Talk by Prof. Ryuji Hamamoto on “Integrated Omics Analysis of Cancer Using Machine Learning and Deep Learning

We are now conducting multimodal analysis of the omics data such as genome data, epigenome data, medical imaging data [CT, MRI, PET, endoscopy, pathology], proteome data, micro RNA data, cell line data, PDX [Patient-Derived Xenografts] data and clinical information in various types of cancers by machine learning and deep learning to clarify the nature of cancer. On the basis of our findings, we plan to develop novel diagnostic and therapeutic methods for cancer, and will also use them to develop novel anti-cancer drugs. Since I hope to contribute to the development of cancer medicine based on the collaboration with members of AIP center, I would be grateful if you could join the seminar and discuss future research strategy.

Cancer Translational Research Team
Ryuji Hamamoto