| 研究課題/領域番号 |
22K12150
|
|---|
| 研究機関 | 京都大学 |
|---|
研究代表者 |
|
|---|
| 研究期間 (年度) |
2022-04-01 – 2025-03-31
|
| キーワード | Graph neural networks / machine learning |
|---|
| 研究実績の概要 |
We are working on the topic of predicting properties of two drugs, formulated as a pair of graphs. Due to its potential high dimensionality and small scale data, we have to leverage more data from different sources to avoid overfitting. The solution is to learn representation of two drugs within a network of drugs, proteins and other biological information.
|
| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
We have found some small but novel methods for particular problem of learning representations of two drugs in its special context.
|
| 今後の研究の推進方策 |
We continue to investigate learning problem with small data by leveraging information from other source to learn reliably.
|
| 次年度使用額が生じた理由 |
Due to corona visus pandemic, we have not proceed to use all the cost yet.
|
