BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

150 related articles for article (PubMed ID: 34806952)

  • 1. O-glycosylation site prediction for
    Zhu Y; Yin S; Zheng J; Shi Y; Jia C
    J Bioinform Comput Biol; 2022 Feb; 20(1):2150029. PubMed ID: 34806952
    [TBL] [Abstract][Full Text] [Related]  

  • 2. PredGly: predicting lysine glycation sites for Homo sapiens based on XGboost feature optimization.
    Yu J; Shi S; Zhang F; Chen G; Cao M
    Bioinformatics; 2019 Aug; 35(16):2749-2756. PubMed ID: 30590442
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Computational Prediction of N- and O-Linked Glycosylation Sites for Human and Mouse Proteins.
    Taherzadeh G; Campbell M; Zhou Y
    Methods Mol Biol; 2022; 2499():177-186. PubMed ID: 35696081
    [TBL] [Abstract][Full Text] [Related]  

  • 4. iRNA-2OM: A Sequence-Based Predictor for Identifying 2'-O-Methylation Sites in Homo sapiens.
    Yang H; Lv H; Ding H; Chen W; Lin H
    J Comput Biol; 2018 Nov; 25(11):1266-1277. PubMed ID: 30113871
    [TBL] [Abstract][Full Text] [Related]  

  • 5. UbNiRF: A Hybrid Framework Based on Null Importances and Random Forest that Combines Multiple Features to Predict Ubiquitination Sites in
    Li X; Yuan Z; Chen Y
    Front Biosci (Landmark Ed); 2024 May; 29(5):197. PubMed ID: 38812315
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Glycosylation site prediction using ensembles of Support Vector Machine classifiers.
    Caragea C; Sinapov J; Silvescu A; Dobbs D; Honavar V
    BMC Bioinformatics; 2007 Nov; 8():438. PubMed ID: 17996106
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Combining handcrafted features with latent variables in machine learning for prediction of radiation-induced lung damage.
    Cui S; Luo Y; Tseng HH; Ten Haken RK; El Naqa I
    Med Phys; 2019 May; 46(5):2497-2511. PubMed ID: 30891794
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Positive-unlabelled learning of glycosylation sites in the human proteome.
    Li F; Zhang Y; Purcell AW; Webb GI; Chou KC; Lithgow T; Li C; Song J
    BMC Bioinformatics; 2019 Mar; 20(1):112. PubMed ID: 30841845
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Improved Prediction of Protein-Protein Interaction Mapping on
    Islam MM; Alam MJ; Ahmed FF; Hasan MM; Mollah MNH
    Protein Pept Lett; 2021; 28(1):74-83. PubMed ID: 32520672
    [TBL] [Abstract][Full Text] [Related]  

  • 10. O-GlyThr: Prediction of human O-linked threonine glycosites using multi-feature fusion.
    Tang H; Tang Q; Zhang Q; Feng P
    Int J Biol Macromol; 2023 Jul; 242(Pt 2):124761. PubMed ID: 37156312
    [TBL] [Abstract][Full Text] [Related]  

  • 11. iDPGK: characterization and identification of lysine phosphoglycerylation sites based on sequence-based features.
    Huang KY; Hung FY; Kao HJ; Lau HH; Weng SL
    BMC Bioinformatics; 2020 Dec; 21(1):568. PubMed ID: 33297954
    [TBL] [Abstract][Full Text] [Related]  

  • 12. O-GlcNAcPRED-II: an integrated classification algorithm for identifying O-GlcNAcylation sites based on fuzzy undersampling and a K-means PCA oversampling technique.
    Jia C; Zuo Y; Zou Q
    Bioinformatics; 2018 Jun; 34(12):2029-2036. PubMed ID: 29420699
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Support vector machine-based mucin-type o-linked glycosylation site prediction using enhanced sequence feature encoding.
    Torii M; Liu H; Hu ZZ
    AMIA Annu Symp Proc; 2009 Nov; 2009():640-4. PubMed ID: 20351933
    [TBL] [Abstract][Full Text] [Related]  

  • 14. ATGPred-FL: sequence-based prediction of autophagy proteins with feature representation learning.
    Jiao S; Chen Z; Zhang L; Zhou X; Shi L
    Amino Acids; 2022 May; 54(5):799-809. PubMed ID: 35286461
    [TBL] [Abstract][Full Text] [Related]  

  • 15. DeepSSPred: A Deep Learning Based Sulfenylation Site Predictor Via a Novel nSegmented Optimize Federated Feature Encoder.
    Khan ZU; Pi D
    Protein Pept Lett; 2021; 28(6):708-721. PubMed ID: 33267753
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Computational analysis and prediction of lysine malonylation sites by exploiting informative features in an integrative machine-learning framework.
    Zhang Y; Xie R; Wang J; Leier A; Marquez-Lago TT; Akutsu T; Webb GI; Chou KC; Song J
    Brief Bioinform; 2019 Nov; 20(6):2185-2199. PubMed ID: 30351377
    [TBL] [Abstract][Full Text] [Related]  

  • 17. HSM6AP: a high-precision predictor for the Homo
    Li J; He S; Guo F; Zou Q
    RNA Biol; 2021 Nov; 18(11):1882-1892. PubMed ID: 33446014
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Predicting lysine phosphoglycerylation with fuzzy SVM by incorporating k-spaced amino acid pairs into Chou׳s general PseAAC.
    Ju Z; Cao JZ; Gu H
    J Theor Biol; 2016 May; 397():145-50. PubMed ID: 26908349
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Prediction of O-glycosylation sites based on multi-scale composition of amino acids and feature selection.
    Chen Y; Zhou W; Wang H; Yuan Z
    Med Biol Eng Comput; 2015 Jun; 53(6):535-44. PubMed ID: 25752770
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Formator: Predicting Lysine Formylation Sites Based on the Most Distant Undersampling and Safe-Level Synthetic Minority Oversampling.
    Jia C; Zhang M; Fan C; Li F; Song J
    IEEE/ACM Trans Comput Biol Bioinform; 2021; 18(5):1937-1945. PubMed ID: 31804942
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.