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Summary of predictions for Δ G , ln ⁡ K , and log ⁡ K of complex formation with α-CD, arranged in chronological order.
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Summary of predictions for Δ G , ln ⁡ K , and log ⁡ K of complex formation with α-CD, arranged in chronological order.
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Image Search Results


Summary of predictions for Δ G , ln ⁡ K , and log ⁡ K of complex formation with α-CD, arranged in chronological order.

Journal: Molecules

Article Title: A Review of Machine Learning and QSAR/QSPR Predictions for Complexes of Organic Molecules with Cyclodextrins

doi: 10.3390/molecules29133159

Figure Lengend Snippet: Summary of predictions for Δ G , ln ⁡ K , and log ⁡ K of complex formation with α-CD, arranged in chronological order.

Article Snippet: log K , 233 [ ] , 186/47, k-means cluster analysis , derived from electrostatic potentials on the molecular surface , MLR, PLS, SVR, least squares SVR, RF, GPR (ZP-explore in MATLAB) , R 2 train = 0.93, R 2 test = 0.83 Q 2 LOO = 0.76, RMSE test = 2.13 kJ/mol , - , [ ] .

Techniques: Software

Summary of predictions for Δ G , ln ⁡ K , and log ⁡ K of complex formation with β-CD, arranged in chronological order.

Journal: Molecules

Article Title: A Review of Machine Learning and QSAR/QSPR Predictions for Complexes of Organic Molecules with Cyclodextrins

doi: 10.3390/molecules29133159

Figure Lengend Snippet: Summary of predictions for Δ G , ln ⁡ K , and log ⁡ K of complex formation with β-CD, arranged in chronological order.

Article Snippet: log K , 233 [ ] , 186/47, k-means cluster analysis , derived from electrostatic potentials on the molecular surface , MLR, PLS, SVR, least squares SVR, RF, GPR (ZP-explore in MATLAB) , R 2 train = 0.93, R 2 test = 0.83 Q 2 LOO = 0.76, RMSE test = 2.13 kJ/mol , - , [ ] .

Techniques: Software, Derivative Assay, Biomarker Discovery, Activity Assay