Statistical potential
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- PROTEIN SECONDARY STRUCTURE PREDICTION USING DEEP CONVOLUTIONAL NEURAL FIELDS Sheng Wang*,1,2, Jian Peng3, Jianzhu Ma1, and Jinbo Xu*,1
- Voromqa: Assessment of Protein Structure Quality Using Interatomic Contact Areas Kliment Olechnovicˇ1,2 and Ceslovas Venclovas1*
- Energy-Based Models for Atomic-Resolution Protein Conformations
- Approach of MODELLER for Protein Homology Modeling
- 1 Tfold-TR: Combining Deep Learning Enhanced Hybrid Potential Energy
- Statistical Computation for Problems in Dynamic Systems and Protein Folding
- In Silico Structure Modeling and Characterization of Hypothetical
- Distance-Based Protein Folding Powered by Deep Learning
- Bayesian Statistical Approach for Protein Residue-Residue Contact Prediction
- A Position-Specific Statistical Potential for Protein Structure and Functional
- Accurate Prediction of Protein Torsion Angles Using
- A Deep-Learning Approach to Contact-Driven Protein
- De Novo Protein Folding Using Statistical Potentials from Deep Learning Group 043 / A7D / Alphafold
- 1 Macromolecular Modeling and Design in Rosetta
- An Introduction to Biomolecular Simulations and Docking
- An Analysis and Evaluation of the Wefold Collaborative for Protein
- Protein Structure Prediction from Primary Sequence
- Statistical and Machine Learning Approaches to Predicting Protein-Ligand Interactions