… 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 …

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

… involves the deployment of a deep convolutional neural network (CNN) using Python 3.12.2, …
cell- pathways prediction A molecular pathway association analysis using PathwayMap has …

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

… 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 …

… 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 …

… to associate with various cellular pathways, they were submitted to a pathway map, a
molecular pathway predictor based on self-normalizing neural networks and ECFP4 fingerprints, …

… , 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 …

… Overview of the major molecular pathways associated with COVID-19 pathogenesis and …
factors are associated with SCLC development and activation of signaling pathways such as …