| Project/Area Number |
22650060
|
|---|
| Research Category |
Grant-in-Aid for Challenging Exploratory Research
|
| Allocation Type | Single-year Grants |
|---|
| Research Field |
Bioinformatics/Life informatics
|
|---|
| Research Institution | Tokyo Institute of Technology (2011)
Ochanomizu University (2010) |
|---|
Principal Investigator |
SESE Jun 東京工業大学, 大学院・情報理工学研究科, 准教授 (40361539)
|
|---|
| Project Period (FY) |
2010 – 2011
|
| Project Status |
Completed (Fiscal Year 2011)
|
| Budget Amount *help |
¥3,390,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥390,000)
Fiscal Year 2011: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2010: ¥1,700,000 (Direct Cost: ¥1,700,000)
|
|---|
| Keywords | 機械学習 / クラスタリング / クラス分類 / 糖鎖 / グリカンアレイ / 組み合わせ / 半教師つきクラスタリング / タンパク質 / 化合物 |
|---|
| Research Abstract |
Although most glycan research has focused on a few interactions between glycans and samples, recent technology has made it possible to observe many glycan-sample interactions at once. Consortium for Functional Glycomics(CFG) has collected data and compiled a database that contains glycan-sample interactions for more than three thousand samples. The large CFG database gives us "birds-eye view" of glycan interactions and the data from this database can be used to generate new hypothesis about interactions between glycans and samples or provide new rules about protein binding sites on glycans. In this work, we investigated the best combination of clustering technique and distance metrics for analyzing the large CFG datasets. We then developed an algorithm to extract glycan sub-structure which interacts target sample by combining the CFG data and glycan structure. The analysis results infer substructures interacting with influenza or galectin.
|
