312
D. Wang
11. Liu J, Mansouri K, Judson RS, Martin MT, Hong H, Chen M, Xu X, Thomas RS, Shah I (2015)
Predicting hepatotoxicity using ToxCast in vitro bioactivity and chemical structure. Chem Res
Toxicol 28(4):738–751
12. Huang R, Xia M, Sakamuru S, Zhao J, Shahane SA, Attene-Ramos M, Zhao T, Austin CP,
Simeonov A (2016) Modelling the Tox21 10K chemical profiles for in vivo toxicity prediction and mechanism characterization. Nat Commun 7:10425. https://doi.org/10.1038/
ncomms10425
13. Kleinstreuer N, Ceger P, Watt E, Martin M, Houck K, Browne P, Thomas R, Casey W,
Dix D, Allen D, Sakamuru S, Xia M, Huang R, Judson R (2017) Development and validation
of a computational model for androgen receptor activity. Chem Res Toxicol 30(4):946–964
14. Ankley GT, Bennett RS, Erickson RJ, Hoff DJ, Hornung MW, Johnson RD et al (2010) Adverse
outcome pathways: a conceptual framework to support ecotoxicology research and risk assessment. Environ Toxicol Chem 29(3):730–741
15. Villeneuve DL, Crump D, Garcia-Reyero N, Hecker M, Hutchinson TH et al (2014) Adverse
outcome pathway (AOP) development I: strategies and principles. Toxicol Sci 142(2):312–320
16. Thomas RS, Allen BC, Nong A, Yang L, Bermudez E, Clewell HJ III, Andersen ME (2007)
A method to integrate benchmark dose estimates with genomic data to assess the functional
effects of chemical exposure. Toxicol Sci 98(1):240–248
17. Thomas RS, Wesselkamper SC, Wang NCY, Zhao QJ, Petersen DD et al (2013) Temporal concordance between apical and transcriptional points of departure for chemical risk assessment.
Toxicol Sci 134(1):180–194
18. Yang L, Allen BC, Thomas RS (2007) BMDExpress: a software tool for the benchmark dose
analyses of genomic data. BMC Genom 8(1):387
19. Irizarry RA, Hobbs B, Collin F, Beazer-Barclay YD, Antonellis KJ, Scherf U, Speed TP (2003)
Exploration, normalization, and summaries of high density oligonucleotide array probe level
data. Biostatistics 4(2):249–264
20. Farmahin R, Williams A, Kuo B, Chepelev NL, Thomas RS, Barton-Maclaren TS, Curran
IH, Nong A, Wade MG, Yauk CL (2017) Recommended approaches in the application of
toxicogenomics to derive points of departure for chemical risk assessment. Arch Toxicol
91(5):2045–2065
21. Kodell RL (2009) Replace the NOAEL and LOAEL with the BMDL01 and BMDL10. Environ
Ecol Stat 16(1):3–12
22. National Toxicology Program (2018) NTP research report on national toxicology program
approach to genomic dose-response modeling. U.S. Department of Health and Human Services,
Washington, DC
23. Zhou YH, Cichocki JA, Soldatow VY, Scholl EH, Gallins PJ, Jima D et al (2017) Comparative dose-response analysis of liver and kidney transcriptomic effects of trichloroethylene and
tetrachloroethylene in B6C3F1 mouse. Toxicol Sci 160(1):95–110
24. Black MB, Parks BB, Pluta L, Chu TM, Allen BC, Wolfinger RD, Thomas RS (2014) Comparison of microarrays and RNA-seq for gene expression analyses of dose-response experiments.
Toxicol Sci 137(2):385–403
25. Robinson MD, McCarthy DJ, Smyth GK (2010) edgeR: a Bioconductor package for differential
expression analysis of digital gene expression data. Bioinformatics 26(1):139–140
26. Anders S, Huber W (2010) Differential expression analysis for sequence count data. Genome
Biol 11(10):R106. https://doi.org/10.1186/gb-2010-11-10-r106, http://genomebiology.com/
2010/11/10/R106/
27. Crump K (2002) Critical issues in benchmark calculations from continuous data. Crit Rev
Toxicol 32(3):133–153
28. Law CW, Chen Y, Shi W, Smyth GK (2014) Voom: precision weights unlock linear model
analysis tools for RNA-seq read counts. Genome Biol 15(2):R29. http://genomebiology.com/
2014/15/2/R29
29. Liberzon A, Birger C, Thorvaldsdóttir H, Ghandi M, Mesirov JP, Tamayo P (2015) The molecular signatures database hallmark gene set collection. Cell Syst 1(6):417–425
D. Wang
11. Liu J, Mansouri K, Judson RS, Martin MT, Hong H, Chen M, Xu X, Thomas RS, Shah I (2015)
Predicting hepatotoxicity using ToxCast in vitro bioactivity and chemical structure. Chem Res
Toxicol 28(4):738–751
12. Huang R, Xia M, Sakamuru S, Zhao J, Shahane SA, Attene-Ramos M, Zhao T, Austin CP,
Simeonov A (2016) Modelling the Tox21 10K chemical profiles for in vivo toxicity prediction and mechanism characterization. Nat Commun 7:10425. https://doi.org/10.1038/
ncomms10425
13. Kleinstreuer N, Ceger P, Watt E, Martin M, Houck K, Browne P, Thomas R, Casey W,
Dix D, Allen D, Sakamuru S, Xia M, Huang R, Judson R (2017) Development and validation
of a computational model for androgen receptor activity. Chem Res Toxicol 30(4):946–964
14. Ankley GT, Bennett RS, Erickson RJ, Hoff DJ, Hornung MW, Johnson RD et al (2010) Adverse
outcome pathways: a conceptual framework to support ecotoxicology research and risk assessment. Environ Toxicol Chem 29(3):730–741
15. Villeneuve DL, Crump D, Garcia-Reyero N, Hecker M, Hutchinson TH et al (2014) Adverse
outcome pathway (AOP) development I: strategies and principles. Toxicol Sci 142(2):312–320
16. Thomas RS, Allen BC, Nong A, Yang L, Bermudez E, Clewell HJ III, Andersen ME (2007)
A method to integrate benchmark dose estimates with genomic data to assess the functional
effects of chemical exposure. Toxicol Sci 98(1):240–248
17. Thomas RS, Wesselkamper SC, Wang NCY, Zhao QJ, Petersen DD et al (2013) Temporal concordance between apical and transcriptional points of departure for chemical risk assessment.
Toxicol Sci 134(1):180–194
18. Yang L, Allen BC, Thomas RS (2007) BMDExpress: a software tool for the benchmark dose
analyses of genomic data. BMC Genom 8(1):387
19. Irizarry RA, Hobbs B, Collin F, Beazer-Barclay YD, Antonellis KJ, Scherf U, Speed TP (2003)
Exploration, normalization, and summaries of high density oligonucleotide array probe level
data. Biostatistics 4(2):249–264
20. Farmahin R, Williams A, Kuo B, Chepelev NL, Thomas RS, Barton-Maclaren TS, Curran
IH, Nong A, Wade MG, Yauk CL (2017) Recommended approaches in the application of
toxicogenomics to derive points of departure for chemical risk assessment. Arch Toxicol
91(5):2045–2065
21. Kodell RL (2009) Replace the NOAEL and LOAEL with the BMDL01 and BMDL10. Environ
Ecol Stat 16(1):3–12
22. National Toxicology Program (2018) NTP research report on national toxicology program
approach to genomic dose-response modeling. U.S. Department of Health and Human Services,
Washington, DC
23. Zhou YH, Cichocki JA, Soldatow VY, Scholl EH, Gallins PJ, Jima D et al (2017) Comparative dose-response analysis of liver and kidney transcriptomic effects of trichloroethylene and
tetrachloroethylene in B6C3F1 mouse. Toxicol Sci 160(1):95–110
24. Black MB, Parks BB, Pluta L, Chu TM, Allen BC, Wolfinger RD, Thomas RS (2014) Comparison of microarrays and RNA-seq for gene expression analyses of dose-response experiments.
Toxicol Sci 137(2):385–403
25. Robinson MD, McCarthy DJ, Smyth GK (2010) edgeR: a Bioconductor package for differential
expression analysis of digital gene expression data. Bioinformatics 26(1):139–140
26. Anders S, Huber W (2010) Differential expression analysis for sequence count data. Genome
Biol 11(10):R106. https://doi.org/10.1186/gb-2010-11-10-r106, http://genomebiology.com/
2010/11/10/R106/
27. Crump K (2002) Critical issues in benchmark calculations from continuous data. Crit Rev
Toxicol 32(3):133–153
28. Law CW, Chen Y, Shi W, Smyth GK (2014) Voom: precision weights unlock linear model
analysis tools for RNA-seq read counts. Genome Biol 15(2):R29. http://genomebiology.com/
2014/15/2/R29
29. Liberzon A, Birger C, Thorvaldsdóttir H, Ghandi M, Mesirov JP, Tamayo P (2015) The molecular signatures database hallmark gene set collection. Cell Syst 1(6):417–425