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.
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