Myungjae Kwak, Matthew Molina, Spencer Arnold, Andrew Woodward, Jin-Young An, Estelle Nuckels, Yingfeng Wang

Journal of Systemics, Cybernetics and Informatics, 20(5), 138-147 (2022); https://doi.org/10.54808/JSCI.20.05.138

Department of Information Technology, Middle Georgia State University, Macon, Georgia, United StatesDepartment of Information Technology, Middle Georgia State University, Macon, Georgia, United StatesDepartment of Computer Science and Engineering, University of Tennessee at Chattanooga, Chattanooga, Tennessee, United StatesDepartment of Information Technology, Middle Georgia State University, Macon, Georgia, United StatesDepartment of Information Technology, Middle Georgia State University, Macon, Georgia, United StatesDepartment of Natural Sciences, Middle Georgia State University, Macon, Georgia, United StatesDepartment of Computer Science and Engineering, University of Tennessee at Chattanooga, Chattanooga, Tennessee, United States

Cite this paper as:
Kwak, M., Molina, M., Arnold, S., Woodward, A., An, J., Nuckels, E., Wang, Y. (2022). Metabolite Fragmentation Visualization. Journal of Systemics, Cybernetics and Informatics, 20(5), 138-147. https://doi.org/10.54808/JSCI.20.05.138

Tandem mass spectrometry (MS/MS) is a popular technology for identifying small molecules involved in metabolism, better known as metabolites. Coupled with liquid chromatography (LC), LC-MS/MS instruments first separate, ionize, and fragment metabolites, then measure mass-to-charge ratios (m/z) and intensities of metabolite fragments. Understanding metabolite fragmentation is crucial to develop computational tools for identifying metabolites based on this spectroscopic data. Metabolite fragmentation patterns have large variations making it especially difficult for computer scientists to design and implement metabolite identification approaches. To address this interdisciplinary challenge, this article presents FragView, a web-based application providing the web service for visualizing metabolite fragmentation. Users can break chemical bonds to produce metabolite fragments and export 3D fragment structures for 3D printing. Developing FragView is an opportunity for exposing student participants to this interdisciplinary bioinformatics project. This paper summarizes the experience of training student participants in bootcamps and designing the implementation plan based on student backgrounds. Students were exposed to project meeting discussions on coding and raw data visualization and visited a lab with an LC-MS/MS instrument. FragView is an open source, freely accessible tool, released under the GPLv3 license. We will continue to improve and update FragView in the future based on feedback.