Highly massive parallel evolutionary computation for designing artificial genetic circuits and microbe networks

2020 Fiscal Year Final Research Report

• Project/Area Number: 17H01796
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Single-year Grants
• Section: 一般
• Research Field: Soft computing
• Research Institution: Tokyo Institute of Technology
• Principal Investigator: Yamamura Masayuki 東京工業大学, 情報理工学院, 教授 (00220442)
• Project Period (FY): 2017-04-01 – 2020-03-31
• Keywords: ウェットGA / 行動並列進化計算 / 人工遺伝子回路 / 微生物ネットワーク / 合成生物学

Outline of Final Research Achievements

Based on our Wet GA experience, we tried to establish a design principle for i) artificial genetic circuits in synthetic biology, and ii) ecological networks of micro- organisms. As a result, we published papers in i) cascading artificial genetic circuits for large scale synthetic biology systems, ii) modeling, analysis, design and controlling microbial ecological systems, and iii) improvements for deep learning method. Especially, we expect more development in ii) modeling, analysis, design and controlling microbial ecological systems, which is novel as a target and methodology and has wide application field such as agriculture and environmental science.

Free Research Field

システム生命科学

Academic Significance and Societal Importance of the Research Achievements

微生物生態系は、腸内細菌叢や皮膚常在菌のように人間生活を支える存在として最近注目を集めている。農業や環境保全でも微生物生態系は重要な役割を果たしている。本研究では、これまで生物にヒントを得てさまざまな計算手法を開発してきた経験を活かし、多摩川および中房温泉でのフィールド実験で得られたデータに基づいて、微生物生態系の構成原理や人為的介入手段の開発に役立つ基礎的知見得た。