Initiative for faster and more precise NMR data measurement and analysis with sparse modeling

2017 Fiscal Year Final Research Report

• Project Area: Initiative for High-Dimensional Data-Driven Science through Deepening of Sparse Modeling
• Project/Area Number: 25120003
• Research Category: Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)
• Allocation Type: Single-year Grants
• Review Section: Complex systems
• Research Institution: Institute of Physical and Chemical Research
• Principal Investigator: Kigawa Takanori 国立研究開発法人理化学研究所, 生命システム研究センター, チームリーダー (20270598)
• Co-Investigator(Kenkyū-buntansha): 池谷 鉄兵 首都大学東京, 理工学研究科, 助教 (30457840)
• Co-Investigator(Renkei-kenkyūsha): Kasai Takuma 国立研究開発法人理化学研究所, 生命システム研究センター, 研究員 (70446516)
• Project Period (FY): 2013-06-28 – 2018-03-31
• Keywords: スパースモデリング / NMR / 圧縮センシング / スペクトル解析 / ベイズ統計 / レプリカ交換モンテカルロ法 / テンソル分解 / 安定同位体標識

Outline of Final Research Achievements

In this project, focusing on the sparseness of NMR data and structure information of biomolecule, we have aimed to achieve faster and more precise NMR measurement and analysis of biomolecules by solving the issues arising from complexity and complicatedness of NMR analysis with the sparse modeling. In the subproject 1, we have successfully developed the spectrum reconstruction method with high reproducibility. In the subproject 2, decoding process of “SiCode” was dramatically improved by concurrently deconvoluting spectra and identifying amino-acid assignment. In the subproject 3, the method for faster and more precise biomolecular structure calculation was established by using Bayesian inference, and was successfully applied to de novo structure determination of proteins in living eukaryotic cells. In later introduced subproject 4, we have successfully developed a novel method enabling concurrent signal identification and structural dynamics analysis.

Free Research Field

構造生物学