CAREER: RUI: NetDA -- Protein Network-Based Software for Disease Analysis Using Cliques, Bipartite Graphs, and Diffusion Kernels

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This project will investigate and analyze the complex phenomena of disease progression at the protein network level. A software tool, NetDA (Network-based Disease Analysis) to understand the essential mechanisms of disease progression as transitions between disease stages will be developed. The outcome of this study will help not only in early diagnosis of a disease but also in drug design specific for a disease stage. Undergraduate students will be involved in the research.The process of disease progression will be analyzed as an event-schedule-like structure, where a) each event representing a disease stage completed by a group of proteins will be analyzed in terms of clique and clique-like graphs, b) transfer of signals from one stage to the next will be analyzed using bipartite and bipartite-like graphs, and c) the strength of signals will be analyzed using diffusion kernels. The outcome of this study will help not only in early diagnosis of a disease but also in drug design specific for a disease stage. The project will integrate research into the undergraduate curriculum by assigning projects, in courses already developed by the PI, to solve problems in the proposed work. The project will provide research experience for undergraduate students using focused short projects during both academic year and summer. There is also a plan for the project to provide research experience for middle and high school students. The project will also develop approaches to introduce K-12 students to programming concepts as well as bioinformatics with the help of graphics. A summer institute is also planned to enhance student participation.