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Online Journal of Bioinformatics ©
Volume 11 (1): 106-127, 2010.
Selection and evaluation of gene-specific biomarkers in pre-clinical and clinical microarray experiments
Dan Lin1;2, Ziv Shkedy1, Geert Molenberghs1;2,Willem Talloen3, Hinrich W.H. Goelhmann3, Luc Bijnens3
1I-BioStat, Universiteit Hasselt, 2I-BioStat, Katholieke Universiteit Leuven, 3Janssen, Beerse, Belgium
Lin D, Shkedy Z, Molenberghs G, Talloen W, Goelhmann HWH, Bijnens L., Selection and evaluation of gene-specific biomarkers in pre-clinical and clinical microarray experiments., Online J Bioinformatics, 11 (1): 106-127, 2010. Biomarker discovery has become one of the major drivers of pharmaceutical research and drug development. Over the last five years, microarray experiments have become an increasingly common laboratory tool allowing investigation of the activity of thousands of genes simultaneously (Amaratunga and Cabera 2004). This enables the determination of genomic biomarkers using microarray experiments. In these experiments, some responses are measured indicating the outcome of the treatments. In such situations, the primary question of the study is whether the gene expression can serve as a biomarker for the responses or not. In this paper, we distinguish between two types of biomarkers: in the first type, the association between the gene expression and the response with adjustment for treatment effect can be captured by a straight line, while in the second type, the treatment effect both on the gene expression and the response plays a central role. We propose a joint model for the gene expression and the response, which allows the investigator (1) to detect differentially expressed genes as biomarkers and (2) to identify genes associated with the response.
Keywords: Joint Model; Microarray Experiments; Biomarkers; Differentially Expressed Genes.