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 *

165 related articles for article (PubMed ID: 17069811)

  • 1. A novel method for apoptosis protein subcellular localization prediction combining encoding based on grouped weight and support vector machine.
    Zhang ZH; Wang ZH; Zhang ZR; Wang YX
    FEBS Lett; 2006 Nov; 580(26):6169-74. PubMed ID: 17069811
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Improved prediction of subcellular location for apoptosis proteins by the dual-layer support vector machine.
    Zhou XB; Chen C; Li ZC; Zou XY
    Amino Acids; 2008 Aug; 35(2):383-8. PubMed ID: 18157588
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Prediction of subcellular localization of apoptosis protein using Chou's pseudo amino acid composition.
    Lin H; Wang H; Ding H; Chen YL; Li QZ
    Acta Biotheor; 2009 Sep; 57(3):321-30. PubMed ID: 19169652
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Prediction of apoptosis protein subcellular location using improved hybrid approach and pseudo-amino acid composition.
    Chen YL; Li QZ
    J Theor Biol; 2007 Sep; 248(2):377-81. PubMed ID: 17572445
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Prediction of the subcellular location of apoptosis proteins.
    Chen YL; Li QZ
    J Theor Biol; 2007 Apr; 245(4):775-83. PubMed ID: 17189644
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Predicting subcellular location of apoptosis proteins based on wavelet transform and support vector machine.
    Qiu JD; Luo SH; Huang JH; Sun XY; Liang RP
    Amino Acids; 2010 Apr; 38(4):1201-8. PubMed ID: 19653066
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A novel representation for apoptosis protein subcellular localization prediction using support vector machine.
    Zhang L; Liao B; Li D; Zhu W
    J Theor Biol; 2009 Jul; 259(2):361-5. PubMed ID: 19328812
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Prediction of subcellular location apoptosis proteins with ensemble classifier and feature selection.
    Gu Q; Ding YS; Jiang XY; Zhang TL
    Amino Acids; 2010 Apr; 38(4):975-83. PubMed ID: 19048186
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Prediction of protein homo-oligomer types by pseudo amino acid composition: Approached with an improved feature extraction and Naive Bayes Feature Fusion.
    Zhang SW; Pan Q; Zhang HC; Shao ZC; Shi JY
    Amino Acids; 2006 Jun; 30(4):461-8. PubMed ID: 16773245
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Predicting subcellular location of apoptosis proteins with pseudo amino acid composition: approach from amino acid substitution matrix and auto covariance transformation.
    Yu X; Zheng X; Liu T; Dou Y; Wang J
    Amino Acids; 2012 May; 42(5):1619-25. PubMed ID: 21344173
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Support vector machines for prediction of protein subcellular location.
    Cai YD; Liu XJ; Xu XB; Chou KC
    Mol Cell Biol Res Commun; 2000 Oct; 4(4):230-3. PubMed ID: 11409917
    [TBL] [Abstract][Full Text] [Related]  

  • 12. [Classification of multi-class homo-oligomer based on a novel method of feature extraction from protein primary structure].
    Zhang S; Pan Q; Zhao C; Cheng Y
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2007 Aug; 24(4):721-6. PubMed ID: 17899731
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Prediction of protein subcellular location using a combined feature of sequence.
    Gao QB; Wang ZZ; Yan C; Du YH
    FEBS Lett; 2005 Jun; 579(16):3444-8. PubMed ID: 15949806
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Prediction of subcellular localization of eukaryotic proteins using position-specific profiles and neural network with weighted inputs.
    Zou L; Wang Z; Huang J
    J Genet Genomics; 2007 Dec; 34(12):1080-7. PubMed ID: 18155620
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Prediction of protein subcellular localization by support vector machines using multi-scale energy and pseudo amino acid composition.
    Shi JY; Zhang SW; Pan Q; Cheng YM; Xie J
    Amino Acids; 2007 Jul; 33(1):69-74. PubMed ID: 17235454
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Prediction of protein structure class by coupling improved genetic algorithm and support vector machine.
    Li ZC; Zhou XB; Lin YR; Zou XY
    Amino Acids; 2008 Oct; 35(3):581-90. PubMed ID: 18427714
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Protein subcellular localization prediction using a hybrid of similarity search and error-correcting output code techniques that produces interpretable results.
    Doderer M; Yoon K; Salinas J; Kwek S
    In Silico Biol; 2006; 6(5):419-33. PubMed ID: 17274771
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Using Nearest Feature Line and Tunable Nearest Neighbor methods for prediction of protein subcellular locations.
    Gao QB; Wang ZZ
    Comput Biol Chem; 2005 Oct; 29(5):388-92. PubMed ID: 16213794
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Prediction of subcellular location of apoptosis proteins combining tri-gram encoding based on PSSM and recursive feature elimination.
    Liu T; Tao P; Li X; Qin Y; Wang C
    J Theor Biol; 2015 Feb; 366():8-12. PubMed ID: 25463695
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Protein location prediction using atomic composition and global features of the amino acid sequence.
    Cherian BS; Nair AS
    Biochem Biophys Res Commun; 2010 Jan; 391(4):1670-4. PubMed ID: 20036215
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.