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184 The road travelledfuture whole-exome or genome sequencing studies, I keep wondering abouthow the knowledge from GWAS could be further refined and ultimately appliedto improve public health. In general, I see the pattern that wheneveranewtechnologyemerges,thereistremendousinterestaboutmakingnew“discovery,” but the effort is not proportionate when it comes to following-upthese discoveries for better “characterization” of risk or/and the underlyingcausal mechanism. Interestingly, while in the discovery effort statisticians facestiff competition from researchers in other quantitative disciplines, like geneticists,bioinformaticians, computer scientists and physicists, statisticians havethe potential to develop a more exclusive niche in the “characterization” stepswhere the underlying inferential issues are often much more of complex naturethan simple hypothesis testing.17.6 ConclusionIn the last fourteen years, the biggest change I observe within myself is howI think about a problem. When I started working on refinement of kin-cohortmethods, I focused on developing novel methods but was not very aware ofall the underlying very complex clinical and epidemiologic subject-matter issues.Now that I am struggling with the question of what would the discoveriesfrom current GWAS and future sequencing studies mean for personalizedmedicine and public health, I feel I have a better appreciation of those pertinentscientific issues and the related debate. For this, I owe much to thehighly stimulating scientific environment of our Division, created and fosteredover decades by our recently retired director Dr. Joseph Fraumeni Jr. and anumber of other leaders. The countless conversations and debates I had withmy statistician, epidemiologist and geneticist colleagues in the meeting rooms,corridors and cafeteria of DCEG about cutting-edge issues for cancer genetics,epidemiology and prevention had a major effect on me. At the same time, mytraining in theory and methods always guides my thinking about these appliedproblems in a statistically rigorous way. I consider myself to be fortunate toinherit my academic “genes” through training in statistics and biostatisticsfrom the Indian Statistical Institute and the University of Washington, andthen be exposed to the great “environment” of DCEG for launching my careeras a statistical scientist.Congratulations to COPSS for sustaining and supporting such a greatprofession as ours for 50 years! It is an exciting time to be a statisticianin the current era of data science. There are tremendous opportunities forour profession which also comes with tremendous responsibility. While I wasfinishing up this chapter, the US Supreme Court ruled that genes are not“patentable,” implying genetic tests would become more openly available toconsumers in the future. The debate about whether Angelina Jolie got the