Abstract
Rapid advances in high-throughput technologies, including next-generation sequencing, proteomics, and metabolomics, are providing exceptionally detailed descriptions of the molecular changes that occur in diseases. However, it is difficult to use these data to reveal new therapeutic insights for several reasons. Despite their power, each of these methods still only captures a small fraction of the cellular response. Moreover, when different assays are applied to the same problem, they provide apparently conflicting answers. I will show how specific network modeling approaches reveal the underlying consistency of the data by identifying small, functionally coherent pathways linking the disparate observations. These patient-specific networks may provide critical insights for targeted therapies.