Applying support-vector machine learning algorithms toward predicting host-guest interactions with cucurbit[7]uril

Keyphrases

• Cucurbits 100%
• Host-guest Interaction 100%
• Support Vector Machine Learning Algorithm 100%
• Selumetinib 66%
• Machine Learning 33%
• Small Molecules 33%
• Supramolecular Chemistry 33%
• Glioma 16%
• Depot 16%
• Drug Delivery System 16%
• Machine Learning Approach 16%
• Chemical Technology 16%
• Density Functional Calculations 16%
• Predictive Ability 16%
• Training Data 16%
• Macrocycles 16%
• Equilibrium Binding 16%
• Systems Chemistry 16%
• Support Vector Machine Learning 16%
• Binding Coefficient 16%
• Tunable Release 16%
• Mass Transfer Simulation 16%
• Stronger Binding 16%
• Kernel-based 16%

Chemistry

• Host-Guest Interaction 100%
• Cucurbit[7]uril 100%
• Selumetinib 100%
• Cucurbit[8]uril 50%
• Supramolecular Chemistry 50%
• Macrocycle 25%
• Hydrogel 25%
• Scanning Voltage Microscopy 25%
• Density Functional Theory 25%
• Drug Delivery System 25%