Development of protein interaction prediction methods by modeling protein substructures
| Project/Area Number |
24500361
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Multi-year Fund |
|---|
| Section | 一般 |
|---|
| Research Field |
Bioinformatics/Life informatics
|
|---|
| Research Institution | Kyoto University |
|---|
Principal Investigator |
|
|---|
| Project Period (FY) |
2012-04-01 – 2016-03-31
|
| Project Status |
Completed (Fiscal Year 2015)
|
| Budget Amount *help |
¥5,200,000 (Direct Cost: ¥4,000,000、Indirect Cost: ¥1,200,000)
Fiscal Year 2015: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2014: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2013: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2012: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
|
|---|
| Keywords | 条件付き確率場 / タンパク質RNA複合体 / タンパク質複合体 / SIFT特徴量 / タンパク質相互作用強度 / オンライン学習 / 中央文字列 / 中心文字列 / 整数計画法 / タンパク質立体構造 / SIFT / SURF / カーネル関数 / サポートベクトルマシン / 正則化 / タンパク質RNA相互作用 / 生体生命情報学 / アルゴリズム / タンパク質 / 機械学習 |
|---|
| Outline of Final Research Achievements |
We developed a similarity measure between protein tertiary structures using SIFT local feature descriptor, which is often used in the field of image recognition. The proposed measure outperforms previously developed measures based on image compression. Furthermore, we proposed conditional random field models for predicting residue-base contacts in protein-RNA complexes. In addition, we developed methods for predicting protein heterodimers and heterotrimers in higher accuracy than existing methods.
|
Report
(5 results)
Research Products
(18 results)
