Quantitative high-throughput screening data analysis: Challenges and recent advances

Drug Discovery Today

Volumn 20, Issue 3, 2015, Pages 296-300

  Shockley, Keith R ^a  

^a NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPARATIVE STUDY; CONCENTRATION RESPONSE; CONFIDENCE INTERVAL; DATA ANALYSIS; GENOMICS; HIGH THROUGHPUT SCREENING; IN VITRO STUDY; PHARMACOGENOMICS; REVIEW; SIGNAL NOISE RATIO; STATISTICAL MODEL; STATISTICAL SIGNIFICANCE; STUDY DESIGN; TOXICITY TESTING; DRUG DEVELOPMENT; NONLINEAR SYSTEM; REGRESSION ANALYSIS; STATISTICAL ANALYSIS; STATISTICS AND NUMERICAL DATA;

DATA INTERPRETATION, STATISTICAL; DRUG DISCOVERY; HIGH-THROUGHPUT SCREENING ASSAYS; NONLINEAR DYNAMICS; REGRESSION ANALYSIS;

EID: 84925644591     PISSN: 13596446     EISSN: 18785832     Source Type: Journal    
DOI: 10.1016/j.drudis.2014.10.005     Document Type: Short Survey

References (30)

1. R. Macarron Critical review of the role of HTS in drug discovery Drug Discov. Today 11 2006 277 279
2. M.S. Attene-Ramos The Tox21 robotic platform for the assessment of environmental chemicals - from vision to reality Drug Discov. Today 18 2013 716 723
3. F.S. Collins Transforming environmental health protection Science 319 2008 906 907
4. N. Malo Statistical practice in high-throughput screening data analysis Nat. Biotechnol. 24 2006 167 175
5. J. Inglese Quantitative high-throughput screening: a titration-based approach that efficiently identifies biological activities in large chemical libraries Proc. Natl. Acad. Sci. U. S. A. 103 2006 11473 11478
6. B. Haibe-Kains Inconsistency in large pharmacogenomics studies Nature 504 2013 389 393
7. M.J. Garnett Systematic identification of genomic markers of drug sensitivity in cancer cells Nature 483 2012 570 575
8. J. Barretina The cancer cell line encyclopedia enables predictive modelling of anticancer drug sensitivity Nature 483 2012 603 607
9. R.S. Thomas. A comprehensive statistical analysis of predicting in vivo hazard using high-throughput in vitro screening Toxicol. Sci. 128 2012 398 417
10. R.R. Tice Improving the human hazard characterization of chemicals: a Tox21 update Environ. Health Perspect. 121 2013 756 765
11. 50s: towards robust statistical methods for in vitro association studies J. Pharmacogenomics Pharmacoproteomics 5 2014 1000121
12. A.V.J. Hill The possible effects of the aggregation of the molecules of haemoglobin on its dissociation curves J. Physiol. 40 1910 4 7
13. J.N. Weiss The Hill equation revisited: uses and misuses FASEB J. 11 1997 835 841
14. R. Reeve, and J.R. Turner Pharmacodynamic models: parameterizing the Hill equation, Michaelis-Menten, the logistic curve, and relationships among these models J. Biopharm. Stat. 24 2013 648 661
15. S. Goutelle The Hill equation: a review of its capabilities in pharmacological modelling Fundam. Clin. Pharmacol. 22 2008 633 648
16. S.D. Peddada, and J.K. Haseman Analysis of nonlinear regression models: a cautionary note Dose Response 3 2005 342 352
17. R.B. Conolly, and W.K. Lutz Nonmonotonic dose-response relationships: mechanistic basis, kinetic modeling, and implications for risk assessment Toxicol. Sci. 77 2004 151 157
18. C. Lim Robust analysis of high throughput screening (HTS) assay data Technometrics 55 2013 150 160
19. K.R. Shockley A three-stage algorithm to make toxicologically relevant activity calls from quantitative high throughput screening data Environ. Health Perspect. 120 2012 1107 1115
20. K.R. Shockley Using weighted entropy to rank chemicals in quantitative high-throughput screening experiments J. Biomol. Screen. 19 2014 344 353
21. G.A.F. Seber, and C.J. Wild Nonlinear Regression 1989 Wiley
22. J. Zhang Estimation of parameters in nonlinear regression models C.R. Rao, G. Szekely, Statistics for the 21st Century 2000 Marcel Dekker 459 483
23. Y. Benjamini, and D. Yekutieli False discovery rate-adjusted multiple confidence intervals for selected parameters J. Am. Stat. Assoc. 100 2005 71 81
24. V. Barnett, and T. Lewis Outliers in Statistical Data 1994 John Wiley & Sons
25. D.A. Ratkowsky Handbook of Nonlinear Regression Models 1990 Marcel Dekker
26. H. Jiang, and J. Salzman Statistical properties of an early stopping rule for resampling-based multiple testing Biometrika 99 2012 973 980
27. D.J. Dix Incorporating biological, chemical, and toxicological knowledge into predictive models of toxicity Toxicol. Sci. 130 2012 440 441
28. R.S. Thomas Response to incorporating biological, chemical, and toxicological knowledge into predictive models of toxicity Toxicol. Sci. 130 2012 442 443
29. M. Bezeau, and L. Endrenyi Design of experiments for the precise estimation of dose-response parameters: the Hill equation J. Theor. Biol. 123 1986 415 430
30. L.A. Khinkis Optimal design for estimating parameters of the 4-parameter Hill model Nonlinearity Biol. Toxicol. Med. 1 2003 363 377