Visual Analytics for OMIC Data
A critical issue for the CCE project is how to rapidly evaluate and validate model predictions. An interactive, integrated, visual and statistical analysis capability was developed that will serve as a model for future CCE projects. An interactive visual analytic approach harnesses the power of traditional analysis and data mining techniques, as well as the power of the human visual system for instantly detecting patterns, trends and clusters, and the increased performance of human reasoning through the use of external cognitive artifacts.
Current efforts in the Cite this work
Researchers should cite this work as follows:
David Ebert; Ross Maciejewski (2008), "Visual Analytics for GCxGC-MS Data," http://ccehub.org/resources/105.