• Search Research Projects
  • Search Researchers
  • How to Use
  1. Back to previous page

Guo Zhongliang  郭 中梁

ORCIDConnect your ORCID iD *help
Researcher Number 20875819
Other IDs
Affiliation (Current) 2026: 愛知県がんセンター(研究所), システム解析学分野, 研究員
Affiliation (based on the past Project Information) *help 2025: 愛知県がんセンター(研究所), システム解析学分野, 研究員
2022 – 2023: 愛知県がんセンター(研究所), システム解析学分野, 研究員
Review Section/Research Field
Principal Investigator
Basic Section 62010:Life, health and medical informatics-related
Keywords
Principal Investigator
サンプリング / タンパク質間相互作用 / タンパク質構造予測モデル / タンパク質動態 / ベイズ推論 / マルチモーダル学習 / 結合能予測 / タンパク質間相互作用予測 / TCR / タンパク質設計 / トポロジカルデータ解析 / タンパク質大規模言語モデル / 機械学習
  • Research Projects

    (2 results)
  • Research Products

    (4 results)
  •  タンパク質の結合動態予測における構造生成モデルの応用と評価手法の開発Principal Investigator

    • Principal Investigator
      郭 中梁
    • Project Period (FY)
      2025 – 2026
    • Research Category
      Grant-in-Aid for Early-Career Scientists
    • Review Section
      Basic Section 62010:Life, health and medical informatics-related
    • Research Institution
      Aichi Cancer Center Research Institute
  •  Design of immunoreceptor protein through the integration of machine learning and Bayesian inferencePrincipal Investigator

    • Principal Investigator
      Guo Zhongliang
    • Project Period (FY)
      2022 – 2023
    • Research Category
      Grant-in-Aid for Early-Career Scientists
    • Review Section
      Basic Section 62010:Life, health and medical informatics-related
    • Research Institution
      Aichi Cancer Center Research Institute

All 2024 2023 2022

All Journal Article Presentation

  • [Journal Article] Machine learning methods for protein-protein binding affinity prediction in protein design2022

    • Author(s)
      Zhongliang Guo and Rui Yamaguchi
    • Journal Title

      Frontiers in Bioinformatics

      Volume: 2 Pages: 1065703-1065703

    • DOI

      10.3389/fbinf.2022.1065703

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-22K18003, KAKENHI-PROJECT-21K19939
  • [Presentation] A Sequence and topological feature integration for accurate protein-protein binding affinity estimation2024

    • Author(s)
      郭 中梁、武藤 理、山口 類
    • Organizer
      第6回日本メディカルAI学会学術集会
    • Data Source
      KAKENHI-PROJECT-22K18003
  • [Presentation] An integrated approach using sequential and structural features for precise prediction of protein-protein binding affinity2024

    • Author(s)
      Zhongliang Guo, Osamu Muto, Rui Yamaguchi
    • Organizer
      IUPAB Congress 2024
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-22K18003
  • [Presentation] A multimodal framework combining sequence and topological features for accurate protein-protein binding affinity prediction2023

    • Author(s)
      Zhongliang Guo, Osamu Muto, Yasunori Fukushima, Ayako Demachi-Okamura, Motonori Ota, Ryo Yoshida, Hirokazu Matsushita, Rui Yamaguchi
    • Organizer
      GIW ISCB ASIA 2023
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-22K18003

URL: 

Are you sure that you want to link your ORCID iD to your KAKEN Researcher profile?
* This action can be performed only by the researcher himself/herself who is listed on the KAKEN Researcher’s page. Are you sure that this KAKEN Researcher’s page is your page?

この研究者とORCID iDの連携を行いますか?
※ この処理は、研究者本人だけが実行できます。

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi