DeepDTIs_DBN
Drug predictor
A Python framework for deep learning-based drug-target interaction prediction using a DBN architecture.
Deep learning-based drug-target interaction prediction / Deep belief net (DBN) based on Theano
49 stars
8 watching
21 forks
Language: Python
last commit: almost 6 years ago
Linked from 1 awesome list
xnuohz/awesome-drug-discoveryRelated projects:
| Repository | Description | Stars |
|---|---|---|
 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 |
 atomistic-machine-learning/dtnn | An open-source Python framework for developing machine learning models to predict quantum-mechanical observables of molecular systems. | 78 |
 simonfqy/padme | A deep learning-based framework for predicting drug-target interaction from protein descriptors | 42 |
 hkmztrk/deepdta | A system that predicts drug-target binding affinity using convolutional neural networks and protein sequences. | 228 |
 luoyunan/dtinet | A computational pipeline to predict novel drug-target interactions from heterogeneous networks | 175 |
 jaechanglim/gnn_dti | This project implements a deep learning approach to predicting docking affinities for molecules with proteins | 66 |
 shen-lab/deepaffinity | A deep learning framework for predicting protein-compound affinity from molecular sequences and structures | 137 |
 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 | 988 |
 lehgtrung/egfr-att | A deep learning framework for predicting drug effects based on multi-input data using an attention mechanism. | 20 |
 astrazeneca/chemicalx | A deep learning library for predicting the effects of combining two drugs | 719 |
 thinng/graphdta | Predicts drug-target binding affinity using graph neural networks | 230 |
 lishuya17/monn | A framework for predicting pairwise non-covalent interactions and binding affinities between compounds and proteins using machine learning | 100 |
 paularindam/chemixnet | A neural network architecture for predicting chemical properties using multiple molecular representations. | 1 |