Introduction

Abstract

Healthcare practice, policy, and research have all become profoundly information-intensive and intertwined. Perhaps in no discipline is this more true than in cancer. Whether one seeks best practice, rational and compassionate resource allocation, or the application of mouse model genomics to human disease, all these activities increasingly depend upon an underlying body of data, inferences, and knowledge to progress intelligently. How then are we to make sense of the burgeoning mass of information relevant to matters in the cancer community? Furthermore, how can we ensure that basic science breakthroughs have an efficient and timely impact upon improved care practices and appropriate policy decisions?