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 *

129 related articles for article (PubMed ID: 16426075)

  • 21. A fully computational model for predicting percutaneous drug absorption.
    Neumann D; Kohlbacher O; Merkwirth C; Lengauer T
    J Chem Inf Model; 2006; 46(1):424-9. PubMed ID: 16426076
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Gaussian processes for classification: QSAR modeling of ADMET and target activity.
    Obrezanova O; Segall MD
    J Chem Inf Model; 2010 Jun; 50(6):1053-61. PubMed ID: 20433177
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Graph kernels for molecular structure-activity relationship analysis with support vector machines.
    Mahé P; Ueda N; Akutsu T; Perret JL; Vert JP
    J Chem Inf Model; 2005; 45(4):939-51. PubMed ID: 16045288
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Rapid prediction of chemical metabolism by human UDP-glucuronosyltransferase isoforms using quantum chemical descriptors derived with the electronegativity equalization method.
    Sorich MJ; McKinnon RA; Miners JO; Winkler DA; Smith PA
    J Med Chem; 2004 Oct; 47(21):5311-7. PubMed ID: 15456275
    [TBL] [Abstract][Full Text] [Related]  

  • 25. A novel QSPR study of normalized migration time for drugs in capillary electrophoresis by new descriptors: quantum chemical investigation.
    Riahi S; Beheshti A; Ganjali MR; Norouzi P
    Electrophoresis; 2008 Oct; 29(19):4027-35. PubMed ID: 18958895
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Effect of selection of molecular descriptors on the prediction of blood-brain barrier penetrating and nonpenetrating agents by statistical learning methods.
    Li H; Yap CW; Ung CY; Xue Y; Cao ZW; Chen YZ
    J Chem Inf Model; 2005; 45(5):1376-84. PubMed ID: 16180914
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Emerging chemical patterns: a new methodology for molecular classification and compound selection.
    Auer J; Bajorath J
    J Chem Inf Model; 2006; 46(6):2502-14. PubMed ID: 17125191
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Statistical instance-based pruning in ensembles of independent classifiers.
    Hernández-Lobato D; Martínez-Muñoz G; Suárez A
    IEEE Trans Pattern Anal Mach Intell; 2009 Feb; 31(2):364-9. PubMed ID: 19110500
    [TBL] [Abstract][Full Text] [Related]  

  • 29. GA(M)E-QSAR: a novel, fully automatic genetic-algorithm-(meta)-ensembles approach for binary classification in ligand-based drug design.
    Pérez-Castillo Y; Lazar C; Taminau J; Froeyen M; Cabrera-Pérez MÁ; Nowé A
    J Chem Inf Model; 2012 Sep; 52(9):2366-86. PubMed ID: 22856471
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Can we estimate the accuracy of ADME-Tox predictions?
    Tetko IV; Bruneau P; Mewes HW; Rohrer DC; Poda GI
    Drug Discov Today; 2006 Aug; 11(15-16):700-7. PubMed ID: 16846797
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Linear dimensionality reduction via a heteroscedastic extension of LDA: the Chernoff criterion.
    Loog M; Duin RP
    IEEE Trans Pattern Anal Mach Intell; 2004 Jun; 26(6):732-9. PubMed ID: 18579934
    [TBL] [Abstract][Full Text] [Related]  

  • 32. In silico ADME modelling 2: computational models to predict human serum albumin binding affinity using ant colony systems.
    Gunturi SB; Narayanan R; Khandelwal A
    Bioorg Med Chem; 2006 Jun; 14(12):4118-29. PubMed ID: 16504519
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Towards integrated ADME prediction: past, present and future directions for modelling metabolism by UDP-glucuronosyltransferases.
    Smith PA; Sorich MJ; Low LS; McKinnon RA; Miners JO
    J Mol Graph Model; 2004 Jul; 22(6):507-17. PubMed ID: 15182810
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Development and validation of in silico models for estimating drug preformulation risk in PEG400/water and Tween80/water systems.
    Crivori P; Morelli A; Pezzetta D; Rocchetti M; Poggesi I
    Eur J Pharm Sci; 2007 Nov; 32(3):169-81. PubMed ID: 17714921
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Identifying P-glycoprotein substrates using a support vector machine optimized by a particle swarm.
    Huang J; Ma G; Muhammad I; Cheng Y
    J Chem Inf Model; 2007; 47(4):1638-47. PubMed ID: 17608407
    [TBL] [Abstract][Full Text] [Related]  

  • 36. A theoretical analysis of bagging as a linear combination of classifiers.
    Fumera G; Fabio R; Alessandra S
    IEEE Trans Pattern Anal Mach Intell; 2008 Jul; 30(7):1293-9. PubMed ID: 18550910
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Boosting random subspace method.
    García-Pedrajas N; Ortiz-Boyer D
    Neural Netw; 2008 Nov; 21(9):1344-62. PubMed ID: 18272334
    [TBL] [Abstract][Full Text] [Related]  

  • 38. 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. PubMed ID: 18767832
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Insolubility classification with accurate prediction probabilities using a MetaClassifier.
    Kramer C; Beck B; Clark T
    J Chem Inf Model; 2010 Mar; 50(3):404-14. PubMed ID: 20088498
    [TBL] [Abstract][Full Text] [Related]  

  • 40. An analysis of ensemble pruning techniques based on ordered aggregation.
    Martínez-Muñoz G; Hernández-Lobato D; Suárez A
    IEEE Trans Pattern Anal Mach Intell; 2009 Feb; 31(2):245-59. PubMed ID: 19110491
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 7.