Disease re-classi cation via integration of biological networks

Abstract

Currently, human diseases are classi ed as they were in the late 19th century, by considering only symptoms of the a ected organ. With a growing body of transcriptomic, proteomic, metabolomic and genomics data sets describing diseases, we ask whether the old classi cation still holds in the light of modern biological data. These large-scale and complex biological data can be viewed as networks of inter-connected elements. We propose to rede ne human disease classi cation by considering diseases as systemslevel disorders of the entire cellular system. To do this, we will integrate di erent types of biological data mentioned above. A network-based mathematical model will be designed to represent these integrated data, and computational algorithms and tools will be developed and implemented for its analysis. In this report, a review of the research progress so far will be presented, including 1) a detailed statement of the research problem, 2) a literature survey on relative research topics, 3) reports of on-going work, and 4) future research plans. 2