Computational Biology Group/Core LaboratoriesTsuda Laboratory
(Laboratory of Large-Scale Knowledge Discovery)

Our areas of research include machine learning, data mining, statistical science and their applications to molecular biology, protein science, organic chemistry, materials science and related fields.

Machine learning, Artificial Intelligence, Statistical Science, Molecular design, Quantum Computation
Development of molecules and materials with machine learning

We are developing machine learning algorithms for automatic design of organic compounds, proteins, peptides and inorganic materials in collaboration with external researchers in other institutes such as NIMS and RIKEN.

  • Fluorescent molecule designed by ChemTS algorithm.

Developing methods for discovering reliable knowledge from various kinds of data

We are developing methods for discovering reliable knowledge from diverse kinds of data produced in life sciences. Examples include CellTree and LAMP.

  • Discovery of combinatorial effects with LAMP

Developing machine learning algorithms based on quantum computation

We are developing machine learning algorithms using Ising machines such as D-wave quantum annealers. Examples include FMQA and CONBQA.

  • Black-box optimization with FMQA

  • Sumita et al., Sci. Adv., 8, eabj3906, 2022.
  • Terayama et al., Acc. Chem. Res., 54, 1334-1346, 2021.
  • Kitai et al., Phys. Rev. Res., 2, 013319, 2020.
  • Sakurai et al., ACS Cent. Sci., 5, 319-326, 2019.
  • Saito et al., ACS Synth. Biol., 7, 2014-2022, 2018.
  • Ju et al., Phys. Rev. X, 7, 021024, 2017.
  • Yang et al., Sci. Tech. Adv. Mater., 18, 972-976, 2017.
  • Ueno et al., Mater. Discov., 4, 18-21, 2016.
  • Terada et al., PNAS, 110, 12996-13001, 2013.

We accept master and doctoral students with various background including computer science and biology. Contact us for further questions.

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