edition):

Liu, J. (2016). Identification and Regulatory Role of E3 Ligases in the Time-Dependent Degradation of the Circadian Factor Period 2. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/81179

Chicago Manual of Style (16th Edition):

Liu, Jingjing. “Identification and Regulatory Role of E3 Ligases in the Time-Dependent Degradation of the Circadian Factor Period 2.” 2016. Doctoral Dissertation, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/81179.

MLA Handbook (7th Edition):

Liu, Jingjing. “Identification and Regulatory Role of E3 Ligases in the Time-Dependent Degradation of the Circadian Factor Period 2.” 2016. Web. 22 Jan 2021.

Vancouver:

Liu J. Identification and Regulatory Role of E3 Ligases in the Time-Dependent Degradation of the Circadian Factor Period 2. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/81179.

Council of Science Editors:

Liu J. Identification and Regulatory Role of E3 Ligases in the Time-Dependent Degradation of the Circadian Factor Period 2. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/81179


Virginia Tech

16. Ahmadian, Mansooreh. Hybrid Modeling and Simulation of Stochastic Effects on Biochemical Regulatory Networks.

Degree: PhD, Computer Science and Applications, 2020, Virginia Tech

 Cell cycle is a process in which a growing cell replicates its DNA and divides into two cells. Progression through the cell cycle is regulated… (more)

Subjects/Keywords: Cell Cycle Modeling; Hybrid Stochastic Modeling; Cell size control; Parameter estimation; Neural network; Theory-guided machine learning

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APA (6th Edition):

Ahmadian, M. (2020). Hybrid Modeling and Simulation of Stochastic Effects on Biochemical Regulatory Networks. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/99481

Chicago Manual of Style (16th Edition):

Ahmadian, Mansooreh. “Hybrid Modeling and Simulation of Stochastic Effects on Biochemical Regulatory Networks.” 2020. Doctoral Dissertation, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/99481.

MLA Handbook (7th Edition):

Ahmadian, Mansooreh. “Hybrid Modeling and Simulation of Stochastic Effects on Biochemical Regulatory Networks.” 2020. Web. 22 Jan 2021.

Vancouver:

Ahmadian M. Hybrid Modeling and Simulation of Stochastic Effects on Biochemical Regulatory Networks. [Internet] [Doctoral dissertation]. Virginia Tech; 2020. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/99481.

Council of Science Editors:

Ahmadian M. Hybrid Modeling and Simulation of Stochastic Effects on Biochemical Regulatory Networks. [Doctoral Dissertation]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/99481


Virginia Tech

17. Lux, Matthew William. Estimation of gene network parameters from imaging cytometry data.

Degree: PhD, Genetics, Bioinformatics, and Computational Biology, 2013, Virginia Tech

 Synthetic biology endeavors to forward engineer genetic circuits with novel function. A major inspiration for the field has been the enormous success in the engineering… (more)

Subjects/Keywords: synthetic biology; computational modeling; parameter estimation; systems biology

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APA (6th Edition):

Lux, M. W. (2013). Estimation of gene network parameters from imaging cytometry data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/23082

Chicago Manual of Style (16th Edition):

Lux, Matthew William. “Estimation of gene network parameters from imaging cytometry data.” 2013. Doctoral Dissertation, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/23082.

MLA Handbook (7th Edition):

Lux, Matthew William. “Estimation of gene network parameters from imaging cytometry data.” 2013. Web. 22 Jan 2021.

Vancouver:

Lux MW. Estimation of gene network parameters from imaging cytometry data. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/23082.

Council of Science Editors:

Lux MW. Estimation of gene network parameters from imaging cytometry data. [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/23082


Virginia Tech

18. Hong, Tian. A framework for understanding heterogeneous differentiation of CD4⁺ T cells.

Degree: PhD, Genetics, Bioinformatics, and Computational Biology, 2013, Virginia Tech

 CD4+ T cells are a group of lymphocytes that play critical roles in the immune system. By releasing cytokines, CD4+ T cells regulate other immune… (more)

Subjects/Keywords: CD4+ T cells; mathematical model; cell differentiation

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APA (6th Edition):

Hong, T. (2013). A framework for understanding heterogeneous differentiation of CD4⁺ T cells. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/51228

Chicago Manual of Style (16th Edition):

Hong, Tian. “A framework for understanding heterogeneous differentiation of CD4⁺ T cells.” 2013. Doctoral Dissertation, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/51228.

MLA Handbook (7th Edition):

Hong, Tian. “A framework for understanding heterogeneous differentiation of CD4⁺ T cells.” 2013. Web. 22 Jan 2021.

Vancouver:

Hong T. A framework for understanding heterogeneous differentiation of CD4⁺ T cells. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/51228.

Council of Science Editors:

Hong T. A framework for understanding heterogeneous differentiation of CD4⁺ T cells. [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/51228


Virginia Tech

19. Adam, Laura. Mapping Genotype to Phenotype using Attribute Grammar.

Degree: PhD, Genetics, Bioinformatics, and Computational Biology, 2013, Virginia Tech

 Over the past 10 years, several synthetic biology research groups have proposed tools and domain-specific languages to help with the design of artificial DNA molecules.… (more)

Subjects/Keywords: Synthetic Biology; Genotype; Phenotype; Formal Language; Attribute Grammar; Compilation; Compiler Generation; Prolog; SBML

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APA (6th Edition):

Adam, L. (2013). Mapping Genotype to Phenotype using Attribute Grammar. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/51768

Chicago Manual of Style (16th Edition):

Adam, Laura. “Mapping Genotype to Phenotype using Attribute Grammar.” 2013. Doctoral Dissertation, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/51768.

MLA Handbook (7th Edition):

Adam, Laura. “Mapping Genotype to Phenotype using Attribute Grammar.” 2013. Web. 22 Jan 2021.

Vancouver:

Adam L. Mapping Genotype to Phenotype using Attribute Grammar. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/51768.

Council of Science Editors:

Adam L. Mapping Genotype to Phenotype using Attribute Grammar. [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/51768


Virginia Tech

20. Ravi, Janani. Mathematical modeling of pathways involved in cell cycle regulation and differentiation.

Degree: PhD, Genetics, Bioinformatics, and Computational Biology, 2011, Virginia Tech

 Cellular processes critical to sustaining physiology, including growth, division and differentiation, are carefully governed by intricate control systems. Deregulations in these systems often result in… (more)

Subjects/Keywords: START transition; Wnt signaling; bistability; cell size control; theoretical biology

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APA (6th Edition):

Ravi, J. (2011). Mathematical modeling of pathways involved in cell cycle regulation and differentiation. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/73006

Chicago Manual of Style (16th Edition):

Ravi, Janani. “Mathematical modeling of pathways involved in cell cycle regulation and differentiation.” 2011. Doctoral Dissertation, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/73006.

MLA Handbook (7th Edition):

Ravi, Janani. “Mathematical modeling of pathways involved in cell cycle regulation and differentiation.” 2011. Web. 22 Jan 2021.

Vancouver:

Ravi J. Mathematical modeling of pathways involved in cell cycle regulation and differentiation. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/73006.

Council of Science Editors:

Ravi J. Mathematical modeling of pathways involved in cell cycle regulation and differentiation. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/73006


Virginia Tech

21. Pratapa, Aditya. Algorithms for regulatory network inference and experiment planning in systems biology.

Degree: PhD, Computer Science and Applications, 2020, Virginia Tech

 A small number of key molecules can completely change the cell's state, for example, a stem cell differentiating into distinct types of blood cells or… (more)

Subjects/Keywords: network biology; experiment planning; gene regulatory networks; deep learning; single cell transcriptomics

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APA (6th Edition):

Pratapa, A. (2020). Algorithms for regulatory network inference and experiment planning in systems biology. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/99378

Chicago Manual of Style (16th Edition):

Pratapa, Aditya. “Algorithms for regulatory network inference and experiment planning in systems biology.” 2020. Doctoral Dissertation, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/99378.

MLA Handbook (7th Edition):

Pratapa, Aditya. “Algorithms for regulatory network inference and experiment planning in systems biology.” 2020. Web. 22 Jan 2021.

Vancouver:

Pratapa A. Algorithms for regulatory network inference and experiment planning in systems biology. [Internet] [Doctoral dissertation]. Virginia Tech; 2020. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/99378.

Council of Science Editors:

Pratapa A. Algorithms for regulatory network inference and experiment planning in systems biology. [Doctoral Dissertation]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/99378

22. Jones, Thomas Carroll Jr. JigCell Model Connector: Building Large Molecular Network Models from Components.

Degree: MS, Computer Science and Applications, 2017, Virginia Tech

 The ever-growing size and complexity of molecular network models makes them difficult to construct and understand. Modifying a model that consists of tens of reactions… (more)

Subjects/Keywords: Computational Systems Biology; Hierarchical Model Composition; SBML; Modeling Tool; Software; JigCell

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APA (6th Edition):

Jones, T. C. J. (2017). JigCell Model Connector: Building Large Molecular Network Models from Components. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/78277

Chicago Manual of Style (16th Edition):

Jones, Thomas Carroll Jr. “JigCell Model Connector: Building Large Molecular Network Models from Components.” 2017. Masters Thesis, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/78277.

MLA Handbook (7th Edition):

Jones, Thomas Carroll Jr. “JigCell Model Connector: Building Large Molecular Network Models from Components.” 2017. Web. 22 Jan 2021.

Vancouver:

Jones TCJ. JigCell Model Connector: Building Large Molecular Network Models from Components. [Internet] [Masters thesis]. Virginia Tech; 2017. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/78277.

Council of Science Editors:

Jones TCJ. JigCell Model Connector: Building Large Molecular Network Models from Components. [Masters Thesis]. Virginia Tech; 2017. Available from: http://hdl.handle.net/10919/78277

23. Li, Fei. Stochastic Modeling and Simulation of Reaction-Diffusion Biochemical Systems.

Degree: PhD, Computer Science and Applications, 2016, Virginia Tech

 Reaction Diffusion Master Equation (RDME) framework, characterized by the discretization of the spatial domain, is one of the most widely used methods in the stochastic… (more)

Subjects/Keywords: stochastic simulation; reaction-diffusion systems; Caulobacter crescentus

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APA (6th Edition):

Li, F. (2016). Stochastic Modeling and Simulation of Reaction-Diffusion Biochemical Systems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/64913

Chicago Manual of Style (16th Edition):

Li, Fei. “Stochastic Modeling and Simulation of Reaction-Diffusion Biochemical Systems.” 2016. Doctoral Dissertation, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/64913.

MLA Handbook (7th Edition):

Li, Fei. “Stochastic Modeling and Simulation of Reaction-Diffusion Biochemical Systems.” 2016. Web. 22 Jan 2021.

Vancouver:

Li F. Stochastic Modeling and Simulation of Reaction-Diffusion Biochemical Systems. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/64913.

Council of Science Editors:

Li F. Stochastic Modeling and Simulation of Reaction-Diffusion Biochemical Systems. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/64913


Virginia Tech

24. Zwolak, Jason Walter. Parameter Estimation in Biological Cell Cycle Models Using Deterministic Optimization.

Degree: MS, Computer Science, 2001, Virginia Tech

 Cell cycle models used in biology can be very complex. These models have parameters with initially unknown values. The values of the parameters vastly aect… (more)

Subjects/Keywords: Cell Cycle Models; Parameter Estima- tion.; Ordinary Di erential Equations

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APA (6th Edition):

Zwolak, J. W. (2001). Parameter Estimation in Biological Cell Cycle Models Using Deterministic Optimization. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/31354

Chicago Manual of Style (16th Edition):

Zwolak, Jason Walter. “Parameter Estimation in Biological Cell Cycle Models Using Deterministic Optimization.” 2001. Masters Thesis, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/31354.

MLA Handbook (7th Edition):

Zwolak, Jason Walter. “Parameter Estimation in Biological Cell Cycle Models Using Deterministic Optimization.” 2001. Web. 22 Jan 2021.

Vancouver:

Zwolak JW. Parameter Estimation in Biological Cell Cycle Models Using Deterministic Optimization. [Internet] [Masters thesis]. Virginia Tech; 2001. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/31354.

Council of Science Editors:

Zwolak JW. Parameter Estimation in Biological Cell Cycle Models Using Deterministic Optimization. [Masters Thesis]. Virginia Tech; 2001. Available from: http://hdl.handle.net/10919/31354


Virginia Tech

25. Dufour, Yann Serge. Experimental Methods in Support of the Development of a Computational Model for Quorum Sensing in Vibrio fischeri.

Degree: MS, Biology, 2004, Virginia Tech

 The quorum sensing signaling system based on intercellular exchange of N-acyl-homoserine lactones is used by many proteobacteria to regulate the transcription of essential genes in… (more)

Subjects/Keywords: microfluidics; quorum sensing; Vibrio fischeri; mathematical modeling; luminescence; gene regulation

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APA (6th Edition):

Dufour, Y. S. (2004). Experimental Methods in Support of the Development of a Computational Model for Quorum Sensing in Vibrio fischeri. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/34290

Chicago Manual of Style (16th Edition):

Dufour, Yann Serge. “Experimental Methods in Support of the Development of a Computational Model for Quorum Sensing in Vibrio fischeri.” 2004. Masters Thesis, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/34290.

MLA Handbook (7th Edition):

Dufour, Yann Serge. “Experimental Methods in Support of the Development of a Computational Model for Quorum Sensing in Vibrio fischeri.” 2004. Web. 22 Jan 2021.

Vancouver:

Dufour YS. Experimental Methods in Support of the Development of a Computational Model for Quorum Sensing in Vibrio fischeri. [Internet] [Masters thesis]. Virginia Tech; 2004. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/34290.

Council of Science Editors:

Dufour YS. Experimental Methods in Support of the Development of a Computational Model for Quorum Sensing in Vibrio fischeri. [Masters Thesis]. Virginia Tech; 2004. Available from: http://hdl.handle.net/10919/34290


Virginia Tech

26. Calzone, Laurence. Mathematical Modeling of the Budding Yeast Cell Cycle.

Degree: MS, Mathematics, 2000, Virginia Tech

 The cell cycle of the budding yeast, Saccharomyces cerevisiae, is regulated by a complex network of chemical reactions controlling the activity of the cyclin-dependent kinases… (more)

Subjects/Keywords: cell cycle; Budding Yeast; CDK

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APA (6th Edition):

Calzone, L. (2000). Mathematical Modeling of the Budding Yeast Cell Cycle. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/31988

Chicago Manual of Style (16th Edition):

Calzone, Laurence. “Mathematical Modeling of the Budding Yeast Cell Cycle.” 2000. Masters Thesis, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/31988.

MLA Handbook (7th Edition):

Calzone, Laurence. “Mathematical Modeling of the Budding Yeast Cell Cycle.” 2000. Web. 22 Jan 2021.

Vancouver:

Calzone L. Mathematical Modeling of the Budding Yeast Cell Cycle. [Internet] [Masters thesis]. Virginia Tech; 2000. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/31988.

Council of Science Editors:

Calzone L. Mathematical Modeling of the Budding Yeast Cell Cycle. [Masters Thesis]. Virginia Tech; 2000. Available from: http://hdl.handle.net/10919/31988


Virginia Tech

27. Petrus, Matthew J. Mechanisms of cell cycle remodeling at the MBT during the development of Xenopus laevis embryos.

Degree: MS, Biology, 2002, Virginia Tech

  During the early development of Xenopus laevis embryos, cells divide without checkpoints. At the midblastula transition (MBT), the cell cycle is remodeled as the… (more)

Subjects/Keywords: cyclin E/Cdk2; XChk1; Xenopus; Xic1; developmental timer; Wee1

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APA (6th Edition):

Petrus, M. J. (2002). Mechanisms of cell cycle remodeling at the MBT during the development of Xenopus laevis embryos. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/32359

Chicago Manual of Style (16th Edition):

Petrus, Matthew J. “Mechanisms of cell cycle remodeling at the MBT during the development of Xenopus laevis embryos.” 2002. Masters Thesis, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/32359.

MLA Handbook (7th Edition):

Petrus, Matthew J. “Mechanisms of cell cycle remodeling at the MBT during the development of Xenopus laevis embryos.” 2002. Web. 22 Jan 2021.

Vancouver:

Petrus MJ. Mechanisms of cell cycle remodeling at the MBT during the development of Xenopus laevis embryos. [Internet] [Masters thesis]. Virginia Tech; 2002. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/32359.

Council of Science Editors:

Petrus MJ. Mechanisms of cell cycle remodeling at the MBT during the development of Xenopus laevis embryos. [Masters Thesis]. Virginia Tech; 2002. Available from: http://hdl.handle.net/10919/32359


Virginia Tech

28. Panning, Thomas D. Deterministic Parallel Global Parameter Estimation for a Model of the Budding Yeast Cell Cycle.

Degree: MS, Computer Science, 2006, Virginia Tech

 Two parallel deterministic direct search algorithms are combined to find improved parameters for a system of differential equations designed to simulate the cell cycle of… (more)

Subjects/Keywords: computational biology; MADS algorithm; direct search; DIRECT algorithm

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APA (6th Edition):

Panning, T. D. (2006). Deterministic Parallel Global Parameter Estimation for a Model of the Budding Yeast Cell Cycle. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/33360

Chicago Manual of Style (16th Edition):

Panning, Thomas D. “Deterministic Parallel Global Parameter Estimation for a Model of the Budding Yeast Cell Cycle.” 2006. Masters Thesis, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/33360.

MLA Handbook (7th Edition):

Panning, Thomas D. “Deterministic Parallel Global Parameter Estimation for a Model of the Budding Yeast Cell Cycle.” 2006. Web. 22 Jan 2021.

Vancouver:

Panning TD. Deterministic Parallel Global Parameter Estimation for a Model of the Budding Yeast Cell Cycle. [Internet] [Masters thesis]. Virginia Tech; 2006. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/33360.

Council of Science Editors:

Panning TD. Deterministic Parallel Global Parameter Estimation for a Model of the Budding Yeast Cell Cycle. [Masters Thesis]. Virginia Tech; 2006. Available from: http://hdl.handle.net/10919/33360


Virginia Tech

29. Hong, Christian I. Mathematical Modeling of Circadian Rhythms in Drosophila melanogaster.

Degree: MS, Biology, 1999, Virginia Tech

 Circadian rhythms are periodic physiological cycles that recur about every 24 hours, by means of which organisms integrate their physiology and behavior to the daily… (more)

Subjects/Keywords: Mathematical biology; Phase response curve; Phase plane; Hopf bifurcation

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APA (6th Edition):

Hong, C. I. (1999). Mathematical Modeling of Circadian Rhythms in Drosophila melanogaster. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/42168

Chicago Manual of Style (16th Edition):

Hong, Christian I. “Mathematical Modeling of Circadian Rhythms in Drosophila melanogaster.” 1999. Masters Thesis, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/42168.

MLA Handbook (7th Edition):

Hong, Christian I. “Mathematical Modeling of Circadian Rhythms in Drosophila melanogaster.” 1999. Web. 22 Jan 2021.

Vancouver:

Hong CI. Mathematical Modeling of Circadian Rhythms in Drosophila melanogaster. [Internet] [Masters thesis]. Virginia Tech; 1999. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/42168.

Council of Science Editors:

Hong CI. Mathematical Modeling of Circadian Rhythms in Drosophila melanogaster. [Masters Thesis]. Virginia Tech; 1999. Available from: http://hdl.handle.net/10919/42168


Virginia Tech

30. Auckland, Ian. Quantitative Analysis of a Cell Cycle Checkpoint in Xenopus laevis Cell-Free Egg Extracts.

Degree: MS, Biology, 2005, Virginia Tech

 In somatic cells, checkpoint pathways trigger cell cycle arrest in response to unreplicated or damaged DNA by inhibiting the activity of cyclin-dependent kinases (Cdks). In… (more)

Subjects/Keywords: cell cycle; Xenopus laevis; nucleocytoplasmic ratio; cyclin-dependent kinases (Cdk)

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APA (6th Edition):

Auckland, I. (2005). Quantitative Analysis of a Cell Cycle Checkpoint in Xenopus laevis Cell-Free Egg Extracts. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/34734

Chicago Manual of Style (16th Edition):

Auckland, Ian. “Quantitative Analysis of a Cell Cycle Checkpoint in Xenopus laevis Cell-Free Egg Extracts.” 2005. Masters Thesis, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/34734.

MLA Handbook (7th Edition):

Auckland, Ian. “Quantitative Analysis of a Cell Cycle Checkpoint in Xenopus laevis Cell-Free Egg Extracts.” 2005. Web. 22 Jan 2021.

Vancouver:

Auckland I. Quantitative Analysis of a Cell Cycle Checkpoint in Xenopus laevis Cell-Free Egg Extracts. [Internet] [Masters thesis]. Virginia Tech; 2005. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/34734.

Council of Science Editors:

Auckland I. Quantitative Analysis of a Cell Cycle Checkpoint in Xenopus laevis Cell-Free Egg Extracts. [Masters Thesis]. Virginia Tech; 2005. Available from: http://hdl.handle.net/10919/34734

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