2022 Fiscal Year Research-status Report
Machine Learning for Structure-Rich Data-Scarce Domains
| Project/Area Number |
22K12150
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| Research Institution | Kyoto University |
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Principal Investigator |
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| Project Period (FY) |
2022-04-01 – 2025-03-31
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| Keywords | Graph neural networks / machine learning |
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| Outline of Annual Research Achievements |
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.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
We have found some small but novel methods for particular problem of learning representations of two drugs in its special context.
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| Strategy for Future Research Activity |
We continue to investigate learning problem with small data by leveraging information from other source to learn reliably.
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| Causes of Carryover |
Due to corona visus pandemic, we have not proceed to use all the cost yet.
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Research Products
(2 results)
