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For: Wei H, Yang W, Tang H, Lin H. The Development of Machine Learning Methods in Cell-Penetrating Peptides Identification: A Brief Review. CDM 2019;20:217-23. [DOI: 10.2174/1389200219666181010114750] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 1.3] [Reference Citation Analysis]
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2 Sun K, Yao Y, Yun L, Zhang C, Xie J, Qian X, Tang Q, Sun L. Application of machine learning for ancestry inference using multi-InDel markers. Forensic Science International: Genetics 2022;59:102702. [DOI: 10.1016/j.fsigen.2022.102702] [Reference Citation Analysis]
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4 Feger G, Angelov B, Angelova A. Prediction of Amphiphilic Cell-Penetrating Peptide Building Blocks from Protein-Derived Amino Acid Sequences for Engineering of Drug Delivery Nanoassemblies. J Phys Chem B 2020;124:4069-78. [PMID: 32337991 DOI: 10.1021/acs.jpcb.0c01618] [Cited by in Crossref: 13] [Cited by in F6Publishing: 11] [Article Influence: 6.5] [Reference Citation Analysis]
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6 Zhou M, Zou X, Cheng K, Zhong S, Su Y, Wu T, Tao Y, Cong L, Yan B, Jiang Y. The role of cell-penetrating peptides in potential anti-cancer therapy. Clin Transl Med 2022;12:e822. [PMID: 35593206 DOI: 10.1002/ctm2.822] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]