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 *

280 related articles for article (PubMed ID: 21458999)

  • 41. Correlation of human jejunal permeability (in vivo) of drugs with experimentally and theoretically derived parameters. A multivariate data analysis approach.
    Winiwarter S; Bonham NM; Ax F; Hallberg A; Lennernäs H; Karlén A
    J Med Chem; 1998 Dec; 41(25):4939-49. PubMed ID: 9836611
    [TBL] [Abstract][Full Text] [Related]  

  • 42. In silico binary classification QSAR models based on 4D-fingerprints and MOE descriptors for prediction of hERG blockage.
    Su BH; Shen MY; Esposito EX; Hopfinger AJ; Tseng YJ
    J Chem Inf Model; 2010 Jul; 50(7):1304-18. PubMed ID: 20565102
    [TBL] [Abstract][Full Text] [Related]  

  • 43. MI-QSAR models for prediction of corneal permeability of organic compounds.
    Chen C; Yang J
    Acta Pharmacol Sin; 2006 Feb; 27(2):193-204. PubMed ID: 16412269
    [TBL] [Abstract][Full Text] [Related]  

  • 44. Prediction of hepatic microsomal intrinsic clearance and human clearance values for drugs.
    Nikolic K; Agababa D
    J Mol Graph Model; 2009 Oct; 28(3):245-52. PubMed ID: 19713138
    [TBL] [Abstract][Full Text] [Related]  

  • 45. Skin permeation rate as a function of chemical structure.
    Katritzky AR; Dobchev DA; Fara DC; Hür E; Tämm K; Kurunczi L; Karelson M; Varnek A; Solov'ev VP
    J Med Chem; 2006 Jun; 49(11):3305-14. PubMed ID: 16722649
    [TBL] [Abstract][Full Text] [Related]  

  • 46. A QSAR model for predicting rejection of emerging contaminants (pharmaceuticals, endocrine disruptors) by nanofiltration membranes.
    Yangali-Quintanilla V; Sadmani A; McConville M; Kennedy M; Amy G
    Water Res; 2010 Jan; 44(2):373-84. PubMed ID: 19616272
    [TBL] [Abstract][Full Text] [Related]  

  • 47. Comparative QSAR- and fragments distribution analysis of drugs, druglikes, metabolic substances, and antimicrobial compounds.
    Karakoc E; Sahinalp SC; Cherkasov A
    J Chem Inf Model; 2006; 46(5):2167-82. PubMed ID: 16995747
    [TBL] [Abstract][Full Text] [Related]  

  • 48. NL MIND-BEST: a web server for ligands and proteins discovery--theoretic-experimental study of proteins of Giardia lamblia and new compounds active against Plasmodium falciparum.
    González-Díaz H; Prado-Prado F; Sobarzo-Sánchez E; Haddad M; Maurel Chevalley S; Valentin A; Quetin-Leclercq J; Dea-Ayuela MA; Teresa Gomez-Muños M; Munteanu CR; José Torres-Labandeira J; García-Mera X; Tapia RA; Ubeira FM
    J Theor Biol; 2011 May; 276(1):229-49. PubMed ID: 21277861
    [TBL] [Abstract][Full Text] [Related]  

  • 49. Predicting hERG activities of compounds from their 3D structures: development and evaluation of a global descriptors based QSAR model.
    Sinha N; Sen S
    Eur J Med Chem; 2011 Feb; 46(2):618-30. PubMed ID: 21185626
    [TBL] [Abstract][Full Text] [Related]  

  • 50. Unified QSAR approach to antimicrobials. 4. Multi-target QSAR modeling and comparative multi-distance study of the giant components of antiviral drug-drug complex networks.
    Prado-Prado FJ; Martinez de la Vega O; Uriarte E; Ubeira FM; Chou KC; González-Díaz H
    Bioorg Med Chem; 2009 Jan; 17(2):569-75. PubMed ID: 19112024
    [TBL] [Abstract][Full Text] [Related]  

  • 51. Combined 4D-fingerprint and clustering based membrane-interaction QSAR analyses for constructing consensus Caco-2 cell permeation virtual screens.
    Santos-Filho OA; Hopfinger AJ
    J Pharm Sci; 2008 Jan; 97(1):566-83. PubMed ID: 17696143
    [TBL] [Abstract][Full Text] [Related]  

  • 52. Three new consensus QSAR models for the prediction of Ames genotoxicity.
    Votano JR; Parham M; Hall LH; Kier LB; Oloff S; Tropsha A; Xie Q; Tong W
    Mutagenesis; 2004 Sep; 19(5):365-77. PubMed ID: 15388809
    [TBL] [Abstract][Full Text] [Related]  

  • 53. Development and validation of a robust QSAR model for prediction of carcinogenicity of drugs.
    Kar S; Roy K
    Indian J Biochem Biophys; 2011 Apr; 48(2):111-22. PubMed ID: 21682143
    [TBL] [Abstract][Full Text] [Related]  

  • 54. Computational prediction of oral drug absorption based on absorption rate constants in humans.
    Linnankoski J; Mäkelä JM; Ranta VP; Urtti A; Yliperttula M
    J Med Chem; 2006 Jun; 49(12):3674-81. PubMed ID: 16759110
    [TBL] [Abstract][Full Text] [Related]  

  • 55. Experimental modelling of drug membrane permeability by capillary electrophoresis using liposomes, micelles and microemulsions.
    Ornskov E; Gottfries J; Erickson M; Folestad S
    J Pharm Pharmacol; 2005 Apr; 57(4):435-42. PubMed ID: 15831203
    [TBL] [Abstract][Full Text] [Related]  

  • 56. Antiprotozoan lead discovery by aligning dry and wet screening: prediction, synthesis, and biological assay of novel quinoxalinones.
    Martins Alho MA; Marrero-Ponce Y; Barigye SJ; Meneses-Marcel A; Machado Tugores Y; Montero-Torres A; Gómez-Barrio A; Nogal JJ; García-Sánchez RN; Vega MC; Rolón M; Martínez-Fernández AR; Escario JA; Pérez-Giménez F; Garcia-Domenech R; Rivera N; Mondragón R; Mondragón M; Ibarra-Velarde F; Lopez-Arencibia A; Martín-Navarro C; Lorenzo-Morales J; Cabrera-Serra MG; Piñero J; Tytgat J; Chicharro R; Arán VJ
    Bioorg Med Chem; 2014 Mar; 22(5):1568-85. PubMed ID: 24513185
    [TBL] [Abstract][Full Text] [Related]  

  • 57. 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]  

  • 58. Predicting myelosuppression of drugs from in silico models.
    Crivori P; Pennella G; Magistrelli M; Grossi P; Giusti AM
    J Chem Inf Model; 2011 Feb; 51(2):434-45. PubMed ID: 21275392
    [TBL] [Abstract][Full Text] [Related]  

  • 59. In vitro testing of drug absorption for drug 'developability' assessment: forming an interface between in vitro preclinical data and clinical outcome.
    Sun D; Yu LX; Hussain MA; Wall DA; Smith RL; Amidon GL
    Curr Opin Drug Discov Devel; 2004 Jan; 7(1):75-85. PubMed ID: 14982151
    [TBL] [Abstract][Full Text] [Related]  

  • 60. QSAR and ADME.
    Hansch C; Leo A; Mekapati SB; Kurup A
    Bioorg Med Chem; 2004 Jun; 12(12):3391-400. PubMed ID: 15158808
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 14.