Bipartition Visualization Using Self Organizing Maps by Neha Nahar a Thesis Submitted in Partial Fulfillment of the Requirements of Master of Science in Computer Science University of Rhode Island

The Tree of Life has provided a framework to study the evolution of organisms. Phylogenetic trees are used to depict the evolution of organisms or of molecules. Comparative genome analyses have shown that genomes are mosaics where different parts have different histories. This discovery calls into question the notion of a unified evolutionary tree for an organism and gives rise to the notion of an evolutionary consensus tree based on the evolutionary patterns of the majority of genes in a genome. The tree topologies that are in conflict with the majority consensus are strong indicators of horizontal gene transfer events. Horizontal gene transfer is the process in which genes from a species are transferred across species border or to different species that are not an offspring. Due to horizontal gene transfer the Tree of Life concept is transforming to a Web of Life where different parts of the genomes can be traced separately from the accepted history of the species. Clustering gene families based on the phylogenetic information they retained, allows extracting a majority consensus for the genomes' evolutionary history, and determination of genes that have a conflicting phylogeny. The purpose of this thesis is to design and implement a framework for an interactive web-based tool that facilitates comparative genome analysis of different species. This tool performs the analysis on a bipartition matrix and generates results as an interactive self-organizing map that allows users to interpret the data and highlight consensus relationships among the organisms. Another important advantage of the tool is an interactive and visual identification of horizontally transferred genes. Additionally, it iii allows researchers to submit their bipartition data online and provides them with the resources and the computation power to perform analyses. iv v ACKNOWLEDGEMENTS I would like to express deepest gratitude towards my advisor, Dr. Lutz Hamel for his unflinching guidance and support. He challenged me and encouraged me to set higher benchmarks and boosted my confidence to solve all the problems. His expertise and experience improved my research skills and prepared me for future work. I would like to thank him for giving me a unique opportunity to work on this interesting and intriguing project. Connecticut, Storrs. They provided me with all the biological knowledge required to complete this dissertation. I am grateful to Maria for always being there to answer all my questions. I am especially thankful to my committee members Dr. Joan Peckham …