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Python framework for connecting molecular dynamics and experimental datasets with the power of machine learning.

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instcheck-vsp-compute-33-diagnostics
instcheck-vsp-compute-33-diagnostics
 
 
LandmarkNystroem.py
LandmarkNystroem.py
 
 
PDB_Order_Fixer.py
PDB_Order_Fixer.py
 
 
PDB_Order_Fixer2.py
PDB_Order_Fixer2.py
 
 
README.md
README.md
 
 
ROC_curve.R
ROC_curve.R
 
 
Rplots.pdf
Rplots.pdf
 
 
TLR8.ipynb
TLR8.ipynb
 
 
Untitled.ipynb
Untitled.ipynb
 
 
Untitled1.ipynb
Untitled1.ipynb
 
 
adrenergic_datasets.ipynb
adrenergic_datasets.ipynb
 
 
adrenergic_prediction.ipynb
adrenergic_prediction.ipynb
 
 
align_in_directory.py
align_in_directory.py
 
 
amir_experiment.ipynb
amir_experiment.ipynb
 
 
analysis.R
analysis.R
 
 
analysis.py
analysis.py
 
 
analyze_tica_performance.R
analyze_tica_performance.R
 
 
aromatic_featurizer.py
aromatic_featurizer.py
 
 
auto_reimage.in
auto_reimage.in
 
 
b1ar_analysis-sparse.ipynb
b1ar_analysis-sparse.ipynb
 
 
b1ar_bias_analysis-tICs_3_5.ipynb
b1ar_bias_analysis-tICs_3_5.ipynb
 
 
b1ar_docking.ipynb
b1ar_docking.ipynb
 
 
b1ar_feature_types
b1ar_feature_types
 
 
b1ar_feature_types.py
b1ar_feature_types.py
 
 
b1ar_tica_config.py
b1ar_tica_config.py
 
 
b2ar_analysis.R
b2ar_analysis.R
 
 
b2ar_analysis.py
b2ar_analysis.py
 
 
b2ar_anton.py
b2ar_anton.py
 
 
b2ar_bias_analysis-Copy1.ipynb
b2ar_bias_analysis-Copy1.ipynb
 
 
b2ar_bias_analysis-Copy2.ipynb
b2ar_bias_analysis-Copy2.ipynb
 
 
b2ar_bias_analysis-Copy3.ipynb
b2ar_bias_analysis-Copy3.ipynb
 
 
b2ar_bias_analysis-Copy4.ipynb
b2ar_bias_analysis-Copy4.ipynb
 
 
b2ar_bias_analysis-HTBC-Analysis.ipynb
b2ar_bias_analysis-HTBC-Analysis.ipynb
 
 
b2ar_bias_analysis-HTBC.ipynb
b2ar_bias_analysis-HTBC.ipynb
 
 
b2ar_bias_analysis-all_tICs.ipynb
b2ar_bias_analysis-all_tICs.ipynb
 
 
b2ar_bias_analysis-short.ipynb
b2ar_bias_analysis-short.ipynb
 
 
b2ar_bias_analysis-tICs_10.ipynb
b2ar_bias_analysis-tICs_10.ipynb
 
 
b2ar_bias_analysis-tICs_1_2.ipynb
b2ar_bias_analysis-tICs_1_2.ipynb
 
 
b2ar_bias_analysis-tICs_1_2_3-Copy1.ipynb
b2ar_bias_analysis-tICs_1_2_3-Copy1.ipynb
 
 
b2ar_bias_analysis-tICs_1_2_3-r2.ipynb
b2ar_bias_analysis-tICs_1_2_3-r2.ipynb
 
 
b2ar_bias_analysis-tICs_1_2_3.ipynb
b2ar_bias_analysis-tICs_1_2_3.ipynb
 
 
b2ar_bias_analysis-tICs_1_2_3_4.ipynb
b2ar_bias_analysis-tICs_1_2_3_4.ipynb
 
 
b2ar_bias_analysis.ipynb
b2ar_bias_analysis.ipynb
 
 
b2ar_exacycle.py
b2ar_exacycle.py
 
 
b2ar_feature_types.py
b2ar_feature_types.py
 
 
b2ar_gprot_analysis.py
b2ar_gprot_analysis.py
 
 
b2ar_gprot_feature_types.py
b2ar_gprot_feature_types.py
 
 
b2ar_gprot_ktica_config.py
b2ar_gprot_ktica_config.py
 
 
b2ar_gprot_tica_config.py
b2ar_gprot_tica_config.py
 
 
b2ar_ktica_config.py
b2ar_ktica_config.py
 
 
b2ar_salmeterol-analysis.ipynb
b2ar_salmeterol-analysis.ipynb
 
 
b2ar_salmeterol-analysis2.ipynb
b2ar_salmeterol-analysis2.ipynb
 
 
b2ar_tica_config.py
b2ar_tica_config.py
 
 
backup_subsample3.py
backup_subsample3.py
 
 
beta1_adrenergic_models.ipynb
beta1_adrenergic_models.ipynb
 
 
beta2_adrenergic_models.ipynb
beta2_adrenergic_models.ipynb
 
 
cannabinoid_docking_tutorial.ipynb
cannabinoid_docking_tutorial.ipynb
 
 
check_docking_results.R
check_docking_results.R
 
 
check_pkg.py
check_pkg.py
 
 
cluster.py
cluster.py
 
 
color_obj.py
color_obj.py
 
 
colormap_docking.R
colormap_docking.R
 
 
conversions.py
conversions.py
 
 
convert_mae.py
convert_mae.py
 
 
cpptraj.log
cpptraj.log
 
 
custom_clusterer.py
custom_clusterer.py
 
 
custom_featurizer.py
custom_featurizer.py
 
 
custom_featurizer_anton.py
custom_featurizer_anton.py
 
 
custom_msm.py
custom_msm.py
 
 
custom_tica.py
custom_tica.py
 
 
detect_intermediates.py
detect_intermediates.py
 
 
dock_subjobs.py
dock_subjobs.py
 
 
docking_analysis.py
docking_analysis.py
 
 
dt.dot
dt.dot
 
 
efficacy_analysis.py
efficacy_analysis.py
 
 
efficacy_scripts.py
efficacy_scripts.py
 
 
enrichment_clusters_vs_samples.R
enrichment_clusters_vs_samples.R
 
 
enrichment_vs_n.R
enrichment_vs_n.R
 
 
enrichment_vs_n_anton_data_exacycle_criteria.R
enrichment_vs_n_anton_data_exacycle_criteria.R
 
 
enrichment_vs_n_anton_data_exacycle_criteria_clusters.R
enrichment_vs_n_anton_data_exacycle_criteria_clusters.R
 
 
enrichment_vs_n_anton_data_exacycle_criteria_samples.R
enrichment_vs_n_anton_data_exacycle_criteria_samples.R
 
 
enrichment_vs_n_anton_data_exacycle_criteria_samples2.R
enrichment_vs_n_anton_data_exacycle_criteria_samples2.R
 
 
enrichment_vs_n_exacycle_data_exacycle_criteria_samples2.R
enrichment_vs_n_exacycle_data_exacycle_criteria_samples2.R
 
 
entropy_estimators.py
entropy_estimators.py
 
 
extra_code.txt
extra_code.txt
 
 
feature_types.py
feature_types.py
 
 
find_states.py
find_states.py
 
 
general_reimage.py
general_reimage.py
 
 
generate_grids.py
generate_grids.py
 
 
get_variable_names.py
get_variable_names.py
 
 
glide_test.py
glide_test.py
 
 
grids.py
grids.py
 
 
instcheck-vsp-compute-33-diagnostics.summary
instcheck-vsp-compute-33-diagnostics.summary
 
 
instcheck-vsp-compute-33-diagnostics.zip
instcheck-vsp-compute-33-diagnostics.zip
 
 
instcheck_results.json
instcheck_results.json
 
 
interpret_tICs.py
interpret_tICs.py
 
 
io_functions.py
io_functions.py
 
 
jointplot-d3.py
jointplot-d3.py
 
 
jointplot_d3.py
jointplot_d3.py
 
 

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Python framework for connecting molecular dynamics and experimental datasets with the power of machine learning.

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