深層学習に基づくメタゲノムデータからの溶菌性ファージ・細菌感染関係予測法の開発

• Project/Area Number: 18K18148
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 62010:Life, health and medical informatics-related
• Research Institution: The University of Tokyo
• Principal Investigator: 木村 恭将 東京大学, 医科学研究所, 特任助教 (30632913)
• Project Period (FY): 2018-04-01 – 2021-03-31
• Project Status: Granted (Fiscal Year 2018)
• Budget Amount: ¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000); Fiscal Year 2020: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000); Fiscal Year 2019: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000); Fiscal Year 2018: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
• Keywords: ウイルス / 細菌 / メタゲノム / モデル化 / バクテリオファージ