Our laboratory applies physical principles and computational methods to understand biological phenomena quantitatively, from single molecules to genomes and populations. Building on our long-standing work on nucleic acid dynamics, we currently pursue the following research themes.

1. Nucleic acid dynamics and G-quadruplexes

We study how DNA and RNA change their conformations through interactions with multivalent ions and proteins, using molecular dynamics simulations and statistical-mechanical analysis. A major focus is the G-quadruplex (G4), a non-canonical structure formed by guanine-rich sequences: we investigate counter-ion (K⁺) binding kinetics and the mechanisms of transitions among chair, basket and hybrid topologies. We also compare how G4-forming sequences are maintained or depleted across genomes, from viruses to eukaryotes (the "G4 paradox").

2. GM-MCMC and large-scale computing on Fugaku

To sample rare events such as conformational transitions efficiently, we develop a new Markov chain Monte Carlo framework (GM-MCMC). Large-scale simulations on the supercomputer Fugaku allow us to access time scales that are difficult to reach by conventional approaches.

3. Evolutionary genomics of aging and longevity

We compare aging-related proteins across animal phyla to characterize the modes of natural selection (purifying selection) underlying longevity evolution, and we analyze survival strategies in fluctuating environments (bet-hedging) theoretically.

4. Bayesian statistics and causal inference on clinical data

As a department within a medical school, we collaborate with clinical departments to apply Bayesian networks and causal inference to clinical databases, aiming to uncover the structure of disease risk factors.

5. AI for Science: machine learning for biophysics

We integrate machine learning with physical simulation, including score-based MCMC using graph neural networks (GNNs) and the evaluation of foundation-model representations for biological sequences.

Education

We teach Mathematics and Physics I–III and a physics laboratory course to first-year medical students. We also contribute to courses in medical informatics, information science and medical information systems for first-year students in medicine, nursing and advanced medical sciences. Through lectures, practical exercises and experiments, students develop foundational skills in mathematics, physics, experimental data analysis, basic statistics and information security.