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You searched for +publisher:"Georgia Tech" +contributor:("Stephen C. Harvey"). Showing records 1 – 3 of 3 total matches.

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1. Boz, Mustafa Burak. Modeling and simulations of single stranded rna viruses.

Degree: PhD, Chemistry and Biochemistry, 2012, Georgia Tech

The presented work is the application of recent methodologies on modeling and simulation of single stranded RNA viruses. We first present the methods of modeling RNA molecules using the coarse-grained modeling package, YUP. Coarse-grained models simplify complex structures such as viruses and let us study general behavior of the complex biological systems that otherwise cannot be studied with all-atom details. Second, we modeled the first all-atom T=3, icosahedral, single stranded RNA virus, Pariacoto virus (PaV). The x-ray structure of PaV shows only 35% of the total RNA genome and 88% of the capsid. We modeled both missing portions of RNA and protein. The final model of the PaV demonstrated that the positively charged protein N- terminus was located deep inside the RNA. We propose that the positively charged N- terminal tails make contact with the RNA genome and neutralize the negative charges in RNA and subsequently collapse the RNA/protein complex into an icosahedral virus. Third, we simulated T=1 empty capsids using a coarse-grained model of three capsid proteins as a wedge-shaped triangular capsid unit. We varied the edge angle and the potentials of the capsid units to perform empty capsid assembly simulations. The final model and the potential are further improved for the whole virus assembly simulations. Finally, we performed stability and assembly simulations of the whole virus using coarse-grained models. We tested various strengths of RNA-protein tail and capsid protein-capsid protein attractions in our stability simulations and narrowed our search for optimal potentials for assembly. The assembly simulations were carried out with two different protocols: co-transcriptional and post-transcriptional. The co-transcriptional assembly protocol mimics the assembly occurring during the replication of the new RNA. Proteins bind the partly transcribed RNA in this protocol. The post-transcriptional assembly protocol assumes that the RNA is completely transcribed in the absence of proteins. Proteins later bind to the fully transcribed RNA. We found that both protocols can assemble viruses, when the RNA structure is compact enough to yield a successful virus particle. The post-transcriptional protocol depends more on the compactness of the RNA structure compared to the co-transcriptional assembly protocol. Viruses can exploit both assembly protocols based on the location of RNA replication and the compactness of the final structure of the RNA. Advisors/Committee Members: Stephen C. Harvey (Committee Chair), Adegboyega Oyelere (Committee Member), Loren Williams (Committee Member), Rigoberto Hernandez (Committee Member), Roger Wartell (Committee Member).

Subjects/Keywords: Virus assembly; Coarse-grained models; RNA virus; RNA viruses; RNA; Nucleic acids

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APA (6th Edition):

Boz, M. B. (2012). Modeling and simulations of single stranded rna viruses. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/44815

Chicago Manual of Style (16th Edition):

Boz, Mustafa Burak. “Modeling and simulations of single stranded rna viruses.” 2012. Doctoral Dissertation, Georgia Tech. Accessed January 16, 2021. http://hdl.handle.net/1853/44815.

MLA Handbook (7th Edition):

Boz, Mustafa Burak. “Modeling and simulations of single stranded rna viruses.” 2012. Web. 16 Jan 2021.

Vancouver:

Boz MB. Modeling and simulations of single stranded rna viruses. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/1853/44815.

Council of Science Editors:

Boz MB. Modeling and simulations of single stranded rna viruses. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/44815


Georgia Tech

2. Momin, Amin Altaf. Application of bioinformatics in studies of sphingolipid biosynthesis.

Degree: PhD, Biology, 2010, Georgia Tech

The studies in this dissertation demonstrate that the gene expression pathway maps are useful tools to notice alteration in different branches of sphingolipid biosynthesis pathway based on microarray and other transcriptomic analysis. To facilitate the integrative analysis of gene expression and sphingolipid amounts, updated pathway maps were prepared using an open access visualization tool, Pathvisio v1.1. The datasets were formatted using Perl scripts and visualized with the aid of color coded pathway diagrams. Comparative analysis of transcriptomics and sphingolipid alterations from experimental studies and published literature revealed 72.8 % correlation between mRNA and sphingolipid differences (p-value < 0.0001 by the Fisher's exact test).The high correlation between gene expression differences and sphingolipid alterations highlights the application of this tool to evaluate molecular changes associate with sphingolipid alterations as well as predict differences in specific metabolites that can be experimentally verified using sensitive approaches such as mass spectrometry. In addition, bioinformatics sequence analysis was used to identify transcripts for sphingolipid biosynthesis enzyme 3-ketosphinganine reductase, and homology modeling studies helped in the evaluation of a cell line defective in sphingolipid metabolism due to mutation in the enzyme serine palmitoyltransferase, the first enzyme of de novo biosynthesis pathway. Hence, the combination of different bioinformatics approaches, including protein and DNA sequence analysis, structure modeling and pathway diagrams can provide valuable inputs for biochemical and molecular studies of sphingolipid metabolism. Advisors/Committee Members: Alfred H Merrill Jr (Committee Chair), Cameron Sullards (Committee Member), I King Jordan (Committee Member), Marion B. Sewer (Committee Member), Stephen C Harvey (Committee Member).

Subjects/Keywords: Pathway analysis; Pathway maps; Gene expression; Metabolomics; Cancer; Sphingolipids; Metabolism; Mass spectrometry; Biosynthesis; Eukaryotic cells; Prokaryotes; Bioinformatics; Biology Data processing

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

APA (6th Edition):

Momin, A. A. (2010). Application of bioinformatics in studies of sphingolipid biosynthesis. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/34842

Chicago Manual of Style (16th Edition):

Momin, Amin Altaf. “Application of bioinformatics in studies of sphingolipid biosynthesis.” 2010. Doctoral Dissertation, Georgia Tech. Accessed January 16, 2021. http://hdl.handle.net/1853/34842.

MLA Handbook (7th Edition):

Momin, Amin Altaf. “Application of bioinformatics in studies of sphingolipid biosynthesis.” 2010. Web. 16 Jan 2021.

Vancouver:

Momin AA. Application of bioinformatics in studies of sphingolipid biosynthesis. [Internet] [Doctoral dissertation]. Georgia Tech; 2010. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/1853/34842.

Council of Science Editors:

Momin AA. Application of bioinformatics in studies of sphingolipid biosynthesis. [Doctoral Dissertation]. Georgia Tech; 2010. Available from: http://hdl.handle.net/1853/34842


Georgia Tech

3. Sapsaman, Temsiri. An energy landscaping approach to the protein folding problem.

Degree: PhD, Mechanical Engineering, 2009, Georgia Tech

The function of a protein is largely dictated by its natural shape called the "native conformation." Since the native conformation and the global minimum energy configuration highly correlate, predicting this conformation is a global optimization known as the "protein folding problem." It is computationally intensive due to the high-dimensional and complex energy landscape. Typical conformation algorithms combine a probabilistic search with analytical optimization. The analytical portion typically takes longer than the probabilistic part since more function evaluations are required, which are algorithm bottlenecks. To reduce the computational cost, this research studies the effects of exponential energy landscaping (XEL) on three analytical optimization algorithms: Newton's method, a quasi-Newton algorithm (QNA), and the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm. The XEL changes the heights and the depths of the extrema but keeps their location the same, which eliminates the troublesome process of remapping minima onto the original landscape. The Newton-XEL is found to have a similar convergence property as Newton's method by showing that their error residues are of the same order. Found by observation, stability and convergence are improved when the error residue is bounded. While XEL is found to have no effect on the similarity of resulting configurations to the native conformation, results show that the XEL can improve the speed in terms of average iterations in the QNA by 47% and in the BFGS by 41%. In terms of the average score improvement, which indicates how the energy of the resulting configuration is compared to that of the initial configuration, the XEL can improve the quality of resulting configurations in the QNA by 12% and in the BFGS by 10%. Since both results were not achieved simultaneously, the adaptive exponential energy landscaping (AXEL) is developed. The results lead to the conclusion that a trade-off between quality and speed must be considered when XEL is implemented. To improve speed by 15% to 47% and efficiency by 13% to 75%, XEL with n within 2⁻⁹-2⁻⁵ should be used and to improve quality by 4% to 7%, AXEL with Scheme E that keeps the error residue bounded should be used. Advisors/Committee Members: Harvey Lipkin (Committee Chair), Joel S. Sokol (Committee Member), Michael J. Leamy (Committee Member), Nader Sadegh (Committee Member), Stephen C. Harvey (Committee Member).

Subjects/Keywords: Energy landscaping; Protein folding; Optimization; Protein folding; Mathematical optimization; Proteins Conformation

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

APA (6th Edition):

Sapsaman, T. (2009). An energy landscaping approach to the protein folding problem. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/31637

Chicago Manual of Style (16th Edition):

Sapsaman, Temsiri. “An energy landscaping approach to the protein folding problem.” 2009. Doctoral Dissertation, Georgia Tech. Accessed January 16, 2021. http://hdl.handle.net/1853/31637.

MLA Handbook (7th Edition):

Sapsaman, Temsiri. “An energy landscaping approach to the protein folding problem.” 2009. Web. 16 Jan 2021.

Vancouver:

Sapsaman T. An energy landscaping approach to the protein folding problem. [Internet] [Doctoral dissertation]. Georgia Tech; 2009. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/1853/31637.

Council of Science Editors:

Sapsaman T. An energy landscaping approach to the protein folding problem. [Doctoral Dissertation]. Georgia Tech; 2009. Available from: http://hdl.handle.net/1853/31637

.