Abstract:

Microarray experiment is a complicated multistep procedure, and since variability can be introduced at each experimental stage that caused some noisy gene expression data in the experiment. In order to obtain much valuable information from the data, many algorithms have been proposed for estimating gene expression level. At present, the most popular model, mmgMOS can improve the accuracy of microarray data analysis, but has a deficiency that the value of the parameter φ  used throughout the whole data set is fixed, while the fixed single value cannot represent real signals from various probes. An alternative way for appropriate parameter setting is  proposed to improve the accuracy in finding differential gene expression level.

Key words: bioinformatics;gene chip;gene expression level;probabilistic method