Session Details
[1MS-09]【E】Future of mathematical data science driven biomedical research
Wed. Dec 3, 2025 11:15 AM - 12:35 PM JST
Wed. Dec 3, 2025 2:15 AM - 3:35 AM UTC
Wed. Dec 3, 2025 2:15 AM - 3:35 AM UTC
Room 9(Pacifico Yokohama Conference Center 4F, 411+412)
Organizer: Shumpei Ishikawa (The University of Tokyo), Haruhisa Oda (The University of Tokyo)
Biomedical data is diversifying due to advances in bioinformatics, including high-dimensional genomics and various imaging techniques. To harness this complexity, mathematical data science is crucial. Here, we will introduce cutting-edge technologies in biomedical research, such as AI, machine learning, topological data analysis, and high-dimensional statistics, with practical examples, offering a platform for participants to discover tools for their own data analysis needs.
Introduction
[1MS-09-01]Topology and biomedicine: the future of fusion research
○Haruhisa Oda1 (1. Univ. Tokyo)
Q & A for Each Presentation
[1MS-09-02]Quantification of histopathological images utilizing deep neural networks
○Daisuke Komura1 (1. The University of Tokyo)
Q & A for Each Presentation
[1MS-09-03]Topological Image Analysis for biological shape measurement and comparison
○Vanessa Robins1 (1. The Australian National University)
Q & A for Each Presentation
[1MS-09-04]Antibody optimization and property prediction based on the development of high-throughput analysis system
○Sae Ito1, Ryo Matsunaga1, Nakakido Makoto1, Komura Daisuke2, Kato Hiroto2, Ishikawa Shumpei2, Tsumoto Kouhei3 (1. Dept. of Bioengineering, Grad Sch. of Eng., Univ. of Tokyo, 2. Dept. of Preventive Medicine, Grad Sch. of Med., Univ. of Tokyo, 3. Dept. of Chemistry and Biotechnology, Grad Sch. of Eng., Univ. of Tokyo)
Q & A for Each Presentation
[1MS-09-05]RECODE: a high-dimensional statistical approach to noise reduction of single-cell data - recent advances and beyond
○Yusuke Imoto1 (1. Kyoto University)
