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Over-expressed genes

Over-expressed genes

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Conference Paper
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Prostate cancer is widely known to be one of the most common cancers among men around the world. Due to its high heterogeneity, many of the studies carried out to identify the molecular level causes for cancer have only been partially successful. Among the techniques used in cancer studies, gene expression profiling is seen to be one of the most po...

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... we compared our results with the existing findings from the literature. Table 3 and Table 4 display results and comparison of expression change between candidate Y-chromosome genes across different models. Table 3. Under-expressed genes Initially, we considered the significantly differentiated samples, which are highly cancerous and highly normal. ...
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... could identify only one common under-expressed gene (CD99) across these 3 models though there are many common over-expressed genes such as BPY2, XKRY2 and SRY etc. These genes that only exhibit early changes expression pattern are shown in gray colour in Table 4. ...
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... ALL model we focused on identifying the genes that generally have a differential expression due to prostate cancer. Out of the resulting candidates, some of the Y-chromosome genes can be recognized as most vital since they significantly vary in expression level across all the categories as illustrated in Table 3 and Table 4. Figure 5.1 to Figure 5.8 depict heatmaps of row-normalized expression for critically identified genes across 8 models in which intensity decrease from red to yellow. ...
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... analysis carried out by the categorical SVM model with a minimum accuracy of 95%, results in a set of decisive Y-chromosome genes namely CD99 (also known as MIC2), ASMTL, DDX3Y, and TXLNGY. Those genes are highlighted in yellow colour in Table 3 and Table 4. It is highly probable that the aforementioned Y-chromosome genes to be actively involved in prostate cancer generation and metastasis process when considering the high accuracy obtained for the SVM models. ...
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... Y-chromosome genes do not exhibit significant expression patterns when compared to the top-ranked genes in differential expression analysis but the changes in their expressions from normal tissue to cancerous tissue are significant for closer observations. Table 3 and Table 4 contains information about many other genes from our findings, which are correlated with Lau's work. Moreover, Dasari et al. [6] have done similar work to add stability to our findings. ...

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