Acknowledgment: This material is based upon work supported by the National Science Foundation through the Mississippi State University MS EPSCoR seed grant.

Disclaimer: Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Project Summary

This collaborative research brings together computer scientists from the University of Southern Mississippi (USM), physiologists from the University of Mississippi Medical Center (UMMC), and biologists from Mississippi State University (MSU) to study effective time-varying graph visualization approaches. The goal is to help interpret the complex parameter space: such as those in HumMod and in the Yeast datasets. Our approach is to integrate depicting and embedding algorithms that will allow scientists to quickly perceive pattern changes, thus optimizing the knowledge discovery process. The outcome will be taxonomy and tools for time-varying graph visualization; the results will be disseminated through open-source software, experimental data, publications, presentations, and classroom educations.