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Investigating molecular descriptors in cell-penetrating peptides prediction with deep learning: Employing N, O, and hydrophobicity according to the Eisenberg scale.

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Title: Investigating molecular descriptors in cell-penetrating peptides prediction with deep learning: Employing N, O, and hydrophobicity according to the Eisenberg scale.
Authors: Seixas Feio, Juliana Auzier1 (AUTHOR) juliana.feio@icen.ufpa.br, de Oliveira, Ewerton Cristhian Lima1,2 (AUTHOR), de Sales Junior, Claudomiro de Souza1 (AUTHOR), da Costa, Kauê Santana3 (AUTHOR), e Lima, Anderson Henrique Lima4 (AUTHOR)
Source: PLoS ONE. 6/13/2024, Vol. 19 Issue 6, p1-19. 19p.
Database: Academic Search Ultimate
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  Data: Investigating molecular descriptors in cell-penetrating peptides prediction with deep learning: Employing N, O, and hydrophobicity according to the Eisenberg scale.
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  Data: <searchLink fieldCode="JN" term="%22PLoS+ONE%22">PLoS ONE</searchLink>. 6/13/2024, Vol. 19 Issue 6, p1-19. 19p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=177839186
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              Text: 6/13/2024
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