BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

266 related articles for article (PubMed ID: 21267749)

  • 1. Prediction of lysine ubiquitination with mRMR feature selection and analysis.
    Cai Y; Huang T; Hu L; Shi X; Xie L; Li Y
    Amino Acids; 2012 Apr; 42(4):1387-95. PubMed ID: 21267749
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Prediction of tyrosine sulfation with mRMR feature selection and analysis.
    Niu S; Huang T; Feng K; Cai Y; Li Y
    J Proteome Res; 2010 Dec; 9(12):6490-7. PubMed ID: 20973568
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A method to distinguish between lysine acetylation and lysine ubiquitination with feature selection and analysis.
    Zhou Y; Zhang N; Li BQ; Huang T; Cai YD; Kong XY
    J Biomol Struct Dyn; 2015; 33(11):2479-90. PubMed ID: 25616595
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Prediction of carbamylated lysine sites based on the one-class k-nearest neighbor method.
    Huang G; Zhou Y; Zhang Y; Li BQ; Zhang N; Cai YD
    Mol Biosyst; 2013 Nov; 9(11):2729-40. PubMed ID: 24056952
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Prediction and analysis of protein palmitoylation sites.
    Hu LL; Wan SB; Niu S; Shi XH; Li HP; Cai YD; Chou KC
    Biochimie; 2011 Mar; 93(3):489-96. PubMed ID: 21075167
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Computational Prediction of Protein Epsilon Lysine Acetylation Sites Based on a Feature Selection Method.
    Gao J; Tao XW; Zhao J; Feng YM; Cai YD; Zhang N
    Comb Chem High Throughput Screen; 2017; 20(7):629-637. PubMed ID: 28292250
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Using WPNNA classifier in ubiquitination site prediction based on hybrid features.
    Feng KY; Huang T; Feng KR; Liu XJ
    Protein Pept Lett; 2013 Mar; 20(3):318-23. PubMed ID: 22591471
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Predicting protein oxidation sites with feature selection and analysis approach.
    Niu S; Hu LL; Zheng LL; Huang T; Feng KY; Cai YD; Li HP; Li YX; Chou KC
    J Biomol Struct Dyn; 2012; 29(6):650-8. PubMed ID: 22545996
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Prediction and analysis of protein methylarginine and methyllysine based on Multisequence features.
    Hu LL; Li Z; Wang K; Niu S; Shi XH; Cai YD; Li HP
    Biopolymers; 2011 Nov; 95(11):763-71. PubMed ID: 21544797
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Computational prediction and analysis of protein γ-carboxylation sites based on a random forest method.
    Zhang N; Li BQ; Gao S; Ruan JS; Cai YD
    Mol Biosyst; 2012 Nov; 8(11):2946-55. PubMed ID: 22918520
    [TBL] [Abstract][Full Text] [Related]  

  • 11. PLMLA: prediction of lysine methylation and lysine acetylation by combining multiple features.
    Shi SP; Qiu JD; Sun XY; Suo SB; Huang SY; Liang RP
    Mol Biosyst; 2012 Apr; 8(5):1520-7. PubMed ID: 22402705
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Mal-Lys: prediction of lysine malonylation sites in proteins integrated sequence-based features with mRMR feature selection.
    Xu Y; Ding YX; Ding J; Wu LY; Xue Y
    Sci Rep; 2016 Dec; 6():38318. PubMed ID: 27910954
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Position-specific analysis and prediction of protein pupylation sites based on multiple features.
    Zhao X; Dai J; Ning Q; Ma Z; Yin M; Sun P
    Biomed Res Int; 2013; 2013():109549. PubMed ID: 24066285
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Predicting N-terminal acetylation based on feature selection method.
    Cai YD; Lu L
    Biochem Biophys Res Commun; 2008 Aug; 372(4):862-5. PubMed ID: 18533108
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Identification of protein methylation sites by coupling improved ant colony optimization algorithm and support vector machine.
    Li ZC; Zhou X; Dai Z; Zou XY
    Anal Chim Acta; 2011 Oct; 703(2):163-71. PubMed ID: 21889630
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Prediction of protein-protein interactions based on PseAA composition and hybrid feature selection.
    Liu L; Cai Y; Lu W; Feng K; Peng C; Niu B
    Biochem Biophys Res Commun; 2009 Mar; 380(2):318-22. PubMed ID: 19171120
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Prediction of GABAA receptor proteins using the concept of Chou's pseudo-amino acid composition and support vector machine.
    Mohabatkar H; Mohammad Beigi M; Esmaeili A
    J Theor Biol; 2011 Jul; 281(1):18-23. PubMed ID: 21536049
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Prediction of active sites of enzymes by maximum relevance minimum redundancy (mRMR) feature selection.
    Gao YF; Li BQ; Cai YD; Feng KY; Li ZD; Jiang Y
    Mol Biosyst; 2013 Jan; 9(1):61-9. PubMed ID: 23117653
    [TBL] [Abstract][Full Text] [Related]  

  • 19. iLM-2L: A two-level predictor for identifying protein lysine methylation sites and their methylation degrees by incorporating K-gap amino acid pairs into Chou׳s general PseAAC.
    Ju Z; Cao JZ; Gu H
    J Theor Biol; 2015 Nov; 385():50-7. PubMed ID: 26254214
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Using increment of diversity to predict mitochondrial proteins of malaria parasite: integrating pseudo-amino acid composition and structural alphabet.
    Chen YL; Li QZ; Zhang LQ
    Amino Acids; 2012 Apr; 42(4):1309-16. PubMed ID: 21191803
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 14.