Drug3D-Net

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A Spatial-temporal Gated Attention Module for Molecular Property Prediction Based on Molecular Geometry

Drug3D-Net 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

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# Drug3D-Net
A Spatial-temporal Gated Attention Module for Molecular Property Prediction Based on Molecular Geometry. This is the official code implementation of Drug3D-Net paper. But the algorithm has been optimized and improved, which is slightly different from the original version.

Requirements 
> Linux (We only tested on Ubuntu-16.04) 
> Keras (version == 2.3.1) 
> Python (version == 3.6.8) 
> tensorflow (version == 1.15.0) 
> matplotlib (version == 3.3.2) 
> numpy (version == 1.19.4) 
> scikit-learn (version == 0.23.2) 
> scipy (version == 1.5.4) 
> pandas (version ==1.1.5)

DataSets 
> esol_v2.csv 
> FreeSolv_SAMPL.csv 
> HIV.csv 
> tox21.csv

PreprocessData 
> grid3Dmols_delaney 
> grid3Dmols_freesolv 
> grid3Dmols_hiv 
> tox21 
>> grid3Dmols_tox21_NR_AhR 
>> grid3Dmols_tox21_NR-AR 
>> grid3Dmols_tox21_NR-AR-LBD 
>> grid3Dmols_tox21_NR-Aromatase 
>> grid3Dmols_tox21_NR-ER 
>> grid3Dmols_tox21_NR-ER-LBD 
>> grid3Dmols_tox21_NR-PPAR-gamma 
>> grid3Dmols_tox21_SR-ARE 
>> grid3Dmols_tox21_SR-ATAD5 
>> grid3Dmols_tox21_SR-HSE 
>> grid3Dmols_tox21_SR-MMP 
>> grid3Dmols_tox21_SR-p53

SaveModel (Take the HIV dataset as an example) 
> 6-0.979.hdf5 
> best_weight.hdf5 
> events.out.tfevents.1608729525.lab406 
> hyper.csv 
> raw_results.csv

Drug3D-Net

Drug3D-Net 최신버젼 다운로드

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Drug3D-Net

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