Journal of Drug Metabolism & Toxicology
Open Access
ISSN: 2157-7609
+44-20-4587-4809
ISSN: 2157-7609
+44-20-4587-4809
Md Masud Rana, Atul Chandra Singha, Md Shakil Ahmed and Md Nurul Haque Mollah
University of Rajshahi, Bangladesh
Posters-Accepted Abstracts: J Drug Metab Toxicol
Biomarker genes can help to forecast about a drug that will undesirably affect an individual for a given disease. There are several kinds of common side effect observed during drug administration and additionally the effect of toxicity of some common compound is not yet well known. The present study aimed to identify genomic biomarkers for early and sensitive detection of toxicity of a candidate drug. Mainly, transcriptomics data are toxicogenomics data of animals that have been treated with chemical compounds. There exists a web based Toxygates-software to discover the toxicogenomics biomarker. This biomarker also known as significantly differential expressed gene between two groups, where each group consist of gene-expressions data corresponding to compound levels, dose levels and measurement time levels. Basically Toxygates-software was developed using Welch��?s t-test and Mann-Whitney u-test. But these tests procedures are not so appropriate for the data-frame that was used in Toxygates-software. It was desirable to identify that what dose level or time point are responsible for revealing relationships between the toxic effects and gene expressionbut there is no options in the Toxygates-software to do it. To overcome these problems, we consider multistage nested designs that are more suitable than the existing test procedure based on Toxigate-software for those data frame. Both simulation and real data analysis results show that the proposed method improves the performance over the Toxygates-software for detecting biomarker gene.