Trinh TX - Search Results

1

Quasi-QSAR for predicting the cell viability of human lung and skin cells exposed to different metal oxide nanomaterials.

Choi JS, Trinh TX, Yoon TH, Kim J, Byun HG. Choi JS, et al. Among authors: trinh tx. Chemosphere. 2019 Feb;217:243-249. doi: 10.1016/j.chemosphere.2018.11.014. Epub 2018 Nov 3. Chemosphere. 2019. PMID: 30419378

2

Quasi-SMILES-Based Nano-Quantitative Structure-Activity Relationship Model to Predict the Cytotoxicity of Multiwalled Carbon Nanotubes to Human Lung Cells.

Trinh TX, Choi JS, Jeon H, Byun HG, Yoon TH, Kim J. Trinh TX, et al. Chem Res Toxicol. 2018 Mar 19;31(3):183-190. doi: 10.1021/acs.chemrestox.7b00303. Epub 2018 Feb 19. Chem Res Toxicol. 2018. PMID: 29439565

3

Towards a generalized toxicity prediction model for oxide nanomaterials using integrated data from different sources.

Choi JS, Ha MK, Trinh TX, Yoon TH, Byun HG. Choi JS, et al. Among authors: trinh tx. Sci Rep. 2018 Apr 17;8(1):6110. doi: 10.1038/s41598-018-24483-z. Sci Rep. 2018. PMID: 29666463 Free PMC article.

4

Implementation of Complementary Model using Optimal Combination of Hematological Parameters for Sepsis Screening in Patients with Fever.

Choi JS, Trinh TX, Ha J, Yang MS, Lee Y, Kim YE, Choi J, Byun HG, Song J, Yoon TH. Choi JS, et al. Among authors: trinh tx. Sci Rep. 2020 Jan 14;10(1):273. doi: 10.1038/s41598-019-57107-1. Sci Rep. 2020. PMID: 31937825 Free PMC article.

5

Status Quo in Data Availability and Predictive Models of Nano-Mixture Toxicity.

Trinh TX, Kim J. Trinh TX, et al. Nanomaterials (Basel). 2021 Jan 7;11(1):124. doi: 10.3390/nano11010124. Nanomaterials (Basel). 2021. PMID: 33430414 Free PMC article. Review.

6

Developing random forest based QSAR models for predicting the mixture toxicity of TiO₂ based nano-mixtures to Daphnia magna.

Trinh TX, Seo M, Yoon TH, Kim J. Trinh TX, et al. NanoImpact. 2022 Jan;25:100383. doi: 10.1016/j.impact.2022.100383. Epub 2022 Jan 21. NanoImpact. 2022. PMID: 35559889 Free article.

7

Toxicity Classification of Oxide Nanomaterials: Effects of Data Gap Filling and PChem Score-based Screening Approaches.

Ha MK, Trinh TX, Choi JS, Maulina D, Byun HG, Yoon TH. Ha MK, et al. Among authors: trinh tx. Sci Rep. 2018 Feb 16;8(1):3141. doi: 10.1038/s41598-018-21431-9. Sci Rep. 2018. PMID: 29453389 Free PMC article.

8

Identification of Ca-rich dense granules in human platelets using scanning transmission X-ray microscopy.

Trinh TX, Kwon SJ, Gerelkhuu Z, Choi JS, Song J, Yoon TH. Trinh TX, et al. J Synchrotron Radiat. 2020 May 1;27(Pt 3):720-724. doi: 10.1107/S1600577520002702. Epub 2020 Mar 16. J Synchrotron Radiat. 2020. PMID: 32381773 Free PMC article.

9

Scanning transmission X-ray microscopy study of subcellular granules in human platelets at the carbon K- and calcium L2,3-edges.

Shin J, Park S, Trinh TX, Kwon SJ, Bae J, Lee H, Valsami-Jones E, Wang J, Song J, Yoon TH. Shin J, et al. Among authors: trinh tx. Platelets. 2022 May 19;33(4):632-639. doi: 10.1080/09537104.2021.1981846. Epub 2021 Dec 14. Platelets. 2022. PMID: 34904525 Free article.

10

Automated machine learning in nanotoxicity assessment: A comparative study of predictive model performance.

Xiao X, Trinh TX, Gerelkhuu Z, Ha E, Yoon TH. Xiao X, et al. Among authors: trinh tx. Comput Struct Biotechnol J. 2024 Feb 9;25:9-19. doi: 10.1016/j.csbj.2024.02.003. eCollection 2024 Dec. Comput Struct Biotechnol J. 2024. PMID: 38414794 Free PMC article.

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