Koji Tsuda
Koji Tsuda (Ph.D.)
Title
Team Leader

Members

  • Team leader
    Koji Tsuda
  • Research scientist
    Masato Sumita
  • Research scientist
    Adnan Sljoka
  • Special postdoctoral researcher
    Kosuke Hamazaki
  • Senior visiting scientist
    Mitsuo Umetsu
  • Visiting scientist
    Yukari Katsura
  • Visiting scientist
    Kazuki Yoshizoe
  • Visiting scientist
    Masaya Kumagai
  • Visiting scientist
    Motoki Shiga
  • Visiting scientist
    Kei Terayama
  • Visiting scientist
    Ryo Tamura
  • Visiting scientist
    Andrejs Tucs
  • Visiting scientist
    Weilin Yuan
  • Part-time worker I
    Liyao Wang
  • Part-time worker I
    Peiheng Zou

Introduction

Laboratory's photo

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
Research Field
Multidisciplinary
Research Subjects
Automatic design methods for molecules and materials
Automatic construction of materials science databases from literature
Theoretical studies about experimental design
RIKEN Website URL
http://www.riken.jp/en/research/labs/aip/goalorient_tech/mol_inf/

Introduction Video

Molecular Informatics Team (PI: Koji Tsuda) thumbnails
Show details
Poster(s)

Related posts

posted on August 8, 2024 12:59Information
Conformational dynamics and allostery elucidate how GPCR couple to multiple G-proteins, offering mechanistic insights into coupling-promiscuity and novel drug discovery strategies (Nature Chemical Biology, August 2, 2024)
posted on December 20, 2023 09:43Information
【Published】“Is Scientific Discovery Possible through AI and Simulation?”（Experimental Medicine, January 2024 Issue, YODOSHA、Decemer 20, 2023）
posted on July 1, 2022 09:31Information
【Published】Close-up Science Road( RIKEN NEWS, July 1, 2022)
posted on May 24, 2022 08:22Information
【Published】Close-up Science Road( RIKEN Web, May 23, 2022)
posted on March 10, 2022 12:07InformationPressrelease
De novo creation of a naked eye–detectable fluorescent molecule based on quantum chemical computation and machine learning
posted on December 2, 2021 17:34InformationPressrelease
Machine-Learning-Guided Library Design Cycle for Directed Evolution of Enzymes: The Effects of Training Data Composition on Sequence Space Exploration
posted on April 15, 2021 16:15Information
YAMAMOTO Yoichiro Team Leader and KATSURA Yukari formar Visiting Scientist of AIP participated in the “NISTEP Selection” Meeting
posted on March 23, 2021 19:26Pressrelease
Conformational Equilibria in GPCRs provides critical clues about activation mechanisms
posted on March 15, 2021 14:08Seminar
[21st AIP Open Seminar] Talks by Molecular Informatics Team
posted on December 18, 2020 10:26Pressrelease
A Method is developed for validating the Accuracy of NMR Protein Structures - Expected to accelerate drug discovery
posted on December 22, 2020 10:02Award
YAMAMOTO Yoichiro Team Leader and KATSURA Yukari Visiting Scientist of AIP were selected as “NISTEP Selection”
posted on May 11, 2020 13:26Information
Research related to COVID-19
posted on November 14, 2019 10:44Information
Our three researchers gave presentations at CAS-RIKEN Young Scientists Seminar
posted on January 23, 2019 09:45Pressrelease
Design and Validation of World-Class Multilayered Thermal Emitter Using Machine Learning —Selection of an Optimum Structure from Approximately Eight Billion Candidates May Make Society More Energy Efficient—
posted on November 16, 2018 10:51Information
Swedish Foundation for Strategic Research "The Future Research Leaders Program" Visit AIP
posted on September 7, 2018 17:55Information
Twelve papers are accepted at NeurIPS 2018