Algorithmic And Computational Approaches For Improving The Efficiency Of Mobile Genomic Element Discovery, A Bioinformatics Framework

Author

Fatema Shormin, Prairie View A&M University

Date of Award

12-2023

Document Type

Thesis

Degree Name

Master of Science

Degree Discipline

Computer Science

Abstract

Through this research, we are showcasing the application of computational approaches to the discoveries in the life sciences spectrum. Our current research not only focused on mobile genetic elements but also developed the computational methods that enabled these findings. We combined the biology sciences and computer science in our research, which is essentially multidisciplinary. To that end, this research intricately probed the role and implications of mobile genetic elements, emphasizing transposable elements. These dynamic components wielded substantial influence over genomic architecture's structure, function, and evolutionary adaptations. An integral component of our study is the innovative computational tool, Target/IGE Retriever (TIGER), employed to detect and map these mobile genetic elements. Given the pronounced impact of these elements on gene regulation and their involvement in various genetic diseases, their precise detection and mapping within a genome were crucial for understanding intricate genetic dynamics and disease etiology.

Addressing computational challenges, the study introduces three new algorithms to enhance TIGER's performance, tested using E. coli genomes. This testing aimed to determine the impact of database size reduction on result accuracy and performance. Findings indicate that while prophage yields are less affected by database size, non-phage islands show sensitivity, suggesting performance improvements with smaller databases. Furthermore, the research conducts a comparative analysis of TIGER and BLAST outputs, focusing on validating transposons identified in E. coli genomes. This involves cross-referencing with established databases and employing statistical methods for match categorization, enhancing the authenticity of transposon location identification.. Within the purview of this rigorous analytical process, particular attention is accorded to evaluating sequence alignment results and the quality of BLAST hits, focusing specifically on identifying direct repeats within insertion sequences. The study underscores TIGER's efficacy in transposon discovery and yields critical insights into its performance relative to BLAST. This research illuminates potential avenues for enhancing computational tools in bioinformatics, all within the larger framework of contributing significantly to genomics and bioinformatics research's ongoing advancements. Our work deepens our understanding of the role and influence of mobile genetic elements on genomic architecture.

Index Term: Computational biology, bioinformatics, mobile genetic elements, transposon, validation, database.

Committee Chair/Advisor

Noushin Ghaffari

Committee Member

Lin Li

Committee Member

Ahmed Ahmed

Committee Member

Sherri S. Frizell

Publisher

Prairie View A&M University

Rights

Date of Digitization

12/7/2023

Contributing Institution

John B Coleman Library

City of Publication

Prairie View

MIME Type

Application/PDF

Recommended Citation

Shormin, F. (2023). Algorithmic And Computational Approaches For Improving The Efficiency Of Mobile Genomic Element Discovery, A Bioinformatics Framework. Retrieved from https://digitalcommons.pvamu.edu/pvamu-theses/1525