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You searched for +publisher:"Virginia Tech" +contributor:("Hoops, Stefan"). Showing records 1 – 11 of 11 total matches.

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1. Grover, Shivani. The Role of the Alternaria Secondary Metabolite Alternariol in Inflammation.

Degree: MS, Biological Sciences, 2016, Virginia Tech

 Allergic inflammatory disorders of the airway like asthma and atopic asthma are complex, often long-term diseases that generate large public health and socioeconomic footprints especially… (more)

Subjects/Keywords: Innate Inflammation; Alternaria Alternata; Host-Pathogen Interactions; Alternariol

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APA (6th Edition):

Grover, S. (2016). The Role of the Alternaria Secondary Metabolite Alternariol in Inflammation. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/78310

Chicago Manual of Style (16th Edition):

Grover, Shivani. “The Role of the Alternaria Secondary Metabolite Alternariol in Inflammation.” 2016. Masters Thesis, Virginia Tech. Accessed December 15, 2019. http://hdl.handle.net/10919/78310.

MLA Handbook (7th Edition):

Grover, Shivani. “The Role of the Alternaria Secondary Metabolite Alternariol in Inflammation.” 2016. Web. 15 Dec 2019.

Vancouver:

Grover S. The Role of the Alternaria Secondary Metabolite Alternariol in Inflammation. [Internet] [Masters thesis]. Virginia Tech; 2016. [cited 2019 Dec 15]. Available from: http://hdl.handle.net/10919/78310.

Council of Science Editors:

Grover S. The Role of the Alternaria Secondary Metabolite Alternariol in Inflammation. [Masters Thesis]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/78310


Virginia Tech

2. Wang, Shuo. Analysis and Application of Haseltine and Rawlings's Hybrid Stochastic Simulation Algorithm.

Degree: PhD, Computer Science, 2016, Virginia Tech

 Stochastic effects in cellular systems are usually modeled and simulated with Gillespie's stochastic simulation algorithm (SSA), which follows the same theoretical derivation as the chemical… (more)

Subjects/Keywords: hybrid stochastic simulation algorithm; linear chain reaction system; ordinary differential equation; cell cycle model

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APA (6th Edition):

Wang, S. (2016). Analysis and Application of Haseltine and Rawlings's Hybrid Stochastic Simulation Algorithm. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/82717

Chicago Manual of Style (16th Edition):

Wang, Shuo. “Analysis and Application of Haseltine and Rawlings's Hybrid Stochastic Simulation Algorithm.” 2016. Doctoral Dissertation, Virginia Tech. Accessed December 15, 2019. http://hdl.handle.net/10919/82717.

MLA Handbook (7th Edition):

Wang, Shuo. “Analysis and Application of Haseltine and Rawlings's Hybrid Stochastic Simulation Algorithm.” 2016. Web. 15 Dec 2019.

Vancouver:

Wang S. Analysis and Application of Haseltine and Rawlings's Hybrid Stochastic Simulation Algorithm. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2019 Dec 15]. Available from: http://hdl.handle.net/10919/82717.

Council of Science Editors:

Wang S. Analysis and Application of Haseltine and Rawlings's Hybrid Stochastic Simulation Algorithm. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/82717


Virginia Tech

3. Carbo Barrios, Adria. Transdisciplinary Strategies to Study the Mechanisms of CD4+ T cell Differentiation and Heterogeneity.

Degree: PhD, Animal and Poultry Sciences, 2014, Virginia Tech

 CD4+ T cells mediate and orchestrate a tremendous panoply of lymphoid cell subsets in the human immune system. CD4+ T cells are able to differentiate… (more)

Subjects/Keywords: Immunology; CD4+ T cells; computational modeling

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APA (6th Edition):

Carbo Barrios, A. (2014). Transdisciplinary Strategies to Study the Mechanisms of CD4+ T cell Differentiation and Heterogeneity. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/64833

Chicago Manual of Style (16th Edition):

Carbo Barrios, Adria. “Transdisciplinary Strategies to Study the Mechanisms of CD4+ T cell Differentiation and Heterogeneity.” 2014. Doctoral Dissertation, Virginia Tech. Accessed December 15, 2019. http://hdl.handle.net/10919/64833.

MLA Handbook (7th Edition):

Carbo Barrios, Adria. “Transdisciplinary Strategies to Study the Mechanisms of CD4+ T cell Differentiation and Heterogeneity.” 2014. Web. 15 Dec 2019.

Vancouver:

Carbo Barrios A. Transdisciplinary Strategies to Study the Mechanisms of CD4+ T cell Differentiation and Heterogeneity. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2019 Dec 15]. Available from: http://hdl.handle.net/10919/64833.

Council of Science Editors:

Carbo Barrios A. Transdisciplinary Strategies to Study the Mechanisms of CD4+ T cell Differentiation and Heterogeneity. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/64833


Virginia Tech

4. Murrugarra Tomairo, David M. Algebraic Methods for Modeling Gene Regulatory Networks.

Degree: PhD, Mathematics, 2012, Virginia Tech

 So called discrete models have been successfully used in engineering and computational systems biology. This thesis discusses algebraic methods for modeling and analysis of gene… (more)

Subjects/Keywords: Systems Biology; Stochastic Discrete Modeling; Intrinsic Noise.; Nested Canalyzing Functions; Gene Regulatory Networks; Robustness

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APA (6th Edition):

Murrugarra Tomairo, D. M. (2012). Algebraic Methods for Modeling Gene Regulatory Networks. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/28388

Chicago Manual of Style (16th Edition):

Murrugarra Tomairo, David M. “Algebraic Methods for Modeling Gene Regulatory Networks.” 2012. Doctoral Dissertation, Virginia Tech. Accessed December 15, 2019. http://hdl.handle.net/10919/28388.

MLA Handbook (7th Edition):

Murrugarra Tomairo, David M. “Algebraic Methods for Modeling Gene Regulatory Networks.” 2012. Web. 15 Dec 2019.

Vancouver:

Murrugarra Tomairo DM. Algebraic Methods for Modeling Gene Regulatory Networks. [Internet] [Doctoral dissertation]. Virginia Tech; 2012. [cited 2019 Dec 15]. Available from: http://hdl.handle.net/10919/28388.

Council of Science Editors:

Murrugarra Tomairo DM. Algebraic Methods for Modeling Gene Regulatory Networks. [Doctoral Dissertation]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/28388


Virginia Tech

5. Philipson, Casandra Washington. Systems analysis and characterization of mucosal immunity.

Degree: PhD, Animal and Poultry Sciences, 2015, Virginia Tech

 During acute and chronic infectious diseases hosts develop complex immune responses to cope with bacterial persistence. Depending on a variety of host and microbe factors,… (more)

Subjects/Keywords: Gut inflammation; Enteroaggregative Escherichia coli; Helicobacter pylori; computational modeling; immunology; immunoinformatics

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APA (6th Edition):

Philipson, C. W. (2015). Systems analysis and characterization of mucosal immunity. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/74392

Chicago Manual of Style (16th Edition):

Philipson, Casandra Washington. “Systems analysis and characterization of mucosal immunity.” 2015. Doctoral Dissertation, Virginia Tech. Accessed December 15, 2019. http://hdl.handle.net/10919/74392.

MLA Handbook (7th Edition):

Philipson, Casandra Washington. “Systems analysis and characterization of mucosal immunity.” 2015. Web. 15 Dec 2019.

Vancouver:

Philipson CW. Systems analysis and characterization of mucosal immunity. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2019 Dec 15]. Available from: http://hdl.handle.net/10919/74392.

Council of Science Editors:

Philipson CW. Systems analysis and characterization of mucosal immunity. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/74392


Virginia Tech

6. Arat, Seda. A Systems Biology Approach to Microbiology and Cancer.

Degree: PhD, Mathematics, 2015, Virginia Tech

 Systems biology is an interdisciplinary field that focuses on elucidating complex biological processes (systems) by investigating the interactions among its components through an iterative cycle… (more)

Subjects/Keywords: data analysis; mathematical modeling; microbiome; drug repositioning; polynomial dynamical system

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APA (6th Edition):

Arat, S. (2015). A Systems Biology Approach to Microbiology and Cancer. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/75149

Chicago Manual of Style (16th Edition):

Arat, Seda. “A Systems Biology Approach to Microbiology and Cancer.” 2015. Doctoral Dissertation, Virginia Tech. Accessed December 15, 2019. http://hdl.handle.net/10919/75149.

MLA Handbook (7th Edition):

Arat, Seda. “A Systems Biology Approach to Microbiology and Cancer.” 2015. Web. 15 Dec 2019.

Vancouver:

Arat S. A Systems Biology Approach to Microbiology and Cancer. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2019 Dec 15]. Available from: http://hdl.handle.net/10919/75149.

Council of Science Editors:

Arat S. A Systems Biology Approach to Microbiology and Cancer. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/75149


Virginia Tech

7. Sullivan, Daniel Edward. Evaluation of Word and Paragraph Embeddings and Analogical Reasoning as an  Alternative to Term Frequency-Inverse Document Frequency-based Classification in Support of Biocuration.

Degree: PhD, Animal and Poultry Sciences, 2016, Virginia Tech

 This research addresses the problem, can unsupervised learning generate a representation that improves on the commonly used term frequency-inverse document frequency (TF-IDF ) representation by… (more)

Subjects/Keywords: text mining; machine learning; biocuration; linguistics; natural language processing

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APA (6th Edition):

Sullivan, D. E. (2016). Evaluation of Word and Paragraph Embeddings and Analogical Reasoning as an  Alternative to Term Frequency-Inverse Document Frequency-based Classification in Support of Biocuration. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/80572

Chicago Manual of Style (16th Edition):

Sullivan, Daniel Edward. “Evaluation of Word and Paragraph Embeddings and Analogical Reasoning as an  Alternative to Term Frequency-Inverse Document Frequency-based Classification in Support of Biocuration.” 2016. Doctoral Dissertation, Virginia Tech. Accessed December 15, 2019. http://hdl.handle.net/10919/80572.

MLA Handbook (7th Edition):

Sullivan, Daniel Edward. “Evaluation of Word and Paragraph Embeddings and Analogical Reasoning as an  Alternative to Term Frequency-Inverse Document Frequency-based Classification in Support of Biocuration.” 2016. Web. 15 Dec 2019.

Vancouver:

Sullivan DE. Evaluation of Word and Paragraph Embeddings and Analogical Reasoning as an  Alternative to Term Frequency-Inverse Document Frequency-based Classification in Support of Biocuration. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2019 Dec 15]. Available from: http://hdl.handle.net/10919/80572.

Council of Science Editors:

Sullivan DE. Evaluation of Word and Paragraph Embeddings and Analogical Reasoning as an  Alternative to Term Frequency-Inverse Document Frequency-based Classification in Support of Biocuration. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/80572


Virginia Tech

8. Lee, Shernita. Ironing Out the Host-fungal Interaction in Airway Epithelial Cells.

Degree: PhD, Animal and Poultry Sciences, 2014, Virginia Tech

 Aspergillus fumigatus is a ubiquitous fungus associated with several airway complications and diseases including asthma, allergies, cystic fibrosis, and most commonly invasive aspergillosis. The airway… (more)

Subjects/Keywords: Iron metabolism; immune response; mathematical model; host-fungal interaction; transferrin receptor; divalent metal ion transporter 1

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APA (6th Edition):

Lee, S. (2014). Ironing Out the Host-fungal Interaction in Airway Epithelial Cells. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/56689

Chicago Manual of Style (16th Edition):

Lee, Shernita. “Ironing Out the Host-fungal Interaction in Airway Epithelial Cells.” 2014. Doctoral Dissertation, Virginia Tech. Accessed December 15, 2019. http://hdl.handle.net/10919/56689.

MLA Handbook (7th Edition):

Lee, Shernita. “Ironing Out the Host-fungal Interaction in Airway Epithelial Cells.” 2014. Web. 15 Dec 2019.

Vancouver:

Lee S. Ironing Out the Host-fungal Interaction in Airway Epithelial Cells. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2019 Dec 15]. Available from: http://hdl.handle.net/10919/56689.

Council of Science Editors:

Lee S. Ironing Out the Host-fungal Interaction in Airway Epithelial Cells. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/56689


Virginia Tech

9. Oremland, Matthew Scott. Techniques for mathematical analysis and optimization of agent-based models.

Degree: PhD, Mathematics, 2014, Virginia Tech

 Agent-based models are computer simulations in which entities (agents) interact with each other and their environment according to local update rules. Local interactions give rise… (more)

Subjects/Keywords: Agent-based modeling; optimization; heuristic algorithms

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APA (6th Edition):

Oremland, M. S. (2014). Techniques for mathematical analysis and optimization of agent-based models. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/25138

Chicago Manual of Style (16th Edition):

Oremland, Matthew Scott. “Techniques for mathematical analysis and optimization of agent-based models.” 2014. Doctoral Dissertation, Virginia Tech. Accessed December 15, 2019. http://hdl.handle.net/10919/25138.

MLA Handbook (7th Edition):

Oremland, Matthew Scott. “Techniques for mathematical analysis and optimization of agent-based models.” 2014. Web. 15 Dec 2019.

Vancouver:

Oremland MS. Techniques for mathematical analysis and optimization of agent-based models. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2019 Dec 15]. Available from: http://hdl.handle.net/10919/25138.

Council of Science Editors:

Oremland MS. Techniques for mathematical analysis and optimization of agent-based models. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/25138


Virginia Tech

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

Degree: MS, Computer Science, 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 December 15, 2019. 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. 15 Dec 2019.

Vancouver:

Jones TCJ. JigCell Model Connector: Building Large Molecular Network Models from Components. [Internet] [Masters thesis]. Virginia Tech; 2017. [cited 2019 Dec 15]. 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

11. Lu, Pinyi. Computational modeling-based discovery of novel classes of anti-inflammatory drugs that  target lanthionine synthetase C-like protein 2.

Degree: PhD, Animal and Poultry Sciences, 2015, Virginia Tech

 Lanthionine synthetase C-like protein 2 (LANCL2) is a member of the LANCL protein family, which is broadly expressed throughout the body. LANCL2 is the molecular… (more)

Subjects/Keywords: LANCL2; Anti-inflammatory Drug Discovery; Molecular Modeling; Virtual Screening; In Silico Clinical Trial

…Laboratory, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, USA… …Veterinary Medicine, Virginia Tech, Blacksburg, Virginia, USA. CORRESPONDENCE: *To whom… …Virginia Tech, Blacksburg, VA 24061. Phone: (540) 231-7421, FAX: (540) 231… …Virginia Tech, Blacksburg, VA 24061. Phone: (540) 231-7421, FAX: (540) 231… 

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APA (6th Edition):

Lu, P. (2015). Computational modeling-based discovery of novel classes of anti-inflammatory drugs that  target lanthionine synthetase C-like protein 2. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/64370

Chicago Manual of Style (16th Edition):

Lu, Pinyi. “Computational modeling-based discovery of novel classes of anti-inflammatory drugs that  target lanthionine synthetase C-like protein 2.” 2015. Doctoral Dissertation, Virginia Tech. Accessed December 15, 2019. http://hdl.handle.net/10919/64370.

MLA Handbook (7th Edition):

Lu, Pinyi. “Computational modeling-based discovery of novel classes of anti-inflammatory drugs that  target lanthionine synthetase C-like protein 2.” 2015. Web. 15 Dec 2019.

Vancouver:

Lu P. Computational modeling-based discovery of novel classes of anti-inflammatory drugs that  target lanthionine synthetase C-like protein 2. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2019 Dec 15]. Available from: http://hdl.handle.net/10919/64370.

Council of Science Editors:

Lu P. Computational modeling-based discovery of novel classes of anti-inflammatory drugs that  target lanthionine synthetase C-like protein 2. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/64370

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