Contents
- Sunyoung Kwon, Sungroh Yoon: DeepCCI: End-to-end Deep Learning for Chemical-Chemical Interaction Prediction
- Jae Yong Ryu, Hyun Uk Kim, and Yup Lee: Deep Learning Improves Prediction of Drug–Drug and Drug–Food Interactions, Code (kaistsystemsbiology/deepddi)
- Kristina Preuer, Richard Lewis, Sepp Hochreiter, Andreas Bender, Krishna C Bulusu, Günter Klambauer: DeepSynergy: Predicting Anti-Cancer Drug Synergy with Deep Learning, Code (KristinaPreuer/DeepSynergy)
- Nuo Xu, Pinghui Wang, Long Chen, Jing Tao, Junzhou Zhao: MR-GNN: Multi-Resolution and Dual Graph Neural Network for Predicting Structured Entity Interactions, Code
- Andreea Deac, Yu-Hsiang Huang, Petar Veličković, Pietro Liò, Jian Tang: Drug-Drug Adverse Effect Prediction with Graph Co-Attention
- Kexin Huang, Cao Xiao, Trong Nghia Hoang, Lucas M. Glass, Jimeng Sun: CASTER: Predicting Drug Interactions with Chemical Substructure Representation, Code (kexinhuang12345/CASTER)
- Arnold K Nyamabo, Hui Yu, Jian-Yu Shi: SSI–DDI: Substructure–Substructure Interactions for Drug–Drug Interaction Prediction, Code (kanz76/SSI-DD)
- Mengying Sun, Fei Wang, Olivier Elemento, Jiayu Zhou: Structure-Based Drug-Drug Interaction Detection via Expressive Graph Convolutional Networks and Deep Sets
- Tianyu Zhang, Liwei Zhang, Philip Payne, Fuhai Li: Synergistic Drug Combination Prediction by Integrating Multiomics Data in Deep Learning Models
- Xusheng Cao, Rui Fan, Wanwen Zeng: DeepDrug: A General Graph-Based Deep Learning Framework for Drug Relation Prediction, Code (wanwenzeng/deepdrug)
- Xin Chen, Xien Liu, Ji Wuab: GCN-BMP: Investigating Graph Representation Learning for DDI Prediction Task,
- Yue-Hua Feng, Shao-Wu Zhang, Jian-Yu Shi: DPDDI: a Deep Predictor for Drug-Drug Interactions, Code (NWPU-903PR/DPDDI)
- Jinxian Wang, Xuejun Liu, Siyuan Shen, Lei Deng, Hui Liu: DeepDDS: Deep Graph Neural Network with Attention Mechanism to Predict Synergistic Drug Combinations, Code (Sinwang404/DeepDDS)
- Halil Ibrahim Kuru, Oznur Tastan, Ercument Cicek: MatchMaker: A Deep Learning Framework for Drug Synergy Prediction, Code (tastanlab/matchmaker)
- Hui Yu, ShiYu Zhao, JianYu Shi: STNN-DDI: A Substructure-aware Tensor Neural Network to Predict Drug-Drug Interactions, Code (zsy-9/STNN-DDI)
- Jan Eric Lenssen and Matthias Fey: Fast Graph Representation Learning with PyTorch Geometric, Code (pyg-team/pytorch_geometric)
- Minjie Wang, Lingfan Yu, Da Zheng, Quan Gan, Yu Gai, Zihao Ye, Mufei Li, Jinjing Zhou, Qi Huang, Chao Ma, Ziyue Huang, Qipeng Guo, Hao Zhang, Haibin Lin, Junbo Zhao, Jinyang Li, Alexander J. Smola, Zheng Zhang: Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs, Code (dmlc/dgl)
- CSIRO Data 61: StellarGraph Machine Learning Library Code (stellargraph/stellargraph)
- Bharath Ramsundar, Peter Eastman, Patrick Walters, Vijay Pande, Karl Leswing, Zhenqin Wu: Deep Learning for the Life Sciences, Code (deepchem/deepchem)
- Abe Motoki, Mihai Mororiu, Tomoya Otabi, Kenshin Abe: Chainer Chemistry: A Library for Deep Learning in Biology and Chemistry Code (chainer/chainer-chemistry)
- Jonathan Godwin, Thomas Keck, Peter Battaglia, Victor Bapst, Thomas Kipf, Yujia Li, Kimberly Stachenfeld, Petar Velickovic, Alvaro Sanchez-Gonzalez: Jraph: A Library for Graph Neural Networks in Jax Code (deepmind/jraph)
- Daniele Grattarola, Cesare Alippi: Graph Neural Networks in TensorFlow and Keras with Spektral, Code (danielegrattarola/spektral)
- Meng Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Hao Yuan, Shurui Gui, Haiyang Yu, Zhao Xu, Jingtun Zhang, Yi Liu, Keqiang Yan, Haoran Liu, Cong Fu, Bora M Oztekin, Xuan Zhang, Shuiwang Ji: DIG: A Turnkey Library for Diving into Graph Deep Learning Research, Code (divelab/DIG)
- Zhaocheng Zhu, Shengchao Liu, Chence Shi: TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug Discovery
- Yukuo Cen, Zhenyu Hou, Yan Wang, Qibin Chen, Yizhen Luo, Xingcheng Yao, Aohan Zeng, Shiguang Guo, Yang Yang, Peng Zhang, Guohao Dai, Yu Wang, Chang Zhou, Hongxia Yang, Jie Tang: CogDL: An Extensive Toolkit for Deep Learning on Graphs, Code (THUDM/cogdl)
- Jun Hu, Shengsheng Qian, Quan Fang, Youze Wang, Quan Zhao, Huaiwen Zhang, Changsheng Xu: Efficient Graph Deep Learning in TensorFlow with TF Geometric, Code (CrawlScript/tf_geometric)
- Mufei Li, Jinjing Zhou, Jiajing Hu, Wenxuan Fan, Yangkang Zhang, Yaxin Gu, George Karypis: DGL-LifeSci: An Open-Source Toolkit for Deep Learning on Graphs in Life Science, Code (awslabs/dgl-lifesci)