Comparative analysis of biological sequences through information visualization

Biology is currently in the beginning of a new high throughput era, more commonly known as The Genomic Era. Genomics has generated unprecedented amounts of biological data, primarily sequence data. However, the generation of the data is fast out-pacing our ability to turn the data into increased biological knowledge. Bioinformatics is the field charged with developing software tools to assist in the management and analysis of this data as biologists strive to use this raw data to better understand the biological processes and functions of organisms.; The field of information visualization is a relatively recent computational field that works to solve the challenges of data presentation and exploration through novel visual representations of data. Information visualization has a wealth of research that is hypothesized to be applicable to the data analysis challenges in genomics. The main objective of this project was to develop and test a software tool implementing a novel information visualization tool for biological sequence analysis. The tool, Biological Arc Diagrams (BARD), was hypothesized to be an effective tool for presenting synteny between multiple sequences, and an effective tool for facilitating discovery of novel genomic features from multiple sequence alignments.; BARD extends the work of Wattenberg [83], who developed the original arc diagram algorithm as a visualization tool for viewing repetitive structures in music. BARD was developed in Java as open source software and is an improvement over existing bioinformatics visualization tools because it is algorithm independent, supports user interactions, and presents all pair-wise comparisons of sequences simultaneously. BARD was evaluated through three case study evaluations and a user evaluation. The study results supported the hypotheses on BARD's effectiveness.; BARD was found to be an effective tool for presenting multiple sequence alignments and supporting user investigation of alignment results for novel features and relationships. The BARD development process illustrated the application of information visualization first principles to the development of a bioinformatics software tool. Finally, potential regions of novel functionality were identified for further testing in a human pathogen.