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- W2897866928 abstract "Background: Cell-penetrating Peptides (CPPs) are important short peptides that facilitate cellular intake or uptake of various molecules. CPPs can transport drug molecules through the plasma membrane and send these molecules to different cellular organelles. Thus, CPP identification and related mechanisms have been extensively explored. In order to reveal the penetration mechanisms of a large number of CPPs, it is necessary to develop convenient and fast methods for CPPs identification. Methods: Biochemical experiments can provide precise details for accurately identifying CPP, but these methods are expensive and laborious. To overcome these disadvantages, several computational methods have been developed to identify CPPs. We have performed review on the development of machine learning methods in CPP identification. This review provides an insight into CPP identification. Results: We summarized the machine learning-based CPP identification methods and compared the construction strategies of 11 different computational methods. Furthermore, we pointed out the limitations and difficulties in predicting CPPs. Conclusion: In this review, the last studies on CPP identification using machine learning method were reported. We also discussed the future development direction of CPP recognition with computational methods." @default.
- W2897866928 created "2018-10-26" @default.
- W2897866928 creator A5003076492 @default.
- W2897866928 creator A5041539298 @default.
- W2897866928 creator A5043530440 @default.
- W2897866928 creator A5066797937 @default.
- W2897866928 date "2019-05-22" @default.
- W2897866928 modified "2023-10-17" @default.
- W2897866928 title "The Development of Machine Learning Methods in Cell-Penetrating Peptides Identification: A Brief Review" @default.
- W2897866928 cites W1186776093 @default.
- W2897866928 cites W1253096047 @default.
- W2897866928 cites W1553897125 @default.
- W2897866928 cites W1663797894 @default.
- W2897866928 cites W1983808106 @default.
- W2897866928 cites W1985718949 @default.
- W2897866928 cites W1986299453 @default.
- W2897866928 cites W1996461253 @default.
- W2897866928 cites W1996745763 @default.
- W2897866928 cites W1996954063 @default.
- W2897866928 cites W2001802384 @default.
- W2897866928 cites W2004132756 @default.
- W2897866928 cites W2021823827 @default.
- W2897866928 cites W2024213882 @default.
- W2897866928 cites W2033357321 @default.
- W2897866928 cites W2036506143 @default.
- W2897866928 cites W2038873127 @default.
- W2897866928 cites W2043153340 @default.
- W2897866928 cites W2043338013 @default.
- W2897866928 cites W2069182579 @default.
- W2897866928 cites W2076859770 @default.
- W2897866928 cites W2077799814 @default.
- W2897866928 cites W2079335891 @default.
- W2897866928 cites W2083557994 @default.
- W2897866928 cites W2093567555 @default.
- W2897866928 cites W2096023347 @default.
- W2897866928 cites W2097606916 @default.
- W2897866928 cites W2116672918 @default.
- W2897866928 cites W2125450037 @default.
- W2897866928 cites W2139166279 @default.
- W2897866928 cites W2141241945 @default.
- W2897866928 cites W2145957695 @default.
- W2897866928 cites W2145991251 @default.
- W2897866928 cites W2154053567 @default.
- W2897866928 cites W2157009395 @default.
- W2897866928 cites W2158714788 @default.
- W2897866928 cites W2168639488 @default.
- W2897866928 cites W2172637956 @default.
- W2897866928 cites W2220780917 @default.
- W2897866928 cites W2254740876 @default.
- W2897866928 cites W2266433062 @default.
- W2897866928 cites W2298467901 @default.
- W2897866928 cites W2334629405 @default.
- W2897866928 cites W2342195926 @default.
- W2897866928 cites W2344557669 @default.
- W2897866928 cites W2347112107 @default.
- W2897866928 cites W2379683068 @default.
- W2897866928 cites W2400814742 @default.
- W2897866928 cites W2414310543 @default.
- W2897866928 cites W2418704427 @default.
- W2897866928 cites W2502823509 @default.
- W2897866928 cites W2506152623 @default.
- W2897866928 cites W2513825894 @default.
- W2897866928 cites W2514534732 @default.
- W2897866928 cites W2518983308 @default.
- W2897866928 cites W2528970029 @default.
- W2897866928 cites W2538780415 @default.
- W2897866928 cites W2563322674 @default.
- W2897866928 cites W2565608178 @default.
- W2897866928 cites W2587688848 @default.
- W2897866928 cites W2588262749 @default.
- W2897866928 cites W2591975816 @default.
- W2897866928 cites W2608969085 @default.
- W2897866928 cites W2625461439 @default.
- W2897866928 cites W2737592062 @default.
- W2897866928 cites W2745811851 @default.
- W2897866928 cites W2765779130 @default.
- W2897866928 cites W2766725728 @default.
- W2897866928 cites W2783049948 @default.
- W2897866928 cites W2805110914 @default.
- W2897866928 cites W2805791355 @default.
- W2897866928 cites W2808950870 @default.
- W2897866928 cites W2884152064 @default.
- W2897866928 cites W2885768951 @default.
- W2897866928 cites W2886373325 @default.
- W2897866928 cites W2911964244 @default.
- W2897866928 cites W2963614249 @default.
- W2897866928 cites W3024347731 @default.
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- W2897866928 doi "https://doi.org/10.2174/1389200219666181010114750" @default.
- W2897866928 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30317992" @default.
- W2897866928 hasPublicationYear "2019" @default.
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