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Ohio University

1. Yerardi, Jason T. The Implementation and Evaluation of Bioinformatics Algorithms for the Classification of Arabinogalactan-Proteins in Arabidopsis thaliana.

Degree: MS, Computer Science (Engineering and Technology), 2011, Ohio University

As a result of the dynamic and progressive nature of modern biological research, new data-related problems are continuously being uncovered, resulting in a growing need for bioinformatics-based solutions. One current and active research area in bioinformatics is the classification of proteins into distinct protein families and varying levels of subfamilies. As part of this thesis research, a highly extensible, module-based software platform was developed to provide a centralized graphical user interface for configuring, executing, and analyzing the results of in silico biological analyses for the automation of the protein classification process. This comprehensive bioinformatics software, aptly named "BioOhio," and its related biological analysis algorithms are detailed in this thesis. Since the BioOhio platform and underlying protein analysis algorithms are generally applicable to any plant species, the fully sequenced, widely used model organism Arabidopsis thaliana was chosen as the test data set for the developed bioinformatics software. A significant advantage of this choice was the extensive volume of existing work on this species, including well-defined protein classification criteria for the initial protein classification problems addressed by this thesis. In particular, this thesis initially focused on the development of algorithms for the classification of the hydroxyproline-rich glycoprotein (HRGP) superfamily of plant cell wall proteins into its three basic protein families: (1) arabinogalactan-proteins (AGPs), (2) extensins (EXTs), and (3) proline-rich proteins (PRPs). These basic classification and related protein analysis algorithms provided a firm foundation for the primary focus of this thesis research, which was the development of techniques and algorithms for the further classification of the AGP protein family into distinct subfamilies. At the time of this research, the classification criteria and accepted protein family members for each of the basic HRGP protein families of Arabidopsis thaliana were well established. However, research on the classification of AGPs into proper subfamilies was still in its early stages. As a result, there were only basic generally accepted AGP protein subfamilies and associated characteristics. In particular, the existing work resulted in the general acceptance of the following three primary AGP subfamilies: (1) Classical AGPs, (2) AG-Peptides, and (3) Fasciclin-Like AGPs. However, there was clearly a need for much more thorough research in this particular area, thus making it an excellent prospect for novel biological and bioifnroamtics research in the HRGP research community. In determining the formal criteria to be utilized in the evaluation of the AGP subfamily classification algorithms developed in this thesis research, it was generally agreed upon that the the existing work of Carolyn Schultz et al. was the most complete, accurate, and well known research on AGP subfamilies at the time. As described as part of the thesis results, a… Advisors/Committee Members: Drews, Frank (Committee Chair), Welch, Lonnie R. (Committee Co-Chair), Drews, Frank (Advisor).

Subjects/Keywords: Bioinformatics; Biology; Botany; Computer Science; Molecular Biology; Plant Biology; Plant Sciences; Arabidopsis thaliana; protein classification; hydroxyproline-rich glycoproteins; Arabinogalactan-proteins; HRGPs; AGPs; protein families and subfamilies; plant cell wall proteins; in silico analysis

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APA (6th Edition):

Yerardi, J. T. (2011). The Implementation and Evaluation of Bioinformatics Algorithms for the Classification of Arabinogalactan-Proteins in Arabidopsis thaliana. (Masters Thesis). Ohio University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1301069861

Chicago Manual of Style (16th Edition):

Yerardi, Jason T. “The Implementation and Evaluation of Bioinformatics Algorithms for the Classification of Arabinogalactan-Proteins in Arabidopsis thaliana.” 2011. Masters Thesis, Ohio University. Accessed January 19, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1301069861.

MLA Handbook (7th Edition):

Yerardi, Jason T. “The Implementation and Evaluation of Bioinformatics Algorithms for the Classification of Arabinogalactan-Proteins in Arabidopsis thaliana.” 2011. Web. 19 Jan 2020.

Vancouver:

Yerardi JT. The Implementation and Evaluation of Bioinformatics Algorithms for the Classification of Arabinogalactan-Proteins in Arabidopsis thaliana. [Internet] [Masters thesis]. Ohio University; 2011. [cited 2020 Jan 19]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1301069861.

Council of Science Editors:

Yerardi JT. The Implementation and Evaluation of Bioinformatics Algorithms for the Classification of Arabinogalactan-Proteins in Arabidopsis thaliana. [Masters Thesis]. Ohio University; 2011. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1301069861

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