Biomedical Engineering Reference
In-Depth Information
47. Ekins S , Williams AJ . When pharmaceutical companies publish large datasets: An
abundance of riches or fool's gold? Drug Discov Today 2010 ; 15 : 812 - 815 .
48. Tapscott D , Williams AJ . Wikinomics: How Mass Collaboration Changes Everything .
New York : Portfolio , 2006 .
49. Louise - May S , Bunin B , Ekins S . Towards integrated web - based tools in drug dis-
covery . Touch Brief Drug Discov 2009 ; 6 : 17 - 21 .
50. Southan C , Varkonyi P , Muresan S . Quantitative assessment of the expanding
complementarity between public and commercial databases of bioactive com-
pounds . J Cheminform 2009 ; 1 : 10 .
51. Ma ' ayan A , Jenkins SL , Goldfarb J , Iyengar R . Network analysis of FDA approved
drugs and their targets. Mount Sinai J Med New York 2007 ; 74 : 27 - 32 .
52. Shah NH , Jonquet C , Chiang AP , Butte AJ , Chen R , Musen MA . Ontology - driven
indexing of public datasets for translational bioinformatics. BMC Bioinform
2009 ; 10 (Suppl 2 ): S1 .
53. Washington NL , Haendel MA , Mungall CJ , Ashburner M , Westerfi eld M , Lewis SE .
Linking human diseases to animal models using ontology-based phenotype annota-
tion . PLoS Biol 2009 ; 7 : e1000247 .
54. Walters WP , Murcko MA . Prediction of “ drug - likeness. ” Adv Drug Del Rev
2002 ; 54 : 255 - 271 .
55. Hann M , Hudson B , Lewell X , Lifely R , Miller L , Ramsden N . Strategic pooling of
compounds
for
high - throughput
screening .
J Chem Inf Comput Sci
1999 ; 39 :
897 - 902 .
56. Pearce BC , Sofi a MJ , Good AC , Drexler DM , Stock DA . An empirical process for
the design of high-throughput screening deck fi lters. J Chem Inf Model 2006 ;
46 : 1060 - 1068 .
57. Huth JR , Mendoza R , Olejniczak ET , Johnson RW , Cothron DA , Liu Y . ALARM
NMR: A rapid and robust experimental method to detect reactive false positives
in biochemical screens. J Am Chem Soc 2005 ; 127 : 217 - 224 .
58. Huth JR , Song D , Mendoza RR , Black - Schaefer CL , Mack JC , Dorwin SA .
Toxicological evaluation of thiol-reactive compounds identifi ed using a la assay to
detect reactive molecules by nuclear magnetic resonance. Chem Res Toxicol 2007 ;
20 : 1752 - 1759 .
59. Metz JT , Huth JR , Hajduk PJ . Enhancement of chemical rules for predicting com-
pound reactivity towards protein thiol groups. J Comput Aided Mol Des 2007 ; 21 :
139 - 144 .
60. Baell JB , Holloway GA . New substructure fi lters for removal of pan assay interfer-
ence compounds (PAINS) from screening libraries and for their exclusion in bioas-
says . J Med Chem 2010 ; 53 : 2719 - 2740 .
61. Bryson CJ , Jones TD , Baker MP . Prediction of immunogenicity of therapeutic pro-
teins: Validity of computational tools. BioDrugs 2010 ; 24 : 1 - 8 .
62. De Groot AS , McMurry J , Moise L . Prediction of immunogenicity: In Silico para-
digms, ex vivo and in vivo correlates. Current Opin Pharmacol 2008 ; 8 : 620 - 626 .
63. Tung CW , Ho SY . POPI: Predicting immunogenicity of MHC class I binding pep-
tides by mining informative physicochemical properties. Bioinformatics 2007 ; 23 :
942 - 949 .
Search WWH ::




Custom Search