| Autor: |
Feng, Ruiwei, Xie, Yufeng, Lai, Minshan, Chen, Danny Z., Cao, Ji, Wu, Jian |
| Rok vydání: |
2021 |
| Předmět: |
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| Druh dokumentu: |
Working Paper |
| DOI: |
10.1109/BIBM52615.2021.9669314 |
| Popis: |
Accurate drug response prediction (DRP) is a crucial yet challenging task in precision medicine. This paper presents a novel Attention-Guided Multi-omics Integration (AGMI) approach for DRP, which first constructs a Multi-edge Graph (MeG) for each cell line, and then aggregates multi-omics features to predict drug response using a novel structure, called Graph edge-aware Network (GeNet). For the first time, our AGMI approach explores gene constraint based multi-omics integration for DRP with the whole-genome using GNNs. Empirical experiments on the CCLE and GDSC datasets show that our AGMI largely outperforms state-of-the-art DRP methods by 8.3%--34.2% on four metrics. Our data and code are available at https://github.com/yivan-WYYGDSG/AGMI. |
| Databáze: |
arXiv |
| Externí odkaz: |
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