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RIKEN Center for Advanced Intelligence Project

Molecular Informatics Team

Team Leader: Koji Tsuda (D.Eng.)
Koji  Tsuda(D.Eng.)

Molecular informatics team aims to develop artificial intelligence methods that design functional biomolecules such as proteins and inorganic compounds such as metal, ceramic and nanoparticles. In addition to theoretical studies about automatic design methods such as Bayesian optimization and Monte Carlo tree search, we synthesize designed materials in collaboration with experimental scientists.

Main Research Field

Computer Science

Related Research Fields


Research Subjects

  • Automatic design methods for molecules and materials
  • Automatic construction of materials science databases from literature
  • Theoretical studies about experimental design

Selected Publications

Papers with an asterisk(*) are based on research conducted outside of RIKEN.
  1. *Ueno, T., Rhone, T.D., Hou, Z., Mizoguchi, T. and Tsuda,K.:
    “COMBO: An Efficient Bayesian Optimization Library for Materials Science”
    Materials Discovery, in press (2016).
  2. *duVerle, D.A., Yotsukura, S., Nomura, S., Aburatani, H. and Tsuda, K.:
    “CellTree: an R/bioconductor package to infer the hierarchical structure of cell populations from single-cell RNA-seq data”
    BMC Bioinformatics, 17, 363 (2016).
  3. *Terada, A., Okada-Hatakeyama, M., Tsuda, K. and Sese, J.:
    “Statistical significance of combinatorial regulations.”
    Proceedings of National Academy of Sciences, 110(32):12996-13001 (2013).
  4. *duVerle, D.A., Takeuchi, I., Murakami-Tonami, Y., Kadomatsu, K. and Tsuda, K.:
    “Discovering Combinatorial Interactions in Survival Data.”
    Bioinformatics, 29(23):3053-3059 (2013).
  5. *Ito, J., Tabei, Y., Shimizu, K., Tomii, K. and Tsuda, K.:
    “PDB-scale Analysis of Known and Putative Ligand-binding Sites with Structural Sketches”
    Proteins, 80:747-763 (2012).
  6. *Tabei, Y. and Tsuda, K.:
    “SketchSort: Fast All Pairs Similarity Search for Large Databases of Molecular Fingerprints”
    Molecular Informatics, 30(9):801-807 (2011).
  7. *Shimizu, K. and Tsuda, K.:
    “SlideSort: All Pairs Similarity Search for Short Reads”
    Bioinformatics, 27(4):464-470 (2011).
  8. *Georgii, E., Dietmann, S., Uno, T., Pagel, P. and Tsuda, K.:
    “Enumeration of Condition-Dependent Dense Modules in Protein Interaction Networks”
    Bioinformatics, 25:933-940 (2009).
  9. *Saigo, H., Nowozin, S., Kadowaki, T., Kudo, T. and Tsuda, K.:
    “gBoost: A mathematical programming approach to graph classification and regression.”
    Machine Learning, 75:69-89 (2009).
  10. *Tsuda, K., Raetsch, G. and Warmuth, M.K.:
    “Matrix exponentiated gradient updates for online learning and Bregman projection.”
    Journal of Machine Learning Research, 6:995–1018 (2005).

Lab Members

Principal Investigator

Koji Tsuda
Team Leader

Core Members

Yu Saito
Postdoctoral Researcher
Kei Terayama
Postdoctoral Researcher
Masato Sumita
Postdoctoral Researcher
Miho Hosoya
Technical Staff I
Yoji Imai
Technical Staff I

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