GNN_DTI
Molecular docking predictor
This project implements a deep learning approach to predicting docking affinities for molecules with proteins
66 stars
1 watching
16 forks
Language: Python
last commit: over 4 years ago
Linked from 1 awesome list
xnuohz/awesome-drug-discoveryRelated projects:
| Repository | Description | Stars |
|---|---|---|
 atomistic-machine-learning/dtnn | An open-source Python framework for developing machine learning models to predict quantum-mechanical observables of molecular systems. | 77 |
 gist-csbl/deepconv-dti | A Python script for training and testing deep learning models to predict drug-target interactions | 71 |
 bplaye/nnk_dti | An open-source project evaluating deep learning methods for predicting ligands and drugs in chemogenomics | 3 |
 kexinhuang12345/deeppurpose | A toolkit for molecular modeling and prediction tasks using deep learning | 974 |
 fangpingwan/neodti | A deep learning framework for predicting new drug-target interactions by integrating neighbor information from heterogeneous networks | 74 |
 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. | 48 |
 muhaochen/seq_ppi | A deep learning framework for predicting protein-protein interactions based on sequence data | 89 |
 hkmztrk/deepdta | A system that predicts drug-target binding affinity using convolutional neural networks and protein sequences. | 225 |
 dougsm/ggcnn | A deep learning-based system for generating precise grasp poses for robots in real-time | 514 |
 lishuya17/monn | A framework for predicting pairwise non-covalent interactions and binding affinities between compounds and proteins using machine learning | 100 |
 masashitsubaki/cpi_prediction | CPI prediction tool using graph neural networks and convolutional neural networks | 159 |
 luoyunan/dtinet | A computational pipeline to predict novel drug-target interactions from heterogeneous networks | 174 |
 zjulearning/graph_level_drug_discovery | A Python project that uses machine learning to improve the representation of molecules in drug discovery | 60 |
 lifanchen-simm/transformercpi | Develops a deep learning model to predict compound-protein interactions by leveraging sequence-based learning and self-attention mechanisms | 134 |