These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

275 related items for PubMed ID: 30576418

  • 1. Research progress in protein posttranslational modification site prediction.
    He W, Wei L, Zou Q.
    Brief Funct Genomics; 2018 Jul 22; 18(4):220-229. PubMed ID: 30576418
    [Abstract] [Full Text] [Related]

  • 2.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 3.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 4. A Text Mining and Machine Learning Protocol for Extracting Posttranslational Modifications of Proteins from PubMed: A Special Focus on Glycosylation, Acetylation, Methylation, Hydroxylation, and Ubiquitination.
    Arumugam K, Sellappan M, Anand D, Anand S, Radhakrishnan SV.
    Methods Mol Biol; 2022 Jul 22; 2496():179-202. PubMed ID: 35713865
    [Abstract] [Full Text] [Related]

  • 5.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 6.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 7. Identification, Quantification, and Site Localization of Protein Posttranslational Modifications via Mass Spectrometry-Based Proteomics.
    Ke M, Shen H, Wang L, Luo S, Lin L, Yang J, Tian R.
    Adv Exp Med Biol; 2016 Jul 22; 919():345-382. PubMed ID: 27975226
    [Abstract] [Full Text] [Related]

  • 8.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 9. Machine learning-based approaches for ubiquitination site prediction in human proteins.
    Pourmirzaei M, Ramazi S, Esmaili F, Shojaeilangari S, Allahvardi A.
    BMC Bioinformatics; 2023 Nov 28; 24(1):449. PubMed ID: 38017391
    [Abstract] [Full Text] [Related]

  • 10. Towards Computational Models of Identifying Protein Ubiquitination Sites.
    Wang L, Zhang R.
    Curr Drug Targets; 2019 Nov 28; 20(5):565-578. PubMed ID: 30246637
    [Abstract] [Full Text] [Related]

  • 11.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 12.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 13.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 14. PTM-X: Prediction of Post-Translational Modification Crosstalk Within and Across Proteins.
    Li Y, Huang Y, Li T.
    Methods Mol Biol; 2022 Nov 28; 2499():275-283. PubMed ID: 35696086
    [Abstract] [Full Text] [Related]

  • 15. A Review of Machine Learning and Algorithmic Methods for Protein Phosphorylation Site Prediction.
    Esmaili F, Pourmirzaei M, Ramazi S, Shojaeilangari S, Yavari E.
    Genomics Proteomics Bioinformatics; 2023 Dec 28; 21(6):1266-1285. PubMed ID: 37863385
    [Abstract] [Full Text] [Related]

  • 16. Computational methods for ubiquitination site prediction using physicochemical properties of protein sequences.
    Cai B, Jiang X.
    BMC Bioinformatics; 2016 Mar 03; 17():116. PubMed ID: 26940649
    [Abstract] [Full Text] [Related]

  • 17. Enhancing the Discovery of Functional Post-Translational Modification Sites with Machine Learning Models - Development, Validation, and Interpretation.
    English N, Torres M.
    Methods Mol Biol; 2022 Mar 03; 2499():221-260. PubMed ID: 35696084
    [Abstract] [Full Text] [Related]

  • 18.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 19.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 20.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

    Page: [Next] [New Search]
    of 14.