On knowledge-based gene expression data analysis

Nowadays, technology and technological diversity of the gene expression measurements raise new issues related to proper data analysis and accurate interpretation of results. Because gene expression measurement includes many complex steps and is performed on randomly selected cells from population, the measured value of gene expression is a stochastic variable, and may vary in wide range. Consequently, based on gene expression values it is hard to distinguish the genes associated with condition of interest from those none-associated. Thepresent articleis focused on theoretical justification ofthe mentioned problemand proposesa solutionthrough complementing of data-driven analysis with knowledge-based approaches.