zhiqiangzhongddu / KDD2023_KaGML_DrugDiscovery_Tutorial
Materials for KDD2023 tutorial: Knowledge-augmented Graph Machine Learning for Drug Discovery: from Precision to Interpretability
☆21Updated last year
Alternatives and similar repositories for KDD2023_KaGML_DrugDiscovery_Tutorial:
Users that are interested in KDD2023_KaGML_DrugDiscovery_Tutorial are comparing it to the libraries listed below
- Recent application of graph neural network in drug discovery☆10Updated 5 years ago
- ☆14Updated 3 years ago
- Implementation of GEFA: Early Fusion Approach in Drug-Target Affinity Prediction☆20Updated 4 years ago
- coming soon☆28Updated last year
- Official Implementation of Expressivity and Generalization: Fragment-Biases for Molecular GNNs☆19Updated 5 months ago
- Comparing graph representations for molecular features prediction☆24Updated last year
- EdgeSHAPer: Bond-Centric Shapley Value-Based Explanation Method for Graph Neural Networks☆26Updated last year
- Source codes for 'A baseline for reliable molecular prediction models via Bayesian learning'☆28Updated 4 years ago
- Code for "HiGNN: A Hierarchical Informative Graph Neural Network for Molecular Property Prediction Equipped with Feature-Wise Attention"☆48Updated 2 years ago
- Deep Generative Models for Drug Combination (Graph Set) Generation given Hierarchical Disease Network Embedding☆30Updated 2 years ago
- An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming (ICML'21)☆51Updated 3 years ago
- An E(3) Equivariant Variational Autoencoder for Molecular Linker Design☆47Updated 2 years ago
- (differentiable) gradient-based optimization on a chemical graph for de novo molecule design/optimization (ICLR 2022)☆28Updated last year
- Molecular Hypergraph Neural Network☆36Updated 9 months ago
- HamidHadipour / Deep-clustering-of-small-molecules-at-large-scale-via-variational-autoencoder-embedding-and-K-means☆16Updated last year
- InterpretableDTIP☆20Updated 6 years ago
- code for Zagidullin et al 2021 "Comparative analysis of molecular fingerprints in prediction of drug combination effects"☆16Updated 2 years ago
- Autoregressive fragment-based diffusion for target-aware ligand design☆29Updated 11 months ago
- Junctional Tree Variational Auto-encoder☆22Updated 5 years ago
- [Bioinformatics 2022] Cross-Modality and Self-Supervised Protein Embedding for Compound-Protein Affinity and Contact Prediction☆15Updated 10 months ago
- ☆17Updated 2 years ago
- ☆21Updated 2 years ago
- Molecule Graph Generation using Graph Convolutional Networks-based Variational Graph AutoEncoders (VGAE) in PyTorch☆23Updated 5 months ago
- Source code accompanying the 'MF-PCBA: Multi-fidelity high-throughput screening benchmarks for drug discovery and machine learning' paper☆25Updated last year
- ☆14Updated 2 years ago
- Official PyTorch implementation of "Molecular Representation Learning via Heterogeneous Motif Graph Neural Networks"☆36Updated 2 years ago
- ☆31Updated 9 months ago
- A Spatial-temporal Gated Attention Module for Molecular Property Prediction Based on Molecular Geometry☆32Updated 4 years ago
- Bi-Level Graph Neural Networks for Drug-Drug Interaction Prediction. ICML 2020 Graph Representation Learning and Beyond (GRL+) Workshop☆29Updated 4 years ago
- A concise and easy-to-customize reimplementation of "ChemProp" (Yang et al, 2019) in PyTorch Geometric.☆22Updated 2 years ago