Background

Genome-wide analyses, especially gene expression profiling using microarrays, have been extensively used in medical research and led to the identification of several molecular signatures involved in various aspects of human disease pathogenesis. Individual studies have typically investigated relatively small numbers of samples, making cross-study validation a crucial step for the scientific community. Combined use of gene expression data from public repositories has proved difficult due to inherent differences in microarray platforms, protocols used in independent laboratories, experimental designs, and annotations for both genes and samples. Several methodologies have been proposed to address these issues, depending on the experimental strategies and on the biological and clinical questions. When samples phenotypes are known, statistical methods that handle data sets separately and then apply gene-wise meta-analytic approaches have proven successful, allowing the identification of statistically relevant intersections of molecular signatures from different studies (Rhodes et al., 2002; Ghosh et al., 2003; Rhodes et al., 2004; Wang et al., 2004). Advanced multilevel models are now available for this task (Conlon et al., 2007; Scharpf et al., 2009). As an alternative, the assimilation of gene expression measurements, achieved by merging the data sets, has also been used to evaluate molecular signatures obtained from different studies (Sorlie et al., 2003; Hu et al., 2005; Kapp et al., 2006; Hayes et al., 2006). Finally, we previously developed a method to evaluate cross-platform consistency of expression patterns, using integrative correlation (ICOR).

This book is designed to enable readers to perceive and understand connections that they might have overlooked: connections among different disciplines; connections among budgetary institutions in the legislative and executive branches of federal and state governments; connections between U.S. budgetary policy and fiscal policy in other countries; connections between the perceptions of voters and policymakers and actual budget policy. In this section, we examine more closely intergovernmental connections that influence fiscal outcomes.

John Joseph Wallis and Barry Weingast's examination of state constitutional debt limitations and their effect on the choice of financing methods for infrastructure differs from previous chapters in two crucial ways. First, they provide the first sustained analysis of local governments and their role in fiscal policy as they issue bonds to build roads, schools, sports stadiums, and other public goods. Any complete assessment of local government must take account of state constitutional and statutory provisions because local governments are created by the state and their powers are dramatically affected by state decisions. Second, Wallis and Weingast provide a different sort of comparative analysis than we have seen before: their analysis is historical, comparing infrastructure financing in the United States at three different periods over a 150-year time span. Although other chapters may have provided some historical context for contemporary budget institutions, this chapter is the most sustained empirical comparison of budget institutions and their consequences across a substantial period of time.