2021 Fiscal Year Final Research Report
Development on molecular data science for biomolecule dynamical systems
| Project/Area Number |
17H02940
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (B)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
Biological physics/Chemical physics/Soft matter physics
|
|---|
| Research Institution | Hokkaido University |
|---|
Principal Investigator |
|
|---|
| Project Period (FY) |
2017-04-01 – 2020-03-31
|
| Keywords | 1分子計測 / 1分子イメージング / 機械学習 / 因果推論 / 強化学習 / ラマン計測 / 情報計測 / 自由エネルギー地形 |
|---|
| Outline of Final Research Achievements |
With the progress of single-molecule measurement and single-cell spectroscopic imaging, a huge amount of data in complex environments such as cells has been accumulated. "How can we correctly extract the underlying molecular mechanism of action from those data?" was an urgent unsolved issue. From the observed single molecule measurement data and imaging data, by taking into account bleaching effect of dye molecules and low signal to noise ratio, we have developed a series of data scientific framework that extracts the underlying energy landscape, classifies the cell states, and accelerate Raman diagnosis with guaranteeing the accuracy of the diagnosis. In addition, we have newly developed an information science analysis method to identify the interaction region and the aspect of many-body interaction from cell tracking data.
|
| Free Research Field |
生物物理
|
| Academic Significance and Societal Importance of the Research Achievements |
物理学の多くは背後の基本方程式の存在を前提とするところから出発するが、細胞などの複雑系を取り扱う場合にその前提は困難となる。本研究課題では、色素分子の退色や低いシグナルノイズ比など計測原理に基づくデータ駆動科学を新規に展開することに成功した。本研究の社会的意義としては、計測科学と情報科学を融合させることで、これまで細胞・組織形態情報を指標にされてきた細胞診断に対し、分子環境を加味した新たな診断に繋がり、形態異常が顕在化する前の超早期診断の可能性を拓くものである。
|
