Rchr
J-GLOBAL ID:202001011756821154   Update date: May. 17, 2024

Tsuda Koji

ツダ コウジ | Tsuda Koji
Affiliation and department:
Job title: 教授
Research theme for competitive and other funds  (14):
  • 2020 - 2025 探索的分析によるデータ駆動型仮説の信頼性評価法の確立と生命科学分野における実証
  • 2020 - 2024 機械学習が道先案内する進化分子工学:がん治療抗体のスマート成熟プロセス提案
  • 2015 - 2020 Research on Fundamental Algorithms of Discrete Structure Manipulation Systems
  • 2016 - 2018 Development of machine learning methods for materials informatics
  • 2015 - 2018 Exploration of nanostructure-property relationships for materials innovation
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Papers (142):
  • Andrejs Tučs, Tomoyuki Ito, Yoichi Kurumida, Sakiya Kawada, Hikaru Nakazawa, Yutaka Saito, Mitsuo Umetsu, Koji Tsuda. Extensive antibody search with whole spectrum black-box optimization. Scientific Reports. 2024. 14. 1. 552
  • Yota Fukui, Kosuke Minami, Kota Shiba, Genki Yoshikawa, Koji Tsuda, Ryo Tamura. Automated odor-blending with one-pot Bayesian optimization. Digital Discovery. 2024. 3. 5. 969-976
  • Takumi Yoshida, Hiroyuki Hanada, Kazuya Nakagawa, Kouichi Taji, Koji Tsuda, Ichiro Takeuchi. Efficient model selection for predictive pattern mining model by safe pattern pruning. Patterns. 2023
  • Kei Terayama, Yamato Osaki, Takehiro Fujita, Ryo Tamura, Masanobu Naito, Koji Tsuda, Toru Matsui, Masato Sumita. Koopmans’ Theorem-Compliant Long-Range Corrected (KTLC) Density Functional Mediated by Black-Box Optimization and Data-Driven Prediction for Organic Molecules. Journal of Chemical Theory and Computation. 2023. 19. 19. 6770-6781
  • Ryo Tamura, Kei Terayama, Masato Sumita, Koji Tsuda. Ranking Pareto optimal solutions based on projection free energy. Physical Review Materials. 2023. 7. 9
more...
MISC (13):
  • Tomoyuki Ito, Hafumi Nishi, Thuy Duong Nguyen, Yutaka Saito, Tomoshi Kameda, Hikaru Nakazawa, Koji Tsuda, Mitsuo Umetsu. Application of Next-Generation Sequencing Analysis in the Directed Evolution for Creating Antibody Mimic. BIOPHYSICAL JOURNAL. 2021. 120. 3. 87A-87A
  • Yutaka Saito, Misaki Oikawa, Hikaru Nakazawa, Takumi Sato, Tomoshi Kameda, Koji Tsuda, Mitsuo Umetsu. Can Machine Learning Guide Directed Evolution of Functional Proteins. BIOPHYSICAL JOURNAL. 2020. 118. 3. 339A-339A
  • Tomoshi Kameda, Yutaka Saito, Misaki Oikawa, Hikaru Nakazawa, Teppei Niide, Koji Tsuda, Mitsuo Umetsu. MACHINE-LEARNING-GUIDED MUTAGENESIS FOR DIRECTED EVOLUTION OF FLUORESCENT PROTEINS. PROTEIN SCIENCE. 2019. 28. 203-204
  • Ichigaku Takigawa, Ken-ichi Shimizu, Koji Tsuda, Satoru Takakusagi. Machine learning predictions of factors affecting the activity of heterogeneous metal catalysts. ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY. 2018. 255
  • Safe Pruning Rule for Predictive Sequential Pattern Mining and Its Application to Bio-logging Data Analysis. 2017. 116. 500. 41-48
more...
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