… In this work, we describe a deep self-normalizing neural network model for the prediction of
molecular pathway association and evaluate its performance, showing an AUC ranging from …

… Association of molecules with pathways can be addressed with self-normalizing neural
networks. (7) Membrane permeation of drug molecules can also be considered and tackled by …

… The interaction of leads with metabolic pathway was modelled using KEGG and Reactome
database, based on self-normalizing neural networks for the identification of pathway. The …

… -pathway interactions using PathwayMap which is based on self-normalizing neural networks
for pathway … model was used to predict molecule pathway association using KEGG and …

… However, by using a novel molecular graph encoding and convolutional neural network …
deep self-normalizing neural network model for the prediction of molecular pathway association …

… While the main goal of the study is not to evaluate the predictive performance of graph
neural networks compared to other machine-learning models, to assess whether the proposed …

… disease heterogeneity, discovering dysregulated molecular pathways and therapeutic targets,
… SMILES enumeration as data augmentation for neural network modeling of molecules. …

… network perturbations by drug molecules, deep self-normalizing neural-network based
metabolic pathway interaction probability predictions were simulated using the PathwayMap tool (…

… , the molecular structure of the hit against a target (first molecule found to bind … molecules,
particularly the structural derivatives of a hit, largely follow certain structure-activity relationship …

… We have to concede our incomplete understanding of molecular pathology and our inability
… the use of the derivative of the output of the neural network with respect to the input (that is, δf…