Publication | Closed Access
Accurate prediction of protein structures and interactions using a three-track neural network
213
Citations
55
References
2022
Year
Structural BioinformaticsBiomolecular Structure PredictionMolecular BiologyProtein FoldingProteomicsMacromolecular AssembliesAccurate PredictionBiophysicsDeep Learning MethodProtein ModelingProtein Structure PredictionBioinformaticsProtein StructuresStructural BiologyAlphafold2 FrameworkProtein BioinformaticsProtein–protein ComplexesThree-track Neural NetworkNatural SciencesComputational BiologySystems BiologyMedicine
Brief summary: This study reveals a Deep Learning method, 'RoseTTA fold', based on DeepMind's Alphafold2 framework, to predict 3-dimensional protein structures from 1-dimensional sequence information and generate models of protein–protein complexes with high accuracy.
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