Closing the scientific loop: bridging correlation and causality in the petaflop age

Abstract

Advances in computing capability offer the biomedical research community the prospect of creating simulations at a previously unimaginable scale. A diagnostic analysis of the underpinnings of the translational dilemma suggests that the current high-throughput, data-rich research environment has led to an imbalance in the relationship between determinations of correlation and the evaluation of causality. Here I describe the use of high-performance computing technologies to facilitate high-throughput hypothesis evaluation combined with an evolutionary paradigm for the advancement of scientific knowledge. This combination provides a roadmap for closing the scientific loop between correlation and causality, a necessary step if translational endeavors are to succeed.