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Items: 1 to 20 of 28

1.

Assessment of the DNA damaging potential of environmental chemicals using a quantitative high-throughput screening approach to measure p53 activation.

Witt KL, Hsieh JH, Smith-Roe SL, Xia M, Huang R, Zhao J, Auerbach SS, Hur J, Tice RR.

Environ Mol Mutagen. 2017 Aug;58(7):494-507. doi: 10.1002/em.22112. Epub 2017 Jul 17.

PMID:
28714573
2.

Real-time cell toxicity profiling of Tox21 10K compounds reveals cytotoxicity dependent toxicity pathway linkage.

Hsieh JH, Huang R, Lin JA, Sedykh A, Zhao J, Tice RR, Paules RS, Xia M, Auerbach SS.

PLoS One. 2017 May 22;12(5):e0177902. doi: 10.1371/journal.pone.0177902. eCollection 2017. Erratum in: PLoS One. 2017 Jul 7;12 (7):e0181291.

3.

Predictive Modeling of Estrogen Receptor Binding Agents Using Advanced Cheminformatics Tools and Massive Public Data.

Ribay K, Kim MT, Wang W, Pinolini D, Zhu H.

Front Environ Sci. 2016 Mar;4. pii: 12. Epub 2016 Mar 8.

4.

Getting the most out of PubChem for virtual screening.

Kim S.

Expert Opin Drug Discov. 2016 Sep;11(9):843-55. doi: 10.1080/17460441.2016.1216967. Epub 2016 Aug 5. Review.

5.

In vitro screening for population variability in toxicity of pesticide-containing mixtures.

Abdo N, Wetmore BA, Chappell GA, Shea D, Wright FA, Rusyn I.

Environ Int. 2015 Dec;85:147-55. doi: 10.1016/j.envint.2015.09.012. Epub 2015 Sep 19.

6.

Mechanism Profiling of Hepatotoxicity Caused by Oxidative Stress Using Antioxidant Response Element Reporter Gene Assay Models and Big Data.

Kim MT, Huang R, Sedykh A, Wang W, Xia M, Zhu H.

Environ Health Perspect. 2016 May;124(5):634-41. doi: 10.1289/ehp.1509763. Epub 2015 Sep 18.

7.

CHEMICAL AND BIOLOGICAL DESCRIPTOR INTEGRATION IMPROVES COMPUTATIONAL MODELING OF IN VIVO RAT TOXICITY.

Bologa CG, Ursu O, Halip L, Curp─ân R, Oprea TI.

Rev Roum Chim. 2015 Feb-Mar;60(2-3):219-226.

8.

Cell-Based High-Throughput Screening for Aromatase Inhibitors in the Tox21 10K Library.

Chen S, Hsieh JH, Huang R, Sakamuru S, Hsin LY, Xia M, Shockley KR, Auerbach S, Kanaya N, Lu H, Svoboda D, Witt KL, Merrick BA, Teng CT, Tice RR.

Toxicol Sci. 2015 Oct;147(2):446-57. doi: 10.1093/toxsci/kfv141. Epub 2015 Jul 3.

9.

A Data Analysis Pipeline Accounting for Artifacts in Tox21 Quantitative High-Throughput Screening Assays.

Hsieh JH, Sedykh A, Huang R, Xia M, Tice RR.

J Biomol Screen. 2015 Aug;20(7):887-97. doi: 10.1177/1087057115581317. Epub 2015 Apr 22.

10.

Developing Enhanced Blood-Brain Barrier Permeability Models: Integrating External Bio-Assay Data in QSAR Modeling.

Wang W, Kim MT, Sedykh A, Zhu H.

Pharm Res. 2015 Sep;32(9):3055-65. doi: 10.1007/s11095-015-1687-1. Epub 2015 Apr 11.

11.

Building a robust 21st century chemical testing program at the U.S. Environmental Protection Agency: recommendations for strengthening scientific engagement.

McPartland J, Dantzker HC, Portier CJ.

Environ Health Perspect. 2015 Jan;123(1):1-5. doi: 10.1289/ehp.1408601. Epub 2014 Oct 24.

12.

Big data in chemical toxicity research: the use of high-throughput screening assays to identify potential toxicants.

Zhu H, Zhang J, Kim MT, Boison A, Sedykh A, Moran K.

Chem Res Toxicol. 2014 Oct 20;27(10):1643-51. doi: 10.1021/tx500145h. Epub 2014 Sep 16. Review.

13.

Prediction of binding affinity and efficacy of thyroid hormone receptor ligands using QSAR and structure-based modeling methods.

Politi R, Rusyn I, Tropsha A.

Toxicol Appl Pharmacol. 2014 Oct 1;280(1):177-89. doi: 10.1016/j.taap.2014.07.009. Epub 2014 Jul 21.

14.

Profiling animal toxicants by automatically mining public bioassay data: a big data approach for computational toxicology.

Zhang J, Hsieh JH, Zhu H.

PLoS One. 2014 Jun 20;9(6):e99863. doi: 10.1371/journal.pone.0099863. eCollection 2014.

15.

Design, synthesis and experimental validation of novel potential chemopreventive agents using random forest and support vector machine binary classifiers.

Sprague B, Shi Q, Kim MT, Zhang L, Sedykh A, Ichiishi E, Tokuda H, Lee KH, Zhu H.

J Comput Aided Mol Des. 2014 Jun;28(6):631-46. doi: 10.1007/s10822-014-9748-9. Epub 2014 May 20.

PMID:
24840854
16.
17.

THE INTERACTIVE DECISION COMMITTEE FOR CHEMICAL TOXICITY ANALYSIS.

Kang C, Zhu H, Wright FA, Zou F, Kosorok MR.

J Stat Res. 2012;46(2):157-186.

18.

QSAR modeling: where have you been? Where are you going to?

Cherkasov A, Muratov EN, Fourches D, Varnek A, Baskin II, Cronin M, Dearden J, Gramatica P, Martin YC, Todeschini R, Consonni V, Kuz'min VE, Cramer R, Benigni R, Yang C, Rathman J, Terfloth L, Gasteiger J, Richard A, Tropsha A.

J Med Chem. 2014 Jun 26;57(12):4977-5010. doi: 10.1021/jm4004285. Epub 2014 Jan 6.

19.

Integrative chemical-biological read-across approach for chemical hazard classification.

Low Y, Sedykh A, Fourches D, Golbraikh A, Whelan M, Rusyn I, Tropsha A.

Chem Res Toxicol. 2013 Aug 19;26(8):1199-208. doi: 10.1021/tx400110f. Epub 2013 Aug 5.

20.

Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR- and structure-based virtual screening approaches.

Zhang L, Sedykh A, Tripathi A, Zhu H, Afantitis A, Mouchlis VD, Melagraki G, Rusyn I, Tropsha A.

Toxicol Appl Pharmacol. 2013 Oct 1;272(1):67-76. doi: 10.1016/j.taap.2013.04.032. Epub 2013 May 23.

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