Machine Learning of Disease Biomarkers from B and T cell Receptor Repertoires

• Project/Area Number: 23K28188
• Project/Area Number (Other): 23H03498 (2023)
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Multi-year Fund (2024); Single-year Grants (2023)
• Section: 一般
• Review Section: Basic Section 62010:Life, health and medical informatics-related
• Research Institution: Osaka University
• Principal Investigator: Standley Daron 大阪大学, 微生物病研究所, 教授 (00448028)
• Project Period (FY): 2023-04-01 – 2026-03-31
• Project Status: Granted (Fiscal Year 2024)
• Budget Amount: ¥18,720,000 (Direct Cost: ¥14,400,000、Indirect Cost: ¥4,320,000); Fiscal Year 2025: ¥5,980,000 (Direct Cost: ¥4,600,000、Indirect Cost: ¥1,380,000); Fiscal Year 2024: ¥6,110,000 (Direct Cost: ¥4,700,000、Indirect Cost: ¥1,410,000); Fiscal Year 2023: ¥6,630,000 (Direct Cost: ¥5,100,000、Indirect Cost: ¥1,530,000)
• Keywords: immunology / repertoire / machine learning / diagnosis / adaptive immune receptor

Outline of Research at the Start

Our goal is to develop a novel liquid biopsy that can be applied to a wide range of diseases. The challenge addressed by our method is the fact that no two donors share more than approximately 6% of the BCRs or TCRs in a typical blood sample. With paratope network features we can double the sharing.