Computational and experimental methods in functional genomics : the good, the bad, and the ugly of systems biology

Abstract

Seven years into the postgenomic era, we sit atop a mountain of data whose generation was enabled by gene sequencing. The creation, integration, and analysis of these large scale data sets allow us to move forward toward the complementary goals of determining the individual roles of the thousands of uncharacterized mammalian genes and understanding how they work together to produce a healthy human being -- or, perhaps more importantly, how their malfunction results in disease. Collapsing the results of large-scale assays into gene networks provides a useful framework from which we can glean information that advances both of these goals. However, the utility of networks is limited by the quality of the data that goes into them. This study offers seeks to shed some light on the quality and breadth of protein interaction networks, describes a new experimental technique for functional genetic assays in mammalian cell lines, and ultimately suggests a strategy for how to improve the overall utility of the output generated by the systems biology community.