Frontier Symposium は、地域および国際的な学術交流と共同研究を促進するために創設された、日中韓による年次シンポジウムです。2026年のプログラムでは、化学や生物物理学を含む計算科学のフロンティア研究と実験生物学を融合し、学際的研究を推進するためにAIや新しい計算手法と実験技術の統合に焦点を当てます。また、若手研究者が研究成果を発表し、アイデアを交換し、地域内外の研究者とのネットワークを構築するための国際的な場を提供することを主要な目的としています。

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Understanding the essence of life requires an integrated approach that spans the vast spatiotemporal scales from atoms and molecules to entire cells. This workshop aims to establish the foundational methodology for “AI-driven multiscale simulation” that harnesses recent advances in AI technology to bridge simulations across different hierarchical levels. Through this workshop, we seek to create a new research paradigm for achieving a truly integrated understanding of life phenomena from molecules to cells, establishing “AI-driven Multiscale Life Science”.

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Understanding the relationship between function and structure of biomolecules such as proteins and nucleic acids requires not only simulations by molecular dynamics, but also a deep understanding of various physical chemical theories such as solution theory and molecular vibrational theory, as well as information science such as machine learning and Bayesian statistics. In this workshop, experts in these fields are invited to give lectures to discuss state-of-the-art techniques/results and to understand their interrelationships. In addition, experts are invited from one of the Programs for Promoting Research on the Supercomputer “Fugaku” to discuss the cutting-edge computational science research.

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Understanding the relationship between function and structure of biomolecules such as proteins and nucleic acids requires not only simulations by molecular dynamics, but also a deep understanding of various physical chemical theories such as solution theory and molecular vibrational theory, as well as information science such as machine learning and Bayesian statistics. In this workshop, experts in these fields are invited to give lectures to discuss state-of-the-art techniques/results and to understand their interrelationships. In addition, experts are invited from one of the Programs for Promoting Research on the Supercomputer “Fugaku” to discuss the cutting-edge computational science research.

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Computational approaches are becoming increasingly important in biophysics, not only for simulations but also for the detailed interpretation of various measurement data. In particular, with the recent launch of modern supercomputers such as Fugaku, enormous computational resources have become available, and new computational methods and applications that were not computationally feasible in the past are becoming possible. In this symposium, we invite researchers who conduct cutting-edge high-performance computations. We discuss current computational research using supercomputers as well as future directions of computational biophysics.

Proteins often assemble to form “mesoscopic” complexes – some ordered and some disordered – to exert their functions in the cell. Therefore, elucidating their architectures and physical properties is necessary to understand the molecular mechanisms underlying life phenomena and diseases. In this research area “Cross-Scale Biology”, we particularly focus on mesoscopic structures in the range of 20–500 nm (including LLPS condensates), which we define as “meso-entangled bodies (MEBs)”, because MEBs are thought to be key factors that determine the fate of organisms through the transition from disordered to ordered states at the mesoscale. In this symposium, researchers working on the MEBs will gather to discuss the latest technologies and findings, including In-cell AFM, cryo-EM, chemical biology and LLPS.

GENESIS (GENeralized-Ensemble SImulation System)は様々な生体分子（タンパク質、核酸、リガンド低分子など）やその複合体を対象にした分子動力学(MD)計算を行うためのソフトウェアです。「富岳」などのスーパーコンピュータによる効率的な大規模並列計算を実現できることが大きな特長です。 本サマースクールでは、GENESISを利用したMD計算の理論と実践の両方を学べるよう、レクチャーおよび「富岳」での計算を実際に体験できるハンズオンチュートリアルを実施します。 初めてMD計算に触れる方からより深く学びたい方、GENESISに興味をお持ちの方まで幅広い参加者を対象としています。 ふるってご参加ください。

Machine learning approaches such as AlphaFold are imparting significant impacts on various scientific fields. Molecular simulations are no exception. In this workshop, we will argue “what is and will be true progress that cannot be achieved without machine learning approaches” and “how AlphaFold will impact the future of molecular simulations.