Improving Signal and Transit Peptide Predictions Using AlphaFold2-predicted Protein Structures

2023/12/06 by Venkata R. Sanaboyana, Adrian H. Elcock · 1 voice · 1 citation
Biochemistry, Genetics and Molecular Biology · #Machine Learning in Bioinformatics #Protein Structure and Dynamics #RNA and protein synthesis mechanisms

paper · doi:10.1016/j.jmb.2023.168393

openalex publication_date 2023/12/06 · crossref created 2023/12/06 · crossref issued 2024/01/01 · crossref published 2024/01/01 · crossref published-print 2024/01/01 · crossref deposited 2025/02/27 · openalex created_date 2025/10/10 · crossref indexed 2026/04/11 · openalex updated_date 2026/07/31

Citations

• Improved protein structure prediction using predicted interresidue orientations
• UniProt: the universal protein knowledgebase in 2021
• Highly accurate protein structure prediction with AlphaFold
• Highly accurate protein structure prediction for the human proteome
• КОМПЬЮТЕРНАЯ ТОМОГРАФИЯ – ОСНОВА ОПТИМИЗАЦИИ МИНИТОРАКОТОМНОГО ДОСТУПА
• SignalP 6.0 predicts all five types of signal peptides using protein language models
• SignalP 6.0 predicts all five types of signal peptides using protein language models

Cited by

• Exploring the lipoproteome of Parageobacillus thermoglucosidasius

Discussions

• “Improving Signal and Transit Peptide Predictions Using AlphaFold2-predicted Protein Structures” has been published Authors use this to look for signal peptides that could be false positives doi.org [bsky, 4 points, 0 comments]