Priority Issue on Post-K computer. Integrated Computational Life Science to Support Personalized and Preventive Medicine
 

Sub-theme A

Unraveling the characteristics, temporal-spatial diversity and origin of cancer by large-scale sequencing

For realization of personalized and preventive medicine for cancer, we need to elucidate characteristics, temporal-spatial diversity and origin of cancer by using large-scale sequencing data analyses obtained from whole genome sequence, RNA sequence, methylation sequence, single cell sequence, and DNA sequence sourced from blood plasma. In sub-theme A, we develop a computational strategy based on these types of sequences and prove that it will strongly augment personalized and preventive medicine.
With the intensive big data analyses, the K computer and the post-K computer can drastically accelerate cancer research and make innovations for prevention, precision diagnosis, and optimal therapeutics for cancer.
To comprehensively understand systems disorders in cancer, we will carry out big data analysis and systems analysis of cancer with the K computer and the post- K computer by developing key software applications together with already available software applications whose effectiveness has been already established.

Group Leader

Satoru MIYANO (The Institute of Medical Science, The University of Tokyo)


Overall image of Subtheme A


Achievements

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