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    Results: 1 to 20 of 117

    2.

    Predicting multiple binding modes using a kernel method based on a vector space model molecular descriptor.

    Burkowski FJ, Wong WW.

    Int J Comput Biol Drug Des. 2009;2(1):58-80.

    PMID:
    20054986
    [PubMed - indexed for MEDLINE]
    3.

    Molecule kernels: a descriptor- and alignment-free quantitative structure-activity relationship approach.

    Mohr JA, Jain BJ, Obermayer K.

    J Chem Inf Model. 2008 Sep;48(9):1868-81. Epub 2008 Sep 4.

    PMID:
    18767832
    [PubMed - indexed for MEDLINE]
    4.

    Using kernel alignment to select features of molecular descriptors in a QSAR study.

    Wong WW, Burkowski FJ.

    IEEE/ACM Trans Comput Biol Bioinform. 2011 Sep-Oct;8(5):1373-84.

    PMID:
    21339534
    [PubMed - indexed for MEDLINE]
    5.

    Developing a methodology for an inverse quantitative structure-activity relationship using the signature molecular descriptor.

    Visco DP Jr, Pophale RS, Rintoul MD, Faulon JL.

    J Mol Graph Model. 2002 Jun;20(6):429-38.

    PMID:
    12071277
    [PubMed - indexed for MEDLINE]
    6.

    Combinatorial QSAR modeling of P-glycoprotein substrates.

    de Cerqueira Lima P, Golbraikh A, Oloff S, Xiao Y, Tropsha A.

    J Chem Inf Model. 2006 May-Jun;46(3):1245-54.

    PMID:
    16711744
    [PubMed - indexed for MEDLINE]
    7.

    QNA-based 'Star Track' QSAR approach.

    Filimonov DA, Zakharov AV, Lagunin AA, Poroikov VV.

    SAR QSAR Environ Res. 2009 Oct;20(7-8):679-709.

    PMID:
    20024804
    [PubMed - indexed for MEDLINE]
    8.

    The signature molecular descriptor. 3. Inverse-quantitative structure-activity relationship of ICAM-1 inhibitory peptides.

    Churchwell CJ, Rintoul MD, Martin S, Visco DP Jr, Kotu A, Larson RS, Sillerud LO, Brown DC, Faulon JL.

    J Mol Graph Model. 2004 Mar;22(4):263-73.

    PMID:
    15177078
    [PubMed - indexed for MEDLINE]
    9.

    Radial basis function network-based transform for a nonlinear support vector machine as optimized by a particle swarm optimization algorithm with application to QSAR studies.

    Tang LJ, Zhou YP, Jiang JH, Zou HY, Wu HL, Shen GL, Yu RQ.

    J Chem Inf Model. 2007 Jul-Aug;47(4):1438-45. Epub 2007 Jun 8.

    PMID:
    17555309
    [PubMed - indexed for MEDLINE]
    10.

    Quantitative structure-activity relationship modeling of juvenile hormone mimetic compounds for Culex pipiens larvae, with a discussion of descriptor-thinning methods.

    Basak SC, Natarajan R, Mills D, Hawkins DM, Kraker JJ.

    J Chem Inf Model. 2006 Jan-Feb;46(1):65-77.

    PMID:
    16426041
    [PubMed - indexed for MEDLINE]
    11.

    Stochastic versus stepwise strategies for quantitative structure-activity relationship generation--how much effort may the mining for successful QSAR models take?

    Horvath D, Bonachera F, Solov'ev V, Gaudin C, Varnek A.

    J Chem Inf Model. 2007 May-Jun;47(3):927-39. Epub 2007 May 5.

    PMID:
    17480052
    [PubMed - indexed for MEDLINE]
    12.

    Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data.

    Zhao X, Cheung LW.

    BMC Bioinformatics. 2007 Feb 28;8:67.

    PMID:
    17328811
    [PubMed - indexed for MEDLINE]
    Free PMC Article
    13.

    Input space versus feature space in kernel-based methods.

    Schölkopf B, Mika S, Burges CC, Knirsch P, Müller KR, Rätsch G, Smola AJ.

    IEEE Trans Neural Netw. 1999;10(5):1000-17.

    PMID:
    18252603
    [PubMed]
    14.

    Combinatorial QSAR of ambergris fragrance compounds.

    Kovatcheva A, Golbraikh A, Oloff S, Xiao YD, Zheng W, Wolschann P, Buchbauer G, Tropsha A.

    J Chem Inf Comput Sci. 2004 Mar-Apr;44(2):582-95.

    PMID:
    15032539
    [PubMed - indexed for MEDLINE]
    15.

    Genetic algorithms and self-organizing maps: a powerful combination for modeling complex QSAR and QSPR problems.

    Bayram E, Santago P 2nd, Harris R, Xiao YD, Clauset AJ, Schmitt JD.

    J Comput Aided Mol Des. 2004 Jul-Sep;18(7-9):483-93.

    PMID:
    15729848
    [PubMed - indexed for MEDLINE]
    16.

    kScore: a novel machine learning approach that is not dependent on the data structure of the training set.

    Oloff S, Muegge I.

    J Comput Aided Mol Des. 2007 Jan-Mar;21(1-3):87-95. Epub 2007 Feb 28.

    PMID:
    17333481
    [PubMed - indexed for MEDLINE]
    17.

    Application of MOLMAP approach for QSAR modeling of various biological activities using substituent electronic descriptors.

    Hemmateenejad B, Mehdipour AR, Miri R, Shamsipur M.

    J Comput Chem. 2009 Oct;30(13):2001-9.

    PMID:
    19130500
    [PubMed - indexed for MEDLINE]
    18.

    Ensemble feature selection: consistent descriptor subsets for multiple QSAR models.

    Dutta D, Guha R, Wild D, Chen T.

    J Chem Inf Model. 2007 May-Jun;47(3):989-97. Epub 2007 Apr 4.

    PMID:
    17407280
    [PubMed - indexed for MEDLINE]
    19.

    Electronic van der Waals surface property descriptors and genetic algorithms for developing structure-activity correlations in olfactory databases.

    Lavine BK, Davidson CE, Breneman C, Katt W.

    J Chem Inf Comput Sci. 2003 Nov-Dec;43(6):1890-905.

    PMID:
    14632438
    [PubMed]
    20.

    LQTA-QSAR: a new 4D-QSAR methodology.

    Martins JP, Barbosa EG, Pasqualoto KF, Ferreira MM.

    J Chem Inf Model. 2009 Jun;49(6):1428-36.

    PMID:
    19422246
    [PubMed - indexed for MEDLINE]

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