Machine Learning Methods in Prediction of Protein Palmitoylation Sites: A Brief Review.

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  • Additional Information
    • Source:
      Publisher: Bentham Science Publishers Country of Publication: United Arab Emirates NLM ID: 9602487 Publication Model: Print Cited Medium: Internet ISSN: 1873-4286 (Electronic) Linking ISSN: 13816128 NLM ISO Abbreviation: Curr Pharm Des Subsets: MEDLINE
    • Publication Information:
      Publication: Saif Zone, Sharjah, U.A.E. : Bentham Science Publishers
      Original Publication: Schiphol, The Netherlands : Bentham Science Publishers, c1995-
    • Subject Terms:
      Computational Biology* ; Lipoylation*; Humans ; Machine Learning ; Protein Processing, Post-Translational
    • Abstract:
      Protein palmitoylation is a fundamental and reversible post-translational lipid modification that involves a series of biological processes. Although a large number of experimental studies have explored the molecular mechanism behind the palmitoylation process, the computational methods has attracted much attention for its good performance in predicting palmitoylation sites compared with expensive and time-consuming biochemical experiments. The prediction of protein palmitoylation sites is helpful to reveal its biological mechanism. Therefore, the research on the application of machine learning methods to predict palmitoylation sites has become a hot topic in bioinformatics and promoted the development in the related fields. In this review, we briefly introduced the recent development in predicting protein palmitoylation sites by using machine learningbased methods and discussed their benefits and drawbacks. The perspective of machine learning-based methods in predicting palmitoylation sites was also provided. We hope the review could provide a guide in related fields.
      (Copyright© Bentham Science Publishers; For any queries, please email at [email protected].)
    • Contributed Indexing:
      Keywords: Palmitoylation; benchmark; bioinformatics; feature extraction; machine learning methods; post-translational; post-translational lipid modification.
    • Publication Date:
      Date Created: 20201113 Date Completed: 20210806 Latest Revision: 20210806
    • Publication Date:
      20231215
    • Accession Number:
      10.2174/1381612826666201112142826
    • Accession Number:
      33183190