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Journal of Biomolecular Structure and Dynamics Volume 40, 2022 - Issue 22

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iGluK-Deep: computational identification of lysine glutarylation sites using deep neural networks with general pseudo amino acid compositions

Sheraz Naseera Department of Computer Science, University of Management and Technology, Lahore, PakistanCorrespondence[email protected]

https://orcid.org/0000-0002-3224-9164

Rao Faizan Alib Department of Computer and Information Sciences, Universiti Teknologi PETRONAS, Perak Darul Ridzuan, Malaysia

https://orcid.org/0000-0003-0701-6761

Yaser Daanial Khana Department of Computer Science, University of Management and Technology, Lahore, Pakistan

P. D. D. Dominicb Department of Computer and Information Sciences, Universiti Teknologi PETRONAS, Perak Darul Ridzuan, Malaysia

https://orcid.org/0000-0002-2496-1311

Pages 11691-11704 | Received 15 May 2021, Accepted 24 Jul 2021, Published online: 16 Aug 2021

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https://doi.org/10.1080/07391102.2021.1962738
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iGluK-Deep: computational identification of lysine glutarylation sites using deep neural networks with general pseudo amino acid compositions

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iGluK-Deep: computational identification of lysine glutarylation sites using deep neural networks with general pseudo amino acid compositions

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