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Title

Toxic Dose prediction of Chemical Compounds to Biomarkers using an ANOVA based Gene Expression Analysis

 

Authors

Mohammad Nazmol Hasan1,3*, Zobaer Akond1,4, Md. Jahangir Alam1, Anjuman Ara Begum1, Moizur Rahman2, Md. Nurul Haque Mollah1

 

Affiliation

1Bioinformatics Lab., Department of Statistics, University of Rajshahi, Rajshahi-6205, Bangladesh; 2Animal Husbandry and Veterinary Science, University of Rajshahi, Rajshahi-6205, Bangladesh; 3Department of Statistics, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur-1706, Bangladesh;

4Agricultural Statistics and ICT Division, Bangladesh Agricultural Research Institute (BARI), Gazipur-1701, Bangladesh;

 

Email

nazmol.sat.bsmrau@gmail.com

 

Article Type

Hypothesis

 

Date

Received July 5, 2018; Revised July 6, 2018; Accepted July 6, 2018; Published July 31, 2018

 

Abstract

The aim of toxicogenomic studies is to optimize the toxic dose levels of chemical compounds (CCs) and their regulated biomarker genes. This is also crucial in drug discovery and development. There are popular online computational tools such as ToxDB and Toxygates to identify toxicogenomic biomarkers using t-test. However, they are not suitable for the identification of biomarker gene regulatory dose of corresponding CCs. Hence, we describe a one-way ANOVA model together with Tukey’s HSD test for the identification of toxicogenomic biomarker genes and their influencing CC dose with improved efficiency. Glutathione metabolism pathway data analysis shows high and middle dose for acetaminophen, and nitrofurazone as well as high dose for methapyrilene as significant toxic CC dose. The corresponding regulated top seven toxicogenomic biomarker genes found in this analysis is Gstp1, Gsr, Mgst2, Gclm, G6pd, Gsta5 and Gclc.

 

Keywords

Dose, chemical Compounds, toxicogenomic biomarker, gene expression, One-way ANOVA, Tukey's HSD test

 

Citation

Hasan et al. Bioinformation 14(7): 369-377 (2018)

 

Edited by

P Kangueane

 

ISSN

0973-2063

 

Publisher

Biomedical Informatics

 

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.