Researcher Database

（Last updated : 2023-08-24 16:32:53）

TOHSATO Yukako

Department / Course College of Information Science and Engineering Department of Information Science and Engineering

Title / Position Professor

Academic background
1.	2002/03 Degree Acquisition	│ Osaka University
2.	1997/03 Degree Acquisition	│ Kyushu Institute of Technology
3.	～1995/03	Faculty of Computer Science and Systems Engineering │ Kyushu Institute of Technology │ Graduated
4.	～1997/03	Doctoral Program (1st Semester) │ Dept. Information Science │ Kyushu Institute of Technology │ Completed
5.	～2002/03	Doctoral Program (2nd Semester) │ Graduate School, Division of Engineering Science │ Osaka University │ Completed

Business career
1.	2013/03/31 ～ 2017/03/31	Research scientist │ Quantitative Biology Center │ RIKEN
2.	2012/09/01 ～ 2013/03/31	Visiting researcher │ │ RIKEN
3.	2008/04/01 ～ 2013/03/31	Assistant Professor │ Department of Bioinformatics │ Ritsumeikan University
4.	2004/04/01 ～ 2008/03/31	Lecturer │ Department of Bioinformatics │ Ritsumeikan University
5.	2003/04/01 ～ 2004/03/31	Assistant Researcher │ │ Osaka University
Display All（7）

Research summary
Computational Analysis and Modeling for Biological Dynamics Data. Recent advances of measuring and manipulating technologies in life sciences are generating biological experimental data including spatiotemporal dynamics within and between molecules, cells, tissues and entire organisms. Computational approaches for such large-scale multi-dimensional data have the potential to improve our understanding of biological phenomena such as development, aging and disease causation – toward a data-driven science. We are therefore pursuing research and development of algorithms, methods, and software tools that will enable comprehensive interpretation of such data; for example, image processing and data analysis methods using statistics, machine learning, and artificial intelligence techniques, and mathematical modeling methods based on physical and chemical laws. Our aim is to understand biological phenomena and to predict how it will be regulated under various perturbations.

Books
1.	2011/04	Protein Function Prediction for Omics Era: (15) Towards elucidation of the Escherichia coli K-12 unknowneome │ ,pp.289-306 (Co-authored)

Papers
1.	2023/06/15	Large-scale image processing and three-dimensional reconstruction of mouse brains with neurogenic-tagged neurons │ Proceedings of the 13th International Conference on Biomedical Engineering and Technology (ICBET 2023) │ (Co-authored)
2.	2023/04/03	Metabolic network analysis by time-series causal inference using the multi-dimensional space of prediction errors │ IPSJ Transactions on Bioinformatics │ 16,pp.13-19 (Co-authored)
3.	2023/02/17	Gene deletion algorithms for minimum reaction network design by mixed-integer linear programming for metabolite production in constraint-based models: gDel_minRN │ Journal of Computational Biology │ 30 (5),pp.553-568 (Co-authored)
4.	2022/09/09	Phenotype anomaly detection for biological dynamics data using a deep generative model │ The 31st International Conference on Artificial Neural Networks (ICANN 2022), Lecture Notes in Computer Science │ 13530,pp.432-444 (Co-authored)
5.	2022/09/07	Unsupervised domain adaptation using temporal association for segmentation and its application to C. elegans time-lapse images │ he 31st International Conference on Artificial Neural Networks (ICANN 2022) │ 13531,pp.469-481 (Co-authored)
Display All（37）

Grants-in-Aid for Scientific Research -KAKENHI-
1.	2020/04/01 ～ 2025/03/31	Algorithms for metabolic network design for producing useful substances │ Grant-in-Aid for Scientific Research(B)
2.	2016/10/21 ～ 2020/03/31	Development of stochastic models to represent cellular states and their application to analysis of nuclear division dynamics │ Grant-in-Aid for Scientific Research (C)
3.	2013/04/01 ～ 2016/03/31	Strategy of a cell to survive during a long term stationary phase before cell proliferation. │ Grant-in-Aid for Scientific Research (A)

E-Mail Address