نتائج البحث

Quantitative model for genome-wide cyclic AMP receptor protein binding site identification and characteristic analysis

• Authors : Chen, Yigang; Lin, Yang-Chi-Dung; Luo, Yijun

Subjects: Cyclic AMP Receptor Protein; Binding Sites; Escherichia coli Proteins

• Source: Brief Bioinform

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Fuse feeds as one: cross-modal framework for general identification of AMPs.

• Authors : Zhang, Wentao¹ (AUTHOR); Xu, Yanchao¹ (AUTHOR); Wang, Aowen¹ (AUTHOR)

• Source: Briefings in Bioinformatics. Nov2023, Vol. 24 Issue 6, p1-14. 14p.

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iAMP-Attenpred: a novel antimicrobial peptide predictor based on BERT feature extraction method and CNN-BiLSTM-Attention combination model.

• Authors : Xing, Wenxuan¹ (AUTHOR); Zhang, Jie² (AUTHOR); Li, Chen¹ (AUTHOR)

• Source: Briefings in Bioinformatics. Jan2024, Vol. 25 Issue 1, p1-9. 9p.

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Comparative analysis of machine learning algorithms on the microbial strain-specific AMP prediction.

• Authors : Vishnepolsky, Boris¹ (AUTHOR) ; Grigolava, Maya¹ (AUTHOR); Managadze, Grigol¹ (AUTHOR)

• Source: Briefings in Bioinformatics. Jul2022, Vol. 23 Issue 4, p1-11. 11p.

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Diff-AMP: tailored designed antimicrobial peptide framework with all-in-one generation, identification, prediction and optimization.

• Authors : Wang, Rui¹ (AUTHOR); Wang, Tao¹ (AUTHOR); Zhuo, Linlin¹ (AUTHOR)

• Source: Briefings in Bioinformatics. Mar2024, Vol. 25 Issue 2, p1-13. 13p.

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Do deep learning models make a difference in the identification of antimicrobial peptides?

• Authors : García-Jacas, César R¹ (AUTHOR) ; Pinacho-Castellanos, Sergio A^2,3 (AUTHOR); García-González, Luis A² (AUTHOR)

• Source: Briefings in Bioinformatics. May2022, Vol. 23 Issue 3, p1-16. 16p.

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Designing antimicrobial peptides using deep learning and molecular dynamic simulations.

• Authors : Cao, Qiushi^1,2 (AUTHOR); Ge, Cheng^1,2 (AUTHOR); Wang, Xuejie^2,3 (AUTHOR)

• Source: Briefings in Bioinformatics. Mar2023, Vol. 24 Issue 2, p1-13. 13p.

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TP-LMMSG: a peptide prediction graph neural network incorporating flexible amino acid property representation.

• Authors : Chen, Nanjun¹ (AUTHOR); Yu, Jixiang¹ (AUTHOR); Zhe, Liu¹ (AUTHOR)

• Source: Briefings in Bioinformatics. Jul2024, Vol. 25 Issue 4, p1-11. 11p.

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Benchmarks in antimicrobial peptide prediction are biased due to the selection of negative data.

• Authors : Sidorczuk, Katarzyna; Gagat, Przemysław; Pietluch, Filip

Subjects: ANTIMICROBIAL peptides; INTERNET servers; MACHINE learning

• Source: Briefings in Bioinformatics; Sep2022, Vol. 23 Issue 5, p1-12, 12p

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A two-stage computational framework for identifying antiviral peptides and their functional types based on contrastive learning and multi-feature fusion strategy.

• Authors : Guan, Jiahui^1,2 (AUTHOR); Yao, Lantian^1,3 (AUTHOR); Xie, Peilin² (AUTHOR)

• Source: Briefings in Bioinformatics. May2024, Vol. 25 Issue 3, p1-13. 13p.

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