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

255 related items for PubMed ID: 22316312

  • 1. Identifying GPCRs and their types with Chou's pseudo amino acid composition: an approach from multi-scale energy representation and position specific scoring matrix.
    Zia-Ur-Rehman, Khan A.
    Protein Pept Lett; 2012 Aug; 19(8):890-903. PubMed ID: 22316312
    [Abstract] [Full Text] [Related]

  • 2. GPCR-MPredictor: multi-level prediction of G protein-coupled receptors using genetic ensemble.
    Naveed M, Khan A.
    Amino Acids; 2012 May; 42(5):1809-23. PubMed ID: 21505826
    [Abstract] [Full Text] [Related]

  • 3. Prediction of G-protein-coupled receptor classes based on the concept of Chou's pseudo amino acid composition: an approach from discrete wavelet transform.
    Qiu JD, Huang JH, Liang RP, Lu XQ.
    Anal Biochem; 2009 Jul 01; 390(1):68-73. PubMed ID: 19364489
    [Abstract] [Full Text] [Related]

  • 4. G-protein-coupled receptor prediction using pseudo-amino-acid composition and multiscale energy representation of different physiochemical properties.
    Ur-Rehman Z, Khan A.
    Anal Biochem; 2011 May 15; 412(2):173-82. PubMed ID: 21295004
    [Abstract] [Full Text] [Related]

  • 5. Prediction of Protein Submitochondrial Locations by Incorporating Dipeptide Composition into Chou's General Pseudo Amino Acid Composition.
    Ahmad K, Waris M, Hayat M.
    J Membr Biol; 2016 Jun 15; 249(3):293-304. PubMed ID: 26746980
    [Abstract] [Full Text] [Related]

  • 6. Prediction of protein subcellular localization with oversampling approach and Chou's general PseAAC.
    Zhang S, Duan X.
    J Theor Biol; 2018 Jan 21; 437():239-250. PubMed ID: 29100918
    [Abstract] [Full Text] [Related]

  • 7. Predicting protein submitochondrial locations by incorporating the pseudo-position specific scoring matrix into the general Chou's pseudo-amino acid composition.
    Qiu W, Li S, Cui X, Yu Z, Wang M, Du J, Peng Y, Yu B.
    J Theor Biol; 2018 Aug 07; 450():86-103. PubMed ID: 29678694
    [Abstract] [Full Text] [Related]

  • 8. Dual-layer wavelet SVM for predicting protein structural class via the general form of Chou's pseudo amino acid composition.
    Chen C, Shen ZB, Zou XY.
    Protein Pept Lett; 2012 Apr 07; 19(4):422-9. PubMed ID: 22185506
    [Abstract] [Full Text] [Related]

  • 9. Prediction of membrane proteins using split amino acid and ensemble classification.
    Hayat M, Khan A, Yeasin M.
    Amino Acids; 2012 Jun 07; 42(6):2447-60. PubMed ID: 21850437
    [Abstract] [Full Text] [Related]

  • 10. An improved classification of G-protein-coupled receptors using sequence-derived features.
    Peng ZL, Yang JY, Chen X.
    BMC Bioinformatics; 2010 Aug 09; 11():420. PubMed ID: 20696050
    [Abstract] [Full Text] [Related]

  • 11. Classification of G-protein coupled receptors at four levels.
    Gao QB, Wang ZZ.
    Protein Eng Des Sel; 2006 Nov 09; 19(11):511-6. PubMed ID: 17032692
    [Abstract] [Full Text] [Related]

  • 12. Predicting membrane protein types by fusing composite protein sequence features into pseudo amino acid composition.
    Hayat M, Khan A.
    J Theor Biol; 2011 Feb 21; 271(1):10-7. PubMed ID: 21110985
    [Abstract] [Full Text] [Related]

  • 13. Prediction of GPCRs with pseudo amino acid composition: employing composite features and grey incidence degree based classification.
    Zia-Ur-Rehman, Khan A.
    Protein Pept Lett; 2011 Sep 21; 18(9):872-8. PubMed ID: 21443502
    [Abstract] [Full Text] [Related]

  • 14. Predict protein structural class by incorporating two different modes of evolutionary information into Chou's general pseudo amino acid composition.
    Liang Y, Zhang S.
    J Mol Graph Model; 2017 Nov 21; 78():110-117. PubMed ID: 29055184
    [Abstract] [Full Text] [Related]

  • 15. Classification of G-protein coupled receptors based on support vector machine with maximum relevance minimum redundancy and genetic algorithm.
    Li Z, Zhou X, Dai Z, Zou X.
    BMC Bioinformatics; 2010 Jun 16; 11():325. PubMed ID: 20550715
    [Abstract] [Full Text] [Related]

  • 16. Classification of membrane protein types using Voting Feature Interval in combination with Chou's Pseudo Amino Acid Composition.
    Ali F, Hayat M.
    J Theor Biol; 2015 Nov 07; 384():78-83. PubMed ID: 26297889
    [Abstract] [Full Text] [Related]

  • 17. Prediction of protein subcellular multi-localization based on the general form of Chou's pseudo amino acid composition.
    Li LQ, Zhang Y, Zou LY, Zhou Y, Zheng XQ.
    Protein Pept Lett; 2012 Apr 07; 19(4):375-87. PubMed ID: 22185507
    [Abstract] [Full Text] [Related]

  • 18. A novel fractal approach for predicting G-protein-coupled receptors and their subfamilies with support vector machines.
    Nie G, Li Y, Wang F, Wang S, Hu X.
    Biomed Mater Eng; 2015 Apr 07; 26 Suppl 1():S1829-36. PubMed ID: 26405954
    [Abstract] [Full Text] [Related]

  • 19. Using ensemble SVM to identify human GPCRs N-linked glycosylation sites based on the general form of Chou's PseAAC.
    Xie HL, Fu L, Nie XD.
    Protein Eng Des Sel; 2013 Nov 07; 26(11):735-42. PubMed ID: 24048266
    [Abstract] [Full Text] [Related]

  • 20. iMem-2LSAAC: A two-level model for discrimination of membrane proteins and their types by extending the notion of SAAC into chou's pseudo amino acid composition.
    Arif M, Hayat M, Jan Z.
    J Theor Biol; 2018 Apr 07; 442():11-21. PubMed ID: 29337263
    [Abstract] [Full Text] [Related]

    Page: [Next] [New Search]
    of 13.