GraphDTA
Drug affinity predictor
Predicts drug-target binding affinity using graph neural networks
GraphDTA: Predicting drug-target binding affinity with graph neural networks
230 stars
4 watching
78 forks
Language: Python
last commit: over 5 years agoLinked from 1 awesome list
xnuohz/awesome-drug-discoveryRelated projects:
| Repository | Description | Stars |
|---|---|---|
 hkmztrk/deepdta | A system that predicts drug-target binding affinity using convolutional neural networks and protein sequences. | 228 |
 lehgtrung/egfr-att | A deep learning framework for predicting drug effects based on multi-input data using an attention mechanism. | 20 |
 shen-lab/deepaffinity | A deep learning framework for predicting protein-compound affinity from molecular sequences and structures | 137 |
 bjoux2/deepdtis_dbn | A Python framework for deep learning-based drug-target interaction prediction using a DBN architecture. | 49 |
 fangpingwan/neodti | A deep learning framework for predicting new drug-target interactions by integrating neighbor information from heterogeneous networks | 75 |
 gist-csbl/deepconv-dti | A Python script for training and testing deep learning models to predict drug-target interactions | 73 |
 luoyunan/dtinet | A computational pipeline to predict novel drug-target interactions from heterogeneous networks | 175 |
 masashitsubaki/cpi_prediction | CPI prediction tool using graph neural networks and convolutional neural networks | 159 |
 zjulearning/graph_level_drug_discovery | A Python project that uses machine learning to improve the representation of molecules in drug discovery | 60 |
 jaechanglim/gnn_dti | This project implements a deep learning approach to predicting docking affinities for molecules with proteins | 66 |
 lishuya17/monn | A framework for predicting pairwise non-covalent interactions and binding affinities between compounds and proteins using machine learning | 100 |
 dougsm/ggcnn | A deep learning-based system for generating precise grasp poses for robots in real-time | 525 |
 atomistic-machine-learning/dtnn | An open-source Python framework for developing machine learning models to predict quantum-mechanical observables of molecular systems. | 78 |
 inoue0426/drgat | This implementation uses Graph Attention Networks to predict drug response based on genetic influences in heterogeneous networks. | 3 |
 benedekrozemberczki/appnp | A PyTorch implementation of a graph neural network model that learns personalized node representations | 367 |