Although a number of strategies for identifying genetic variations that influence common complex neuropsychiatric diseases have been proposed, implemented, and pursued, many of these strategies have not been able to yield compelling insights into disease pathogenesis. The reasons for this are themselves complex, but it is arguable that extending and integrating available strategies to include detailed biological information can only improve their yield. In this review we consider computational methods, databases, and related resources that can help put into perspective the biological and functional significance of genes and genetic variations interrogated in contemporary gene mapping strategies for neuropsychiatric diseases. Computational methods for evaluating the biological significance of genetic variations, as opposed to laboratory assays, are quick and, for the most part, easy to use and are growing in sophistication. We provide a discussion of the limitations of available resources, but ultimately argue that more integrated approaches to the genetic dissection of complex neuropsychiatric conditions are necessary and likely to be the rule rather than the exception in future investigations.