Following the widespread use of genome-wide association studies to elucidate the genetic architectures of complex phenotypes, there has been a push to augment existing observational studies with additional layers of molecular information. The resulting high-dimensional data have led the emergence of research in integrative systems biology. Here, we examine recent progress in characterizing biological networks as well as the corresponding conceptual and analytical challenges. Using examples from metabolomics, we contend that integrative systems biology should prompt a re-examination of conventional phenotypic measures where heterogeneous or correlated phenotypes can be fine-mapped. Although still in its infancy, it is apparent that the large-scale characterization of molecular systems will transform our understanding of phenotype, biology and pathogenesis.