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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

209 related articles for article (PubMed ID: 25248923)

  • 41. iRSpot-TNCPseAAC: identify recombination spots with trinucleotide composition and pseudo amino acid components.
    Qiu WR; Xiao X; Chou KC
    Int J Mol Sci; 2014 Jan; 15(2):1746-66. PubMed ID: 24469313
    [TBL] [Abstract][Full Text] [Related]  

  • 42. iPSW(2L)-PseKNC: A two-layer predictor for identifying promoters and their strength by hybrid features via pseudo K-tuple nucleotide composition.
    Xiao X; Xu ZC; Qiu WR; Wang P; Ge HT; Chou KC
    Genomics; 2019 Dec; 111(6):1785-1793. PubMed ID: 30529532
    [TBL] [Abstract][Full Text] [Related]  

  • 43. pLoc_bal-mPlant: Predict Subcellular Localization of Plant Proteins by General PseAAC and Balancing Training Dataset.
    Cheng X; Xiao X; Chou KC
    Curr Pharm Des; 2018; 24(34):4013-4022. PubMed ID: 30451108
    [TBL] [Abstract][Full Text] [Related]  

  • 44. iGlu-Lys: A Predictor for Lysine Glutarylation Through Amino Acid Pair Order Features.
    Xu Y; Yang Y; Ding J; Li C
    IEEE Trans Nanobioscience; 2018 Oct; 17(4):394-401. PubMed ID: 29994125
    [TBL] [Abstract][Full Text] [Related]  

  • 45. Multi-iPPseEvo: A Multi-label Classifier for Identifying Human Phosphorylated Proteins by Incorporating Evolutionary Information into Chou's General PseAAC via Grey System Theory.
    Qiu WR; Zheng QS; Sun BQ; Xiao X
    Mol Inform; 2017 Mar; 36(3):. PubMed ID: 27681207
    [TBL] [Abstract][Full Text] [Related]  

  • 46. iSuc-PseAAC: predicting lysine succinylation in proteins by incorporating peptide position-specific propensity.
    Xu Y; Ding YX; Ding J; Lei YH; Wu LY; Deng NY
    Sci Rep; 2015 Jun; 5():10184. PubMed ID: 26084794
    [TBL] [Abstract][Full Text] [Related]  

  • 47. GPCR-2L: predicting G protein-coupled receptors and their types by hybridizing two different modes of pseudo amino acid compositions.
    Xiao X; Wang P; Chou KC
    Mol Biosyst; 2011 Mar; 7(3):911-9. PubMed ID: 21180772
    [TBL] [Abstract][Full Text] [Related]  

  • 48. iGPCR-drug: a web server for predicting interaction between GPCRs and drugs in cellular networking.
    Xiao X; Min JL; Wang P; Chou KC
    PLoS One; 2013; 8(8):e72234. PubMed ID: 24015221
    [TBL] [Abstract][Full Text] [Related]  

  • 49. Predicting secretory proteins of malaria parasite by incorporating sequence evolution information into pseudo amino acid composition via grey system model.
    Lin WZ; Fang JA; Xiao X; Chou KC
    PLoS One; 2012; 7(11):e49040. PubMed ID: 23189138
    [TBL] [Abstract][Full Text] [Related]  

  • 50. MeMo: a web tool for prediction of protein methylation modifications.
    Chen H; Xue Y; Huang N; Yao X; Sun Z
    Nucleic Acids Res; 2006 Jul; 34(Web Server issue):W249-53. PubMed ID: 16845004
    [TBL] [Abstract][Full Text] [Related]  

  • 51. The origins and evolution of ubiquitination sites.
    Hagai T; Tóth-Petróczy Á; Azia A; Levy Y
    Mol Biosyst; 2012 Jul; 8(7):1865-77. PubMed ID: 22588506
    [TBL] [Abstract][Full Text] [Related]  

  • 52. pRNAm-PC: Predicting N(6)-methyladenosine sites in RNA sequences via physical-chemical properties.
    Liu Z; Xiao X; Yu DJ; Jia J; Qiu WR; Chou KC
    Anal Biochem; 2016 Mar; 497():60-7. PubMed ID: 26748145
    [TBL] [Abstract][Full Text] [Related]  

  • 53. Identification and characterization of lysine-methylated sites on histones and non-histone proteins.
    Lee TY; Chang CW; Lu CT; Cheng TH; Chang TH
    Comput Biol Chem; 2014 Jun; 50():11-8. PubMed ID: 24560580
    [TBL] [Abstract][Full Text] [Related]  

  • 54. iROS-gPseKNC: Predicting replication origin sites in DNA by incorporating dinucleotide position-specific propensity into general pseudo nucleotide composition.
    Xiao X; Ye HX; Liu Z; Jia JH; Chou KC
    Oncotarget; 2016 Jun; 7(23):34180-9. PubMed ID: 27147572
    [TBL] [Abstract][Full Text] [Related]  

  • 55. pLoc_bal-mHum: Predict subcellular localization of human proteins by PseAAC and quasi-balancing training dataset.
    Chou KC; Cheng X; Xiao X
    Genomics; 2019 Dec; 111(6):1274-1282. PubMed ID: 30179658
    [TBL] [Abstract][Full Text] [Related]  

  • 56. iPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition.
    Lin H; Deng EZ; Ding H; Chen W; Chou KC
    Nucleic Acids Res; 2014 Dec; 42(21):12961-72. PubMed ID: 25361964
    [TBL] [Abstract][Full Text] [Related]  

  • 57. Prediction of lysine crotonylation sites by incorporating the composition of k-spaced amino acid pairs into Chou's general PseAAC.
    Ju Z; He JJ
    J Mol Graph Model; 2017 Oct; 77():200-204. PubMed ID: 28886434
    [TBL] [Abstract][Full Text] [Related]  

  • 58. dForml(KNN)-PseAAC: Detecting formylation sites from protein sequences using K-nearest neighbor algorithm via Chou's 5-step rule and pseudo components.
    Ning Q; Ma Z; Zhao X
    J Theor Biol; 2019 Jun; 470():43-49. PubMed ID: 30880183
    [TBL] [Abstract][Full Text] [Related]  

  • 59. 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]  

  • 60. pLoc_bal-mGneg: Predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC.
    Cheng X; Xiao X; Chou KC
    J Theor Biol; 2018 Dec; 458():92-102. PubMed ID: 30201434
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 11.