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BiGKbhb: a bi-directional gated recurrent unit model for predicting lysine β-hydroxybutyrylation sites
by
El-Samie, Fathi E. Abd
, Elreify, Heba M.
, El-Khamy, Said E.
, Dessouky, Moawad I.
, Torkey, Hanaa
, Shalaby, Wafaa A.
in
Accuracy
/ Amino acid sequence
/ Animal Genetics and Genomics
/ Artificial intelligence
/ Bidirectional gated recurrent unit
/ Biomedical and Life Sciences
/ BLOSUM
/ Cell cycle
/ Chemical synthesis
/ Datasets
/ Deep learning
/ Enzymes
/ Fungi
/ Gene expression
/ Genetic aspects
/ Genetic research
/ Genomes
/ Histones
/ Kbhb
/ Kinases
/ Life Sciences
/ Localization
/ Lysine
/ Mass spectrometry
/ Metabolism
/ Metabolites
/ Microarrays
/ Microbial Genetics and Genomics
/ Neural networks
/ Physiological aspects
/ Plant Genetics and Genomics
/ Post-translation
/ Post-translational modification
/ Post-translational modifications
/ Protein biosynthesis
/ Protein folding
/ Protein language models
/ Protein synthesis
/ Proteins
/ Proteomes
/ Proteomics
/ Scientific imaging
/ Signal transduction
/ Software
/ Species
/ Species diversity
/ Statistical analysis
/ Statistical models
/ Β-hydroxybutyrylation
2026
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BiGKbhb: a bi-directional gated recurrent unit model for predicting lysine β-hydroxybutyrylation sites
by
El-Samie, Fathi E. Abd
, Elreify, Heba M.
, El-Khamy, Said E.
, Dessouky, Moawad I.
, Torkey, Hanaa
, Shalaby, Wafaa A.
in
Accuracy
/ Amino acid sequence
/ Animal Genetics and Genomics
/ Artificial intelligence
/ Bidirectional gated recurrent unit
/ Biomedical and Life Sciences
/ BLOSUM
/ Cell cycle
/ Chemical synthesis
/ Datasets
/ Deep learning
/ Enzymes
/ Fungi
/ Gene expression
/ Genetic aspects
/ Genetic research
/ Genomes
/ Histones
/ Kbhb
/ Kinases
/ Life Sciences
/ Localization
/ Lysine
/ Mass spectrometry
/ Metabolism
/ Metabolites
/ Microarrays
/ Microbial Genetics and Genomics
/ Neural networks
/ Physiological aspects
/ Plant Genetics and Genomics
/ Post-translation
/ Post-translational modification
/ Post-translational modifications
/ Protein biosynthesis
/ Protein folding
/ Protein language models
/ Protein synthesis
/ Proteins
/ Proteomes
/ Proteomics
/ Scientific imaging
/ Signal transduction
/ Software
/ Species
/ Species diversity
/ Statistical analysis
/ Statistical models
/ Β-hydroxybutyrylation
2026
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BiGKbhb: a bi-directional gated recurrent unit model for predicting lysine β-hydroxybutyrylation sites
by
El-Samie, Fathi E. Abd
, Elreify, Heba M.
, El-Khamy, Said E.
, Dessouky, Moawad I.
, Torkey, Hanaa
, Shalaby, Wafaa A.
in
Accuracy
/ Amino acid sequence
/ Animal Genetics and Genomics
/ Artificial intelligence
/ Bidirectional gated recurrent unit
/ Biomedical and Life Sciences
/ BLOSUM
/ Cell cycle
/ Chemical synthesis
/ Datasets
/ Deep learning
/ Enzymes
/ Fungi
/ Gene expression
/ Genetic aspects
/ Genetic research
/ Genomes
/ Histones
/ Kbhb
/ Kinases
/ Life Sciences
/ Localization
/ Lysine
/ Mass spectrometry
/ Metabolism
/ Metabolites
/ Microarrays
/ Microbial Genetics and Genomics
/ Neural networks
/ Physiological aspects
/ Plant Genetics and Genomics
/ Post-translation
/ Post-translational modification
/ Post-translational modifications
/ Protein biosynthesis
/ Protein folding
/ Protein language models
/ Protein synthesis
/ Proteins
/ Proteomes
/ Proteomics
/ Scientific imaging
/ Signal transduction
/ Software
/ Species
/ Species diversity
/ Statistical analysis
/ Statistical models
/ Β-hydroxybutyrylation
2026
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BiGKbhb: a bi-directional gated recurrent unit model for predicting lysine β-hydroxybutyrylation sites
Journal Article
BiGKbhb: a bi-directional gated recurrent unit model for predicting lysine β-hydroxybutyrylation sites
2026
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Overview
Post-Translational Modifications (PTMs) are covalent chemical alterations that occur after protein synthesis, critically regulating protein function, localization, and interactions. β-hydroxybutyrylation (Kbhb), a metabolically derived histone modification discovered in 2016, influences gene activation and cellular metabolism. While accurate PTM site identification is essential for understanding protein regulation and disease mechanisms, experimental approaches face significant limitations, including low modification abundance, high cost, and limited proteome coverage. Kbhb remains computationally underexplored, with only three existing prediction tools exhibiting modest accuracy and limited cross-species applicability. To address this gap, we developed BiGKbhb, a deep learning framework that depends on Bidirectional Gated Recurrent Units (BiGRU). With BiGKbhb, we systematically evaluate seven protein sequence encoding strategies, and compare six deep learning architectures using datasets from human, mouse, and fungal species. Results demonstrated that BLOSUM62 evolutionary encoding combined with BiGRU architecture achieves optimal performance, with BiGKbhb consistently achieving higher accuracy than those of existing methods with test set accuracies of 0.824, 0.832, and 0.871 for human, mouse, and fungal balanced datasets, respectively, with corresponding Area Under Curve (AUC) values of 0.920, 0.902, and 0.945, while additional evaluation on imbalanced datasets confirmed model robustness under realistic conditions. Cross-species analysis revealed enhanced transferability of the general multi-species model, and statistical validation confirmed significant improvements over existing predictors (
p
< 0.05). These findings contribute a robust computational tool for Kbhb prediction and provide insights into sequence determinants of this important modification across evolutionarily diverse species.
Publisher
BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
Subject
/ Animal Genetics and Genomics
/ Bidirectional gated recurrent unit
/ Biomedical and Life Sciences
/ BLOSUM
/ Datasets
/ Enzymes
/ Fungi
/ Genomes
/ Histones
/ Kbhb
/ Kinases
/ Lysine
/ Microbial Genetics and Genomics
/ Post-translational modification
/ Post-translational modifications
/ Proteins
/ Software
/ Species
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