Alternative Neural Network Training Methods
IEEE Expert: Intelligent Systems and Their Applications
Evolutionary Computation: Toward a New Philosophy of Machine Intelligence (IEEE Press Series on Computational Intelligence)
High-Throughput Ligand Screening via Preclustering and Evolved Neural Networks
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Computational Intelligence in Bioinformatics
Computational Intelligence in Bioinformatics
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Linear and nonlinear quantitative structure-activity relationship (QSAR) models and docking score functions were developed for dihydrofolate reductase (DHFR) inhibition by cycloguanil derivatives using small molecule descriptors derived from MOE and in silico docking energies. The best QSAR models and docking score functions were identified when using artificial neural networks optimized by evolutionary computation. The resulting models can be used to identify key descriptors for DHFR inhibition and are useful for high-throughput screening of novel drug compounds.