iGluK-Deep: computational identification of lysine glutarylation sites using deep neural networks with general pseudo amino acid compositions
Author:
Affiliation:
1. Department of Computer Science, University of Management and Technology, Lahore, Pakistan
2. Department of Computer and Information Sciences, Universiti Teknologi PETRONAS, Perak Darul Ridzuan, Malaysia
Publisher
Informa UK Limited
Subject
Molecular Biology,General Medicine,Structural Biology
Link
https://www.tandfonline.com/doi/pdf/10.1080/07391102.2021.1962738
Reference59 articles.
1. Accurately Predicting Glutarylation Sites Using Sequential Bi-Peptide-Based Evolutionary Features
2. Assessing the accuracy of prediction algorithms for classification: an overview
3. Glutarylation of Histone H4 Lysine 91 Regulates Chromatin Dynamics
4. Learning long-term dependencies with gradient descent is difficult
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