Caroline performed a comparative analysis of proteomic and phosphoproteomic data from ovarian cancer patients in R, as well as, worked with a breast cancer database using MySQL, Cloud SQL, and the Google Cloud Platform in conjunction with a doctor at MUSC. She converting the large breast cancer cell line database from CSV files into a SQL database that was to be used in a web application.
This project completed Caroline's Capstone requirement during her last semester of undergraduate studies at the College of Charleston. A team composed of herself and two addition undergraduate studentsworked with KopisUSA & Vigilix, using their system alert database to predict if a store qualified as a high frequency alert store, as well as, quantify the probability for a repeat alert for a given time interval.
Caroline has had the wonderful opportunity to pair with Dr. Dan McGlinn and the mob-r team of collaborators, to create a graphical user interface for the R package mob-r using R shiny framework. This application features various biodiversity calculation functions, such as rarefaction, abundance, mob metrics, & delta statistics, and allows for dynamic parameter selection which allows the user to customize the functions to meet their specific calculation needs without having to use or see any of the r package code.
Working with Dr. McGlinn and the mob-r team once again, Caroline helps to develop a testing suite for various the mob-r functions that are altered and/or optimized at a greater frequency. These test assure that any changes to the functions can be tested quickly and accurately by members of the mob-r team to help streamline the package development process.