Date of Award
Open Access Dissertation
Doctor of Philosophy in Computational Science and Engineering (PhD)
Administrative Home Department
College of Forest Resources and Environmental Science
Committee Member 1
Laura E Brown
Committee Member 2
Committee Member 3
Victor B Busov
In the era of genetics and genomics, the advent of big data is transforming the field of biology into a data-intensive discipline. Novel computational algorithms and software tools are in demand to address the data analysis challenges in this growing field. This dissertation comprises the development of a novel algorithm, web-based data analysis tools, and a data visualization platform. Triple Gene Mutual Interaction (TGMI) algorithm, presented in Chapter 2 is an innovative approach to identify key regulatory transcription factors (TFs) that govern a particular biological pathway or a process through interaction among three genes in a triple gene block, which consists of a pair of pathway genes and a TF. The identification of key TFs controlling a biological pathway or a process allows biologists to understand the complex regulatory mechanisms in living organisms. TF-Miner, presented in Chapter 3, is a high-throughput gene expression data analysis web application that was developed by integrating two highly efficient algorithms; TF-cluster and TF-Finder. TF-Cluster can be used to obtain collaborative TFs that coordinately control a biological pathway or a process using genome-wide expression data. On the other hand, TF-Finder can identify regulatory TFs involved in or associated with a specific biological pathway or a process using Adaptive Sparse Canonical Correlation Analysis (ASCCA). Chapter 4 presents ExactSearch; a suffix tree based motif search algorithm, implemented in a web-based tool. This tool can identify the locations of a set of motif sequences in a set of target promoter sequences. ExactSearch also provides the functionality to search for a set of motif sequences in flanking regions from 50 plant genomes, which we have incorporated into the web tool. Chapter 5 presents STTM JBrowse; a web-based RNA-Seq data visualization system built using the JBrowse open source platform. STTM JBrowse is a unified repository to share/produce visualizations created from large RNA-Seq datasets generated from a variety of model and crop plants in which miRNAs were destroyed using Short Tandem Target Mimic (STTM) Technology.
Gunasekara, Chathura J., "DEVELOPMENT OF BIOINFORMATICS TOOLS AND ALGORITHMS FOR IDENTIFYING PATHWAY REGULATORS, INFERRING GENE REGULATORY RELATIONSHIPS AND VISUALIZING GENE EXPRESSION DATA", Open Access Dissertation, Michigan Technological University, 2017.