Improving prediction of secondary structure, local backbone angles and solvent accessible surface area of proteins by iterative deep learning
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Title
Improving prediction of secondary structure, local backbone angles and solvent accessible surface area of proteins by iterative deep learning
Authors
Keywords
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Journal
Scientific Reports
Volume 5, Issue 1, Pages -
Publisher
Springer Nature
Online
2015-06-22
DOI
10.1038/srep11476
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Note: Only part of the references are listed.- Context-Based Features Enhance Protein Secondary Structure Prediction Accuracy
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- Template-based protein structure modeling using TASSERVMT
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- I-TASSER: a unified platform for automated protein structure and function prediction
- (2010) Ambrish Roy et al. Nature Protocols
- Trends in template/fragment-free protein structure prediction
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- Predicting Continuous Local Structure and the Effect of Its Substitution for Secondary Structure in Fragment-Free Protein Structure Prediction
- (2009) Eshel Faraggi et al. STRUCTURE
- Real-value prediction of backbone torsion angles
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- Alternating evolutionary pressure in a genetic algorithm facilitates protein model selection
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