<p><b>Copyright information:</b></p><p>Taken from "Quantitative gene expression assessment identifies appropriate cell line models for individual cervical cancer pathways"</p><p>http://www.biomedcentral.com/1471-2164/8/117</p><p>BMC Genomics 2007;8():117-117.</p><p>Published online 10 May 2007</p><p>PMCID:PMC1878486.</p><p></p>ey, while the pathways where only one or two cell lines are adequate models are white. The pathway example "RNA Processing" indicates some cell lines were anti-correlated and therefore a quantitative analysis was needed to identify better models that could be used to study this pathway. Error bars were generated from the correlation of a single cell line for each pathway and calculating the standard deviation. The pathways shown here represented a minimum of four cell lines or growth conditions. Numbers in parenthesis indicate how many cell lines were used to calculate the correlation. B: The highest and lowest pathway correlations between normal cervix and cervical cancer. The JNK cascade has a high correlation between normal and tumor, and is modeled well by most cell lines (Figure 5A). Mitosis and a number of other pathways involved in growth and regulation show poor correlation in their gene expression between normal and tumor, as expected. Numbers in parenthesis indicate how many genes were used to calculate the Pearson correlation coefficient
