Quantitative structure-activity machine-learning methods

Due to space restrictions this chapter will not cover in any detail the structure-based or docking methods which we have compared extensively with machine learning methods in the case of PXR. During the chapter we will highlight how our understanding of molecular causes of toxicity has allowed quantitative modeling, how various pharmaceutical companies actively use such computational models and their impact on drug discovery and toxicity-related attrition. 

Artificial Intelligence in Chemistry Chemical Engineering Expert Systems Chemometrics Multivariate View on Chemical Problems Electrostatic Potentials Chemical Applications Environmental Chemistry QSAR Experimental Data Evaluation and Quality Control Fuzzy Methods in Chemistry Infrared Data Correlations with Chemical Structure Infrared Spectra Interpretation by the Characteristic Frequency Approach Machine Learning Techniques in Chemistry NMR Data Correlation with Chemical Structure Protein Modeling Protein Structure Prediction in ID, 2D, and 3D Quality Control, Data Analysis Quantitative Structure-Activity Relationships in Drug Design Quantitative Structure-Property Relationships (QSPR) Shape Analysis Spectroscopic Databases Structure Determination by Computer-based Spectrum Interpretation. 

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