Improving the accuracy of RNA secondary structure prediction by machine learning based on next-generation sequencing data
| Project/Area Number |
16K00404
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Multi-year Fund |
|---|
| Section | 一般 |
|---|
| Research Field |
Life / Health / Medical informatics
|
|---|
| Research Institution | Keio University |
|---|
Principal Investigator |
Sato Kengo 慶應義塾大学, 理工学部(矢上), 講師 (20365472)
|
|---|
| Project Period (FY) |
2016-04-01 – 2020-03-31
|
| Project Status |
Completed (Fiscal Year 2019)
|
| Budget Amount *help |
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2018: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2017: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2016: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
|
|---|
| Keywords | バイオインフォマティクス / RNA二次構造予測 / 機械学習 / NGSデータ |
|---|
| Outline of Final Research Achievements |
We have developed a machine learning algorithm that makes it possible to use secondary structure profiles, which are partial structural information, as weak-level learning data, and aims to improve the accuracy of RNA secondary structure prediction without overfitting by learning a large number of secondary structure models that are more precise than existing methods. First, we developed a more robust and accurate method for RNA secondary structure prediction by integrating the free energy minimization method based on the existing Turner thermodynamic model with the machine learning method using a structured SVM. The results of the computer experiments showed that no overfitting was observed, unlike in the existing methods, and the prediction accuracy was improved.
|
| Academic Significance and Societal Importance of the Research Achievements |
RNA 二次構造予測は古くから研究されているが，長い配列に対する予測精度は未だに十分とは言えない．本研究によりRNA二次構造予測の精度が向上し，生体内におけるRNAの機能を推定する手がかりが得られることが期待される．さらに，RNAウィルスをターゲットとする創薬などに応用することが可能である．
|
Report
(5 results)
Research Products
(15 results)
