GitHub - tarsri/antihyperglycemia_Thaiherbs: Srisongkram, Tarapong, Sasisom Waithong, Thaweesak Thitimetharoch, and Natthida Weerapreeyakul. 2022. "Machine Learning and In Vitro Chemical Screening of Potential α-Amylase and α-Glucosidase Inhibitors from Thai Indigenous Plants" Nutrients 14, no. 2: 267.

This repository contains data and source code used in the paper

Machine Learning and In Vitro Chemical Screening of Potential α-Amylase and α-Glucosidase Inhibitors from Thai Indigenous Plants

Tarapong Srisongkram, Sasisom Waithong, Thaweesak Thitimetharoch, Natthida Weerapreeyakul
Corresponding author: TS ([email protected])
Nutrients 14, no. 2: 267. https://doi.org/10.3390/nu14020267

If you find this source codes helpful, please cite us at

Srisongkram, Tarapong, Sasisom Waithong, Thaweesak Thitimetharoch, and Natthida Weerapreeyakul. 2022. "Machine Learning and In Vitro Chemical Screening of Potential α-Amylase and α-Glucosidase Inhibitors from Thai Indigenous Plants" Nutrients 14, no. 2: 267. https://doi.org/10.3390/nu14020267

Name		Name	Last commit message	Last commit date
Latest commit History 7 Commits
Classification_Amylase.ipynb		Classification_Amylase.ipynb
Classification_Glucosidase.ipynb		Classification_Glucosidase.ipynb
Clustering.ipynb		Clustering.ipynb
Correlation_analysis_antiglycosidic-Sig-CategoryIC50.ipynb		Correlation_analysis_antiglycosidic-Sig-CategoryIC50.ipynb
Correlation_analysis_antiglycosidic-Sig.ipynb		Correlation_analysis_antiglycosidic-Sig.ipynb
Correlation_analysis_antiglycosidic.ipynb		Correlation_analysis_antiglycosidic.ipynb
Emax_all.csv		Emax_all.csv
Emax_all_rename.csv		Emax_all_rename.csv
IC50_amylase.csv		IC50_amylase.csv
IC50_amylase_rename.csv		IC50_amylase_rename.csv
IC50_glucosidase.csv		IC50_glucosidase.csv
IC50_glucosidase_rename.csv		IC50_glucosidase_rename.csv
Network_Amylase.ipynb		Network_Amylase.ipynb
Network_Emax_Dunnet.ipynb		Network_Emax_Dunnet.ipynb
Network_antihyperglycemia.ipynb		Network_antihyperglycemia.ipynb
PCA.ipynb		PCA.ipynb
PCA_RF.ipynb		PCA_RF.ipynb
PCA_plotpy.ipynb		PCA_plotpy.ipynb
PLS-DA.ipynb		PLS-DA.ipynb
Phytocomponent.ipynb		Phytocomponent.ipynb
README.md		README.md
Random forest.ipynb		Random forest.ipynb
Res_pearson.csv		Res_pearson.csv
Res_pearson_cat.csv		Res_pearson_cat.csv
Res_pearson_pval.csv		Res_pearson_pval.csv
Res_pearson_pval_cat.csv		Res_pearson_pval_cat.csv
Res_pearson_samples.csv		Res_pearson_samples.csv
Res_pearson_samples_pval.csv		Res_pearson_samples_pval.csv
Res_pearson_sig.csv		Res_pearson_sig.csv
Res_pearson_sig_cat.csv		Res_pearson_sig_cat.csv
Res_pearson_sig_new_sampe.csv		Res_pearson_sig_new_sampe.csv
Res_pearson_sig_samples.csv		Res_pearson_sig_samples.csv
Result_Emax_amylase_posthoc.csv		Result_Emax_amylase_posthoc.csv
Result_Emax_amylase_posthoc_dunn.csv		Result_Emax_amylase_posthoc_dunn.csv
Result_Emax_amylase_posthoc_text_separate.csv		Result_Emax_amylase_posthoc_text_separate.csv
Result_Emax_glucosidase_posthoc.csv		Result_Emax_glucosidase_posthoc.csv
Result_Emax_glucosidase_posthoc_dunn.csv		Result_Emax_glucosidase_posthoc_dunn.csv
Result_IC50_amlyase_posthoc_dunn.csv		Result_IC50_amlyase_posthoc_dunn.csv
Result_IC50_amylase_posthoc_dunn.csv		Result_IC50_amylase_posthoc_dunn.csv
Result_IC50_glucosidase_posthoc_dunn.csv		Result_IC50_glucosidase_posthoc_dunn.csv
Sample_correlation-Copy1.ipynb		Sample_correlation-Copy1.ipynb
Sample_correlation_IC.ipynb		Sample_correlation_IC.ipynb
Single outcome classfication.ipynb		Single outcome classfication.ipynb
Stat_analysis.ipynb		Stat_analysis.ipynb
Supervised clustering.ipynb		Supervised clustering.ipynb
antihyperglycemia.csv		antihyperglycemia.csv
antihyperglycemia_rename.csv		antihyperglycemia_rename.csv
data_preparation_for_stat.ipynb		data_preparation_for_stat.ipynb
df_bioactivities.csv		df_bioactivities.csv
df_clean.csv		df_clean.csv
df_clean_class.csv		df_clean_class.csv
df_clean_class_number.csv		df_clean_class_number.csv
df_pca_PC.csv		df_pca_PC.csv
df_pca_loading.csv		df_pca_loading.csv
df_topfeat.csv		df_topfeat.csv
df_transpore.csv		df_transpore.csv
notebook_file.ipynb		notebook_file.ipynb
plsda-glucosidase.csv		plsda-glucosidase.csv

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This repository contains data and source code used in the paper

Machine Learning and In Vitro Chemical Screening of Potential α-Amylase and α-Glucosidase Inhibitors from Thai Indigenous Plants

If you find this source codes helpful, please cite us at

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This repository contains data and source code used in the paper

Machine Learning and In Vitro Chemical Screening of Potential α-Amylase and α-Glucosidase Inhibitors from Thai Indigenous Plants

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