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The second bracketed term is obviously the difference between the expected value of the target h( ) in the true distribution at time n and the expected value of h( ) in the stationary distribution. Given a geometrically ergodic Markov chain, this quantity converges geometrically fast to zero since Ef h( ) E 0 h( ) k n for a positive k, and a (0 : 1). Now the rst bracketed term is the difference between the current empirical average and its expectation at time n. Except at the uninteresting starting point, these are never nonasymptotically equivalent, so even in stationarity, the empirical average has not converged. This is not bad news, however, since we know for certain by the central limit theorem that

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basic processes are illustrated in Figure 5.1. Genetics can impact each phase of the process. It is important to know that the impact of genetics and genomics on society will be felt soonest in genetics predicting the safety and ef cacy of medicines in the marketplace. In contrast to popular belief, the impact will be greater in the traditional area of small molecules than in gene therapy. The process of drug discovery encompasses identifying a biological target that appears to play a role in the disease of interest or a role in the symptom expression of the disease. From that point, small molecules are usually designed to increase the level of the target or block its activity. These molecules must also be designed so that the chemical synthesis is not too expensive and is amenable to making large quantities. Additional requirements for the chemical include properties that make it stable in heat and light and easily absorbed by the human gastrointestinal tract. Because people generally do not do well taking medicines more than twice a day, the chemical must also last in the body long enough to enable patients to take only two pills a day. Last but not least, the medicine must be nontoxic. Genetics has been touted as playing a role in the very rst part of this process: identifying new targets for the design of medicines. To date, this approach has been disappointing. Even though many susceptibility genes have been identi ed (e.g., NIDDM 1, low-density lipoprotein receptorrelated protein 5, ApoE), few, if any, have resulted in new drug candidates. While the target work continues, there is value in using genetics for drug discovery for better disease understanding and the identi cation of new disease pathways that were not identi ed using traditional approaches.

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Casanova, M F, Buxhoeveden, D P, Cohen, M J, Switala, A E, & Roy, E L (2002) Minicolumnar pathology in dyslexia Annals of Neurology, 52, 108 110 Casanova, M F, Buxhoeveden, D P, Switala, A E, & Roy, E (2002) Minicolumnar pathology in autism Neurology, 58, 428 432 Casanova, M F, van Kooten, A J, Switala, A E, van Engeland, H, Heinsen, H, Steinbusch, H M, et al (2006) Minicolumnar abnormalities in autism Acta Neuropathologica, 112, 287 303 Casey, B J (2004) Mathematics problem-solving adventures: A language arts based supplementary series for early childhood that focuses on spatial sense In D H Clements, J Sarama, & A DiBiase (Eds), Engaging young children in mathematics: Standards for early childhood mathematics education (pp 377 389) Mahwah, NJ: Erlbaum Casey, P H, Whiteside-Mansell, L, Barrett, K.

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