Advanced search options

Sorted by: relevance · author · university · date | New search

You searched for `+publisher:"University of Georgia" +contributor:("H. B. Schuttler")`

.
Showing records 1 – 3 of
3 total matches.

▼ Search Limiters

University of Georgia

1. Huang, Yanping. Parameter estimation of chemical reaction networks: the super-ensemble approach.

Degree: MS, Physics, 2007, University of Georgia

URL: http://purl.galileo.usg.edu/uga_etd/huang_yanping_200708_ms

This thesis describes a novel Monte Carlo simulation algorithm for the estimation of
the model parameters of kinetic rate equation systems, describing biochemical reaction networks;
and for the quantitative prediction of the time-dependent behavior of real biochemical
systems described by such kinetics models. This simulation method, referred to as the
super-ensemble approach, combines Monte Carlo sampling of the kinetics model parameter
space with a simultaneous Galerkin-type variational Monte Carlo solution of the underlying
kinetic rate equation system. Unlike the recently proposed and closely related “standard”
ensemble simulation method, the super-ensemble does not rely on the high-volume execution
of a conventional serial ordinary differential equation(ODE) solver algorithm, and it is
therefore amenable to an efficient scalable parallelization by straightforward time domain
decomposition techniques. With minor modifications, the super-ensemble algorithm can also
be deployed as a parallelizable variational ODE solution method, in a conventional ODE
solver setting where a unique ODE solution is sought for given initial conditions and given
rate functions. Test applications of the super-ensemble algorithm in both ODE solver mode
and in parameter estimation mode, for a simple enzyme catalysis model, will be discussed.
*Advisors/Committee Members: H. B. Schuttler.*

Subjects/Keywords: Monte Carlo

Record Details Similar Records

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Huang, Y. (2007). Parameter estimation of chemical reaction networks: the super-ensemble approach. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/huang_yanping_200708_ms

Chicago Manual of Style (16^{th} Edition):

Huang, Yanping. “Parameter estimation of chemical reaction networks: the super-ensemble approach.” 2007. Masters Thesis, University of Georgia. Accessed February 17, 2019. http://purl.galileo.usg.edu/uga_etd/huang_yanping_200708_ms.

MLA Handbook (7^{th} Edition):

Huang, Yanping. “Parameter estimation of chemical reaction networks: the super-ensemble approach.” 2007. Web. 17 Feb 2019.

Vancouver:

Huang Y. Parameter estimation of chemical reaction networks: the super-ensemble approach. [Internet] [Masters thesis]. University of Georgia; 2007. [cited 2019 Feb 17]. Available from: http://purl.galileo.usg.edu/uga_etd/huang_yanping_200708_ms.

Council of Science Editors:

Huang Y. Parameter estimation of chemical reaction networks: the super-ensemble approach. [Masters Thesis]. University of Georgia; 2007. Available from: http://purl.galileo.usg.edu/uga_etd/huang_yanping_200708_ms

University of Georgia

2. Liu, Cejun. Monte Carlo and self-consistent feynman diagram studies of magnetic and correlated electron models.

Degree: PhD, Physics, 2002, University of Georgia

URL: http://purl.galileo.usg.edu/uga_etd/liu_cejun_200212_phd

A Metropolis-Type Dynamics and the Monte Carlo Damage Spreading technique are proposed to study Ising,mixed-spin Ising,and Blume-Capel models on the 2- dimensional square lattice.For the mixed spin Ising model,our results strongly suggest that this spin model may have a tricritical point at .nite temperature;For S =1 and 2 integer spin Blume-Capel models,our results suggest there exists one multi-critical point along the order-disorder transition line.For S =3/2 and 5/2 half- integer spin Blume-Capel models,our results show that this multi-critical behavior does not exist. The Self-Consistent High-Order Feynman Diagram Expansion Technique is intro- duced and then employed to study two correlated electron models:the Hubbard Model (HBM)and the Anderson Impurity Model (AIM)with maximum expansion order n =3.The basic idea of Monte Carlo Summation technique combined with the Self-Consistent Feynman Diagram Expansion,the initial results,and proposed future work on this topic are also presented.
*Advisors/Committee Members: H. B. Schuttler.*

Subjects/Keywords: Monte Carlo

Record Details Similar Records

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Liu, C. (2002). Monte Carlo and self-consistent feynman diagram studies of magnetic and correlated electron models. (Doctoral Dissertation). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/liu_cejun_200212_phd

Chicago Manual of Style (16^{th} Edition):

Liu, Cejun. “Monte Carlo and self-consistent feynman diagram studies of magnetic and correlated electron models.” 2002. Doctoral Dissertation, University of Georgia. Accessed February 17, 2019. http://purl.galileo.usg.edu/uga_etd/liu_cejun_200212_phd.

MLA Handbook (7^{th} Edition):

Liu, Cejun. “Monte Carlo and self-consistent feynman diagram studies of magnetic and correlated electron models.” 2002. Web. 17 Feb 2019.

Vancouver:

Liu C. Monte Carlo and self-consistent feynman diagram studies of magnetic and correlated electron models. [Internet] [Doctoral dissertation]. University of Georgia; 2002. [cited 2019 Feb 17]. Available from: http://purl.galileo.usg.edu/uga_etd/liu_cejun_200212_phd.

Council of Science Editors:

Liu C. Monte Carlo and self-consistent feynman diagram studies of magnetic and correlated electron models. [Doctoral Dissertation]. University of Georgia; 2002. Available from: http://purl.galileo.usg.edu/uga_etd/liu_cejun_200212_phd

University of Georgia

3. Yu, Yihai. Monte Carlo studies of genetic networks with special reference to the biological clock of Neurospora crassa.

Degree: PhD, Physics, 2005, University of Georgia

URL: http://purl.galileo.usg.edu/uga_etd/yu_yihai_200508_phd

to be a very simple and ecient view of a living system. A general purpose kinetic simulator (KINSOLVER) is developed. As a stochastic alternative, an ecient statistical Monte Carlo method is applied to identify an ensemble of deterministic models consistent with RNA and protein proling data for biological clock of Neuropora crassa. Maximally Informative Next Experiment (MINE) is designed and employed to guide new experiments to further improve the quality of the quantitative prediction. A Java Servlet based web site (ENSSOLVER) is developed to visualize and analyze the simulation results.
*Advisors/Committee Members: H. B. Schuttler.*

Subjects/Keywords: Monte Carlo

Record Details Similar Records

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Yu, Y. (2005). Monte Carlo studies of genetic networks with special reference to the biological clock of Neurospora crassa. (Doctoral Dissertation). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/yu_yihai_200508_phd

Chicago Manual of Style (16^{th} Edition):

Yu, Yihai. “Monte Carlo studies of genetic networks with special reference to the biological clock of Neurospora crassa.” 2005. Doctoral Dissertation, University of Georgia. Accessed February 17, 2019. http://purl.galileo.usg.edu/uga_etd/yu_yihai_200508_phd.

MLA Handbook (7^{th} Edition):

Yu, Yihai. “Monte Carlo studies of genetic networks with special reference to the biological clock of Neurospora crassa.” 2005. Web. 17 Feb 2019.

Vancouver:

Yu Y. Monte Carlo studies of genetic networks with special reference to the biological clock of Neurospora crassa. [Internet] [Doctoral dissertation]. University of Georgia; 2005. [cited 2019 Feb 17]. Available from: http://purl.galileo.usg.edu/uga_etd/yu_yihai_200508_phd.

Council of Science Editors:

Yu Y. Monte Carlo studies of genetic networks with special reference to the biological clock of Neurospora crassa. [Doctoral Dissertation]. University of Georgia; 2005. Available from: http://purl.galileo.usg.edu/uga_etd/yu_yihai_200508_phd