Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Graph neural networks (GNNs) have been shown to be astonishingly capable models for ...
Recent developments of neural network–based atomistic models enable large scale molecular dynamics based on quantum mechanical theory. However, there is still a gap between modeling microscale ...
Molecular geometry modeling is a powerful tool for understanding the intricate relationships between molecular structure and biological activity – a field known as structure-activity relationships ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Predictive modeling of toxicity is a crucial step in the drug discovery pipeline. It ...
Peptide-protein interactions between a smaller or disordered peptide stretch and a folded receptor make up a large part of all protein-protein interactions. A common approach for modeling such ...
Brief: Researchers from the Computing and Computational Sciences Directorate (CCSD) at Oak Ridge National Laboratory (ORNL) have developed a distributed implementation of graph convolutional neural ...
Physical interactions of proteins play key functional roles in many important cellular processes. To understand molecular mechanisms of such functions, it is crucial to determine the structure of ...
GeneValidator helps in identifying problems with gene predictions and provide useful information extracted from analysing orthologs in BLAST databases. The results produced can be used by biocurators ...
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