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Performance comparisons of server groups participating in the... | Download Scientific Diagram
PDF) Protein structure prediction using multiple deep neural networks in CASP13
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Frontiers | Deep Learning-Powered Prediction of Human-Virus Protein-Protein Interactions
Figure 6 from Progress from CASP 6 to CASP 7 | Semantic Scholar
Assessment of protein model structure accuracy estimation in CASP13: Challenges in the era of deep learning - Won - 2019 - Proteins: Structure, Function, and Bioinformatics - Wiley Online Library
Topology evaluation of models for difficult targets in the 14th round of the critical assessment of protein structure prediction (CASP14) - Kinch - 2021 - Proteins: Structure, Function, and Bioinformatics - Wiley Online Library
Performance comparisons of server groups participating in the... | Download Scientific Diagram
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Global versus Local Hubs in Human Protein–Protein Interaction Network | Journal of Proteome Research
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1 Protein structure Prediction. 2 Copyright notice Many of the images in this power point presentation are from Bioinformatics and Functional Genomics. - ppt download
Protein tertiary structure modeling driven by deep learning and contact distance prediction in CASP13 | bioRxiv
FALCON2: a web server for high-quality prediction of protein tertiary structures | BMC Bioinformatics | Full Text
The pipeline of MULTICOM server and human prediction systems. | Download Scientific Diagram
An analysis and evaluation of the WeFold collaborative for protein structure prediction and its pipelines in CASP11 and CASP12 | Scientific Reports
Assessment of protein model structure accuracy estimation in CASP14: Old and new challenges - Kwon - 2021 - Proteins: Structure, Function, and Bioinformatics - Wiley Online Library
IJMS | Free Full-Text | Incorporating Machine Learning into Established Bioinformatics Frameworks | HTML
Top groups in CASP9 in terms of the number of models with the highest... | Download Table
CASP9 results compared to those of previous CASP experiments. - Abstract - Europe PMC
ROPIUS0: A deep learning-based protocol for protein structure prediction and model selection and its performance in CASP14 | bioRxiv
AlphaFold2 examples from CASP 14 - Proteopedia, life in 3D
Fast and effective protein model refinement by deep graph neural networks | bioRxiv
TopModel: Template-Based Protein Structure Prediction at Low Sequence Identity Using Top-Down Consensus and Deep Neural Networks | Journal of Chemical Theory and Computation