13.2節 創薬
| タイトル | 著者名 | 年 | リンク | 登場順 |
|---|---|---|---|---|
| Convolutional Networks on Graphs for Learning Molecular Fingerprints | Duvenaud et al | 2015 | arxiv | 1 |
| Chemi-net: a graph convolutional network for accurate drug property prediction | Liu et al | 2018a | arxiv | 2 |
| Neural Message Passing for Quantum Chemistry | Gilmer et al | 2017 | arxiv | 3 |
| Protein Interface Prediction using Graph Convolutional Networks | Fout et al | 2017 | リンク | 4 |
| PAIRpred: Partner-specific prediction of interacting residues from sequence and structure | Afsar Minhas et al | 2014 | リンク | 5 |
| GraphDTA: Predicting drug-target binding affinity with graph neural networks | Nguyen et al | 2020 | リンク | 6 |
13.3節 薬物類似性学習
| タイトル | 著者名 | 年 | リンク | 登場順 |
|---|---|---|---|---|
| The SIDER database of drugs and side effects | Kuhn et al | 2016 | リンク | 1 |
| Drug Similarity Integration Through Attentive Multi-view Graph Auto-Encoders | Ma et al | 2018c | arxiv | 2 |
13.4節 ポリファーマシー副作用予測
| タイトル | 著者名 | 年 | リンク | 登場順 |
|---|---|---|---|---|
| Modeling polypharmacy side effects with graph convolutional networks | Zitnik et al | 2018 | arxiv | 1 |
| Modeling Relational Data with Graph Convolutional Networks | Schlichtkrull et al | 2018 | arxiv | 2 |
13.5節 疾病予測
| タイトル | 著者名 | 年 | リンク | 登場順 |
|---|---|---|---|---|
| The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism | Di Martino et al | 2014 | リンク | 1 |
| Disease Prediction using Graph Convolutional Networks: Application to Autism Spectrum Disorder and Alzheimer's Disease | Parisot et al | 2018 | arxiv | 2 |
| Sex differences in autism spectrum disorders | Werling and Geschwind | 2013 | リンク | 3 |
| Brain connectivity in autism | Kana et al | 2014 | リンク | 4 |
13.7節 参考文献
| タイトル | 著者名 | 年 | リンク | 登場順 |
|---|---|---|---|---|
| GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combination | Shang et al | 2019b | arxiv | 1 |
| Pre-training of Graph Augmented Transformers for Medication Recommendation | Shang et al | 2019c | arxiv | 2 |
| Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation | You et al | 2018a | arxiv | 3 |
| Graph Neural Networks with Generated Parameters for Relation Extraction | Zhu et al | 2019b | リンク | 4 |
| Learning the Graphical Structure of Electronic Health Records with Graph Convolutional Transformer | Choi et al | 2020 | arxiv | 5 |
| Graph Convolutional Network and Convolutional Neural Network Based Method for Predicting lncRNA-Disease Associations | Xuan et al | 2019 | リンク | 6 |
| A Novel Computational Model for Predicting microRNA-Disease Associations Based on Heterogeneous Graph Convolutional Networks | Li et al | 2019a | リンク | 7 |