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Items: 1 to 20 of 118

1.

Sequencing XMET genes to promote genotype-guided risk assessment and precision medicine.

Jin Y, Chen G, Xiao W, Hong H, Xu J, Guo Y, Xiao W, Shi T, Shi L, Tong W, Ning B.

Sci China Life Sci. 2019 Jul;62(7):895-904. doi: 10.1007/s11427-018-9479-5. Epub 2019 May 20. Review.

2.

Correction to: Similarities and differences between variants called with human reference genome HG19 or HG38.

Pan B, Kusko R, Xiao W, Zheng Y, Liu Z, Xiao C, Sakkiah S, Guo W, Gong P, Zhang C, Ge W, Shi L, Tong W, Hong H.

BMC Bioinformatics. 2019 May 15;20(1):252. doi: 10.1186/s12859-019-2776-7.

3.

In silico identification of genetic mutations conferring resistance to acetohydroxyacid synthase inhibitors: A case study of Kochia scoparia.

Li Y, Netherland MD, Zhang C, Hong H, Gong P.

PLoS One. 2019 May 7;14(5):e0216116. doi: 10.1371/journal.pone.0216116. eCollection 2019.

4.

Similarities and differences between variants called with human reference genome HG19 or HG38.

Pan B, Kusko R, Xiao W, Zheng Y, Liu Z, Xiao C, Sakkiah S, Guo W, Gong P, Zhang C, Ge W, Shi L, Tong W, Hong H.

BMC Bioinformatics. 2019 Mar 14;20(Suppl 2):101. doi: 10.1186/s12859-019-2620-0. Erratum in: BMC Bioinformatics. 2019 May 15;20(1):252.

5.

Deep learning for predicting toxicity of chemicals: a mini review.

Tang W, Chen J, Wang Z, Xie H, Hong H.

J Environ Sci Health C Environ Carcinog Ecotoxicol Rev. 2018;36(4):252-271. doi: 10.1080/10590501.2018.1537563. Epub 2019 Mar 1. Review.

PMID:
30821199
6.

Computational prediction models for assessing endocrine disrupting potential of chemicals.

Sakkiah S, Guo W, Pan B, Kusko R, Tong W, Hong H.

J Environ Sci Health C Environ Carcinog Ecotoxicol Rev. 2018;36(4):192-218. doi: 10.1080/10590501.2018.1537132. Epub 2019 Jan 11. Review.

PMID:
30633647
7.

A review on machine learning methods for in silico toxicity prediction.

Idakwo G, Luttrell J, Chen M, Hong H, Zhou Z, Gong P, Zhang C.

J Environ Sci Health C Environ Carcinog Ecotoxicol Rev. 2018;36(4):169-191. doi: 10.1080/10590501.2018.1537118. Epub 2019 Jan 10. Review.

PMID:
30628866
8.

Comparative toxicogenomics of three insensitive munitions constituents 2,4-dinitroanisole, nitroguanidine and nitrotriazolone in the soil nematode Caenorhabditis elegans.

Gong P, Donohue KB, Mayo AM, Wang Y, Hong H, Wilbanks MS, Barker ND, Guan X, Gust KA.

BMC Syst Biol. 2018 Dec 14;12(Suppl 7):92. doi: 10.1186/s12918-018-0636-0.

9.

Quantum chemical simulations revealed the toxicokinetic mechanisms of organic phosphorus flame retardants catalyzed by P450 enzymes.

Fu Z, Chen J, Wang Y, Hong H, Xie H.

J Environ Sci Health C Environ Carcinog Ecotoxicol Rev. 2018;36(4):272-291. doi: 10.1080/10590501.2018.1537564. Epub 2018 Nov 20.

PMID:
30457030
10.

Target-specific toxicity knowledgebase (TsTKb): a novel toolkit for in silico predictive toxicology.

Li Y, Idakwo G, Thangapandian S, Chen M, Hong H, Zhang C, Gong P.

J Environ Sci Health C Environ Carcinog Ecotoxicol Rev. 2018;36(4):219-236. doi: 10.1080/10590501.2018.1537148. Epub 2018 Nov 14.

PMID:
30426823
11.

Application of genome analysis strategies in the clinical testing for pediatric diseases.

Jin Y, Zhang L, Ning B, Hong H, Xiao W, Tong W, Tao Y, Ni X, Shi T, Guo Y.

Pediatr Investig. 2018 Jul 16;2(2):72-81. doi: 10.1002/ped4.12044.

12.

Structural Changes Due to Antagonist Binding in Ligand Binding Pocket of Androgen Receptor Elucidated Through Molecular Dynamics Simulations.

Sakkiah S, Kusko R, Pan B, Guo W, Ge W, Tong W, Hong H.

Front Pharmacol. 2018 May 15;9:492. doi: 10.3389/fphar.2018.00492. eCollection 2018.

13.

In Silico Pharmacoepidemiologic Evaluation of Drug-Induced Cardiovascular Complications Using Combined Classifiers.

Cai C, Fang J, Guo P, Wang Q, Hong H, Moslehi J, Cheng F.

J Chem Inf Model. 2018 May 29;58(5):943-956. doi: 10.1021/acs.jcim.7b00641. Epub 2018 May 10.

14.

Competitive docking model for prediction of the human nicotinic acetylcholine receptor α7 binding of tobacco constituents.

Ng HW, Leggett C, Sakkiah S, Pan B, Ye H, Wu L, Selvaraj C, Tong W, Hong H.

Oncotarget. 2018 Feb 8;9(24):16899-16916. doi: 10.18632/oncotarget.24458. eCollection 2018 Mar 30.

15.

Deep learning architectures for multi-label classification of intelligent health risk prediction.

Maxwell A, Li R, Yang B, Weng H, Ou A, Hong H, Zhou Z, Gong P, Zhang C.

BMC Bioinformatics. 2017 Dec 28;18(Suppl 14):523. doi: 10.1186/s12859-017-1898-z.

16.

Endocrine Disrupting Chemicals Mediated through Binding Androgen Receptor Are Associated with Diabetes Mellitus.

Sakkiah S, Wang T, Zou W, Wang Y, Pan B, Tong W, Hong H.

Int J Environ Res Public Health. 2017 Dec 23;15(1). pii: E25. doi: 10.3390/ijerph15010025. Review.

17.

Development of Decision Forest Models for Prediction of Drug-Induced Liver Injury in Humans Using A Large Set of FDA-approved Drugs.

Hong H, Thakkar S, Chen M, Tong W.

Sci Rep. 2017 Dec 11;7(1):17311. doi: 10.1038/s41598-017-17701-7.

18.

Development of estrogen receptor beta binding prediction model using large sets of chemicals.

Sakkiah S, Selvaraj C, Gong P, Zhang C, Tong W, Hong H.

Oncotarget. 2017 Oct 10;8(54):92989-93000. doi: 10.18632/oncotarget.21723. eCollection 2017 Nov 3.

19.

Multiple microRNAs function as self-protective modules in acetaminophen-induced hepatotoxicity in humans.

Yu D, Wu L, Gill P, Tolleson WH, Chen S, Sun J, Knox B, Jin Y, Xiao W, Hong H, Wang Y, Ren Z, Guo L, Mei N, Guo Y, Yang X, Shi L, Chen Y, Zeng L, Dreval K, Tryndyak V, Pogribny I, Fang H, Shi T, McCullough S, Bhattacharyya S, Schnackenberg L, Mattes W, Beger RD, James L, Tong W, Ning B.

Arch Toxicol. 2018 Feb;92(2):845-858. doi: 10.1007/s00204-017-2090-y. Epub 2017 Oct 24.

20.

Direct comparison of performance of single nucleotide variant calling in human genome with alignment-based and assembly-based approaches.

Wu L, Yavas G, Hong H, Tong W, Xiao W.

Sci Rep. 2017 Sep 8;7(1):10963. doi: 10.1038/s41598-017-10826-9.

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