2020
DOI: 10.1007/s10822-020-00307-z
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TargetCPP: accurate prediction of cell-penetrating peptides from optimized multi-scale features using gradient boost decision tree

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Cited by 51 publications
(26 citation statements)
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“…In addition, identifying shorter sequences is of great value when taking easier synthesis pathways and lower production costs into account. Importantly, computational methods attract more and more notice to predict novel CPP sequences [111].…”
Section: Current State-of-the-art and Future Perspectivesmentioning
confidence: 99%
“…In addition, identifying shorter sequences is of great value when taking easier synthesis pathways and lower production costs into account. Importantly, computational methods attract more and more notice to predict novel CPP sequences [111].…”
Section: Current State-of-the-art and Future Perspectivesmentioning
confidence: 99%
“…Numerous studies have suggested that applying bioinformatic tools for CPP predictions prior to wet-lab experimental characterization can save time and money (Arif et al, 2020 ; Kardani and Bolhassani, 2021 ). Therefore, in this study, we combined bioinformatic prediction and experimental validation to find and characterize novel and potent CPPs as a DNA vaccine and drug delivery system.…”
Section: Introductionmentioning
confidence: 99%
“…Notably, computational methods are receiving increasing attention in predicting novel CPP sequences. [261][262][263] Substantial efforts have been made to design and modulate novel CPP sequences, exhibiting increased membrane permeability and improved target specificity. Quantitative analysis tracking non-fragmented peptide drugs has a high possibility to contribute to the development of CPP-based therapeutic.…”
Section: Conclusion and Prospectsmentioning
confidence: 99%