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Chemical imaging analysis holds great potential in probing the chemical heterogeneity of samples with high spatial resolution and molecular specificity. This paper demonstrates the implementation of(More)
The use of numerous descriptors that are indicative of molecular structure is becoming common in quantitative structure-activity relationship (QSAR) studies. As all of the descriptors might carry(More)
In the current work, we employed optimized block-wise variable combination (OBVC) by particle swarm optimization (PSO) based on partial least squares (PLS) modeling for variable combination and(More)
Multilayer feedforward neural networks (MLFNNs) are important modeling techniques widely used in QSAR studies for their ability to represent nonlinear relationships between descriptors and activity.(More)