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Annals of Data Science

DeepKPred: Prediction and Functional Analysis of Lysine 2-Hydroxyisobutyrylation Sites Based on Deep Learning

  • 18-12-2023
Published in:
Authors
Shiqi Fan
Yan Xu
Published in
Annals of Data Science | Issue 2/2024

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Abstract

The article introduces DeepKPred, a novel deep learning model designed to predict and functionally analyze lysine 2-hydroxyisobutyrylation sites. This post-translational modification is essential in proteomics, affecting protein functions and regulatory processes. The model combines convolutional neural networks (CNN) and long short-term memory networks (LSTM) to improve prediction accuracy. The authors also provide a detailed functional analysis using Gene Ontology (GO) and KEGG pathways, revealing insights into the biological processes and pathways associated with 2-hydroxyisobutyrylated proteins. The study highlights the potential of deep learning in advancing our understanding of protein modifications and their roles in various biological systems.
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Title
DeepKPred: Prediction and Functional Analysis of Lysine 2-Hydroxyisobutyrylation Sites Based on Deep Learning
Authors
Shiqi Fan
Yan Xu
Publication date
18-12-2023
Publisher
Springer Berlin Heidelberg
Published in
Annals of Data Science / Issue 2/2024
Print ISSN: 2198-5804
Electronic ISSN: 2198-5812
DOI
https://doi.org/10.1007/s40745-023-00504-1
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