Development of a personalized web-based data management system for physiological and metabolomic data integration in systems biology research.

Abstract

The Surgical Critical Care laboratory at the University of Minnesota conducts pre-clinical research that involves integration of physiological and metabolomic data. Managing the data using flat file data management systems has become increasingly difficult as the research progressed. Diversity of research groups and differences in data generation timeline makes data sharing between research groups difficult. This project explains the development of a data management system that can fulfill the data needs of the Surgical Critical Care laboratory at the University of Minnesota, and other research with similar data needs. Each systems biology research project has unique data needs and requires a personalized data management system. A web-based data management system would be independent of any computer operating system and makes data access and sharing easier. A relational database management system manages enormous amounts of data more effectively than a flat file data management system. These are some of the factors that influenced the development of a personalized web-based data management system with a back end relational database management system. Multi-disciplinary teams’ involvement, short-term goals, need for continuous changes/development, pre-clinical research, etc., are some of the factors that have driven the hybridization of open-source/commercial software products, and the usage of a health informatics model in combination with an agile software development model, in developing this software product named c-Surge. The c-Surge software was tested for user satisfaction using a survey, and to find any differences in the real-time data collected by the software and the manually collected data. Out of 12 members who used the software or participated in its development, 10 members have participated in the survey. Most of the users were satisfied/extremely satisfied with several functions of the software, or the overall software. A paired t-test was conducted to compare the real-time and manual data of each subject, and there was no statistically significant difference between the data types. The results show that home grown applications like c-Surge data management system are useful in fulfilling the data needs of a systems biology research project. The c-Surge data management system’s development process shows easier ways to develop a home grown application that can fulfill unique data needs of a systems biology research project within a reasonable economic expense.