Prop3D: A flexible, Python-based platform for machine learning with protein structural properties and biophysical data - Draizen, Eli J.; Readey, John; Mura, Cameron; Bourne, Philip E. (BMC bioinformatics, 2024)
Keywords: Accessibility; Algorithms; Analysis; Bioinformatics; Biomedical and Life Sciences; Cloud computing; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Data integrity; Datasets; Deep learning; Electrostatic properties; Electrostatics; Evaluation; Evolution; Kinases; Learning algorithms; Life Sciences; Machine learning; Massively parallel workflows; Microarrays; Phylogeny; Pipelines; Prediction models; Protein structure; Proteins; Software; Structural bioinformatics; Structure-function relationships; Three-dimensional display systems; Workflow; United States; Deep learning; Structural bioinformatics; Protein structure; Machine learning; Massively parallel workflows