Abstract:
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One pivotal advantage of using statistical modeling to biological system is that it leads the model to be a cost-effective and time-saving substitute for lab experiments in which patterns of the system are sometimes delicate to be observed. Especially the stochastic approach is useful to quantify the role of fluctuations in the behavior of the system of interest. Telomeres, which are shortened per normal cell division as a so-called 'mitotic clock', can maintain their lengths in cancer cells by two mechanisms, telomerase and Alternative Lengthening of Telomeres (ALT). However the connections between two mechanisms are complicated and still poorly understood. In this research, we show that the Abnormal Pathway Detection Algorithm from G-Networks, which are stochastic models motivated by queuing network theory, is useful to identify anomalous gene pathways expressing different mRNA expression levels in ALT cells as compared with a normal condition. This study expands our existing knowledge of genes associated with telomere maintenance mechanisms and provides a platform to understand a link between telomerase and ALT in different tumor types and normal tissues.
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