Literature DB >> 20041446

The Japanese toxicogenomics project: application of toxicogenomics.

Takeki Uehara1, Atsushi Ono, Toshiyuki Maruyama, Ikuo Kato, Hiroshi Yamada, Yasuo Ohno, Tetsuro Urushidani.   

Abstract

Biotechnology advances have provided novel methods for the risk assessment of chemicals. The application of microarray technologies to toxicology, known as toxicogenomics, is becoming an accepted approach for identifying chemicals with potential safety problems. Gene expression profiling is expected to identify the mechanisms that underlie the potential toxicity of chemicals. This technology has also been applied to identify biomarkers of toxicity to predict potential hazardous chemicals. Ultimately, toxicogenomics is expected to aid in risk assessment. The following discussion explores potential applications and features of the Japanese Toxicogenomics Project.

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Year:  2010        PMID: 20041446     DOI: 10.1002/mnfr.200900169

Source DB:  PubMed          Journal:  Mol Nutr Food Res        ISSN: 1613-4125            Impact factor:   5.914


  58 in total

1.  Predictive modeling of chemical hazard by integrating numerical descriptors of chemical structures and short-term toxicity assay data.

Authors:  Ivan Rusyn; Alexander Sedykh; Yen Low; Kathryn Z Guyton; Alexander Tropsha
Journal:  Toxicol Sci       Date:  2012-03-02       Impact factor: 4.849

2.  Discovery of Transcriptional Targets Regulated by Nuclear Receptors Using a Probabilistic Graphical Model.

Authors:  Mikyung Lee; Ruili Huang; Weida Tong
Journal:  Toxicol Sci       Date:  2015-12-07       Impact factor: 4.849

Review 3.  The Promise of AI for DILI Prediction.

Authors:  Andreu Vall; Yogesh Sabnis; Jiye Shi; Reiner Class; Sepp Hochreiter; Günter Klambauer
Journal:  Front Artif Intell       Date:  2021-04-14

Review 4.  Crowdsourcing biomedical research: leveraging communities as innovation engines.

Authors:  Julio Saez-Rodriguez; James C Costello; Stephen H Friend; Michael R Kellen; Lara Mangravite; Pablo Meyer; Thea Norman; Gustavo Stolovitzky
Journal:  Nat Rev Genet       Date:  2016-07-15       Impact factor: 53.242

5.  Identification of Translational microRNA Biomarker Candidates for Ketoconazole-Induced Liver Injury Using Next-Generation Sequencing.

Authors:  Dongying Li; Bridgett Knox; Binsheng Gong; Si Chen; Lei Guo; Zhichao Liu; Weida Tong; Baitang Ning
Journal:  Toxicol Sci       Date:  2021-01-06       Impact factor: 4.849

6.  Prediction of drug-induced liver injury using keratinocytes.

Authors:  Rika Hirashima; Tomoo Itoh; Robert H Tukey; Ryoichi Fujiwara
Journal:  J Appl Toxicol       Date:  2017-01-31       Impact factor: 3.446

7.  Human skin-derived stem cells as a novel cell source for in vitro hepatotoxicity screening of pharmaceuticals.

Authors:  Robim M Rodrigues; Joery De Kock; Steven Branson; Mathieu Vinken; Kesavan Meganathan; Umesh Chaudhari; Agapios Sachinidis; Olivier Govaere; Tania Roskams; Veerle De Boe; Tamara Vanhaecke; Vera Rogiers
Journal:  Stem Cells Dev       Date:  2013-09-21       Impact factor: 3.272

Review 8.  Analysis of the transcriptome in molecular epidemiology studies.

Authors:  Cliona M McHale; Luoping Zhang; Reuben Thomas; Martyn T Smith
Journal:  Environ Mol Mutagen       Date:  2013-08-01       Impact factor: 3.216

9.  Population-based dose-response analysis of liver transcriptional response to trichloroethylene in mouse.

Authors:  Abhishek Venkatratnam; John S House; Kranti Konganti; Connor McKenney; David W Threadgill; Weihsueh A Chiu; David L Aylor; Fred A Wright; Ivan Rusyn
Journal:  Mamm Genome       Date:  2018-01-20       Impact factor: 2.957

Review 10.  Integrative approaches for predicting in vivo effects of chemicals from their structural descriptors and the results of short-term biological assays.

Authors:  Yen Sia Low; Alexander Yeugenyevich Sedykh; Ivan Rusyn; Alexander Tropsha
Journal:  Curr Top Med Chem       Date:  2014       Impact factor: 3.295

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