Corrigendum to: A holistic approach towards a generalizable machine learning predictor of cell penetrating peptides

Bahaa Ismail; Sarah Jones; John Howl

doi:10.1071/CH22247

Corrigendum to: A holistic approach towards a generalizable machine learning predictor of cell penetrating peptides

Bahaa Ismail, Sarah Jones, John Howl^*

^*Corresponding author for this work

University of Wolverhampton

Research output: Contribution to journal › Article › peer-review

1 Citation (SciVal)

Original language	English
Pages (from-to)	493-506
Number of pages	14
Journal	Australian Journal of Chemistry
Volume	76
Issue number	8
DOIs	https://doi.org/10.1071/CH22247
Publication status	Published (VoR) - 21 Jun 2023

Funding

This work was financially supported by CARA fellowship program which included the computational facilities support. Acknowledgements

Funders	Funder number
Cara

Keywords

amino acid composition
cellular uptake
CPP
data pre-processing
drug delivery
feature optimization
machine learning
peptide classification
SVM

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10.1071/CH22247

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title = "Corrigendum to: A holistic approach towards a generalizable machine learning predictor of cell penetrating peptides",

keywords = "amino acid composition, cellular uptake, CPP, data pre-processing, drug delivery, feature optimization, machine learning, peptide classification, SVM",

author = "Bahaa Ismail and Sarah Jones and John Howl",

note = "Publisher Copyright: {\textcopyright} 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing.",

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doi = "10.1071/CH22247",

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T2 - A holistic approach towards a generalizable machine learning predictor of cell penetrating peptides

AU - Ismail, Bahaa

AU - Jones, Sarah

AU - Howl, John

PY - 2023/6/21

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KW - amino acid composition

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KW - data pre-processing

KW - drug delivery

KW - feature optimization

KW - machine learning

KW - peptide classification

KW - SVM

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M3 - Article

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JF - Australian Journal of Chemistry

IS - 8

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Corrigendum to: A holistic approach towards a generalizable machine learning predictor of cell penetrating peptides

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Keywords

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