🚨Apply for a position under the BDR–RISE Program!
Seeking highly motivated early-career researchers to lead cross-disciplinary projects across multiple BDR labs.
🗓️Deadline: June 30, 2026
See full job ad👇
www.riken.jp/en/careers/r...
What is the BDR-RISE Program?
Find out more about the program from the link below.👇
www.bdr.riken.jp/en/career/jo...
RIKEN BDR is now entering its 9th year!
We begin FY2026 with 34 principal investigators.
Stay tuned for updates on our research, events, and job opportunities.
Thank you for your continued support!
【採用情報】
理化学研究所では、2027年度から研究を開始する理研ECL(Early Career Leaders)制度に基づくチームリーダー/ユニットリーダーを公募中です！
理研BDRでも複数のECLリーダーが活躍中です。
応募締切など詳細は以下の画像のリンク先からご確認ください。
www.riken.jp/careers/prog...
Read about a study led by BDR's Tomoya Kitajima showing that a protein-based artificial #kinetochore they developed can serve as decoys to relieve pulling forces acting on #chromosome pairs in dividing aged mouse #oocytes to prevent premature segregation.
👇
www.riken.jp/en/news_pubs...
bdr.riken.jp
🚨Apply now for the #RIKEN Early Career Leader (ECL) program!
Seeking talented #earlycareer #researchers with no or limited PI experience to pursue original research at one of RIKEN's centers, including BDR!
Preregistration deadline: Noon, July 9, 2026 JST
More details👇
www.riken.jp/en/careers/p...
The above study was published in #NatureCellBiology.
"Designing protein-based artificial kinetochores as decoys to prevent meiotic errors in oocytes."
doi.org/10.1038/s415...
RIKEN BDR's Shiwei Su, Nobuyuki Tanaka & others developed a new AI model “Biointerface BERT Encoder for Interaction Translation (BB-EIT)” that can accurately predict protein adsorption across a wide range of polymer surfaces, useful for biomaterial design.
doi.org/10.1021/acsa...
RIKEN researchers have developed protein assemblies that relieve the strain on chromosome pairs during cell division, and which could ultimately be used to facilitate healthy reproduction in older par...
Zhou et al. design protein-based artificial kinetochore constructs as decoys to prevent premature chromosomal separation in aged oocytes. These constructs compete with chromosomal kinetochores, reduci...
doi.org
Precise control of protein adsorption on polymer surfaces is essential in materials science and biomaterial design, with applications in antifouling materials, biosensors, cell culture, and drug delivery systems. However, the complex interactions between polymers and proteins and the limited availability of high-quality interaction data remain major challenges in polymer informatics. Current approaches often lack the generalizability needed to model diverse polymer–protein systems within a single unified framework, and there is a paucity of comprehensive predictive models capable of handling diverse polymer–protein interactions. To address these challenges, we introduce BB-EIT (Biointerface BERT Encoder for Interaction Translation), a novel generalized model designed to accurately predict the amount of diverse protein adsorption on polymer brushes. BB-EIT leverages the pretrained ChemBERTa large language model (LLM) architecture using SMILES strings for robust chemical representation and convenient data augmentation through SMILES enumeration. By adapting the pretrained model with an extended layer integrating a comprehensive set of physicochemical and biochemical features, including polymer thickness, water contact angle, and surface charge as well as protein isoelectric point (pI) and size, the BB-EIT showed state-of-the-art performance and strong generalizability. The model accurately predicted the adsorption behavior in previously unseen polymer and protein systems. This work represents an important step toward the data-driven design of biomaterials with tailored protein adsorption properties.
