With an emphasis on the signaling network, the Systems Biomedicine Lab looks at the changes in the network during the transition from a normal state to a disease state. We use high throughput systems to measure biological quantities and we also use computational tools to project these measurements onto biological understanding through signaling pathways and network biology. We concentrate on understanding the cancer phenotype, mainly breast cancer and liver cancer, where we try to pinpoint malfunctions in network alterations, through RNA inhibition and RNA-seq (transcription measurements on massive parallel sequencing machine). We generate the data, as well as develop the computational tools to explore the data. We devise algorithms to convert data into legible biology and thus define the biological measurements we need to make progress. Our ultimate goal is to provide targets for therapeutical intervention.