Genetic algorithms with QSAR

Li, T Mei, H. and Cong, P. (1999) Combining nonlinear PLS with the numeric genetic algorithm for QSAR. Chemom. Intell. Lab. Syst., 45, 177-184. 

Fig. 5. Representation of a genetic algorithm for the selection of descriptors for a QSAR model. The model is commonly referred to as a gene and is encoded with different descriptors. Two Parents creating two Children is a crossover of genetic information (descriptors). The genes of an individual can mutate, introducing random changes in the model. Crossover and mutation are can occur independent of each other.

In terms of practical application, expert systems overlap with systems for deriving and applying quantitative structure-activity relationship (QSAR) models or equations, and with systems using artificial neural networks (ANN) or genetic algorithms. The expert systems described in this chapter are characterized by their use of a generalized store of knowledge. 

Turner, D.B. and Willett, P. (2000a) Evaluation of the EVA descriptor for QSAR studies. 3. The use of a genetic algorithm to search for models with enhanced predictive properties (EVA GA). 

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