Abstract.
Tachyplesin I (TP-I) is an antimicrobial peptide isolated from the hemocytes of the horseshoe crab. A series of biochemical analysis has been performed to gain insight into the mechanism of its strong antimicrobial and anticancer activity. In this study, we employ the microarray technology to identify the co-regulated gene groups of TP-I on human glioma cell lines. The 3 phenotypes of cell lines are treated with the different doses of TP-I including 1-ug/ml, 4-ug/ml and blank groups. As a result, the differentially expressed genes are identified by the paired-comparison of the phenotypes. Considering the consistency within the replicated samples, only the 2572 differential genes are used for the biclustering analysis. Different from the standard clustering, the biclustering algorithms perform clustering along two dimensions of row and column of the data matrix. Detected local patterns may provide clues about the biological processes associated with different physiological states. With the expression data matrix of significant genes across 9 samples, we performs the geometrical biclustering algorithm to find significant co-expressed genes within every phenotype. The further GO analysis with the co-expressed genes are performed to infer the therapeutic and toxic effect of TP-I on human glioma cell lines at the genome level. Some biological processes are of interests. For example, the process related to actin is significantly enriched in Glioblastoma without the treatment with TP-I. Genes defenses virus with the treatment of TP-I. With the increasing dose of TP-I, some toxic effect such as a defensive response to other organism are shown. Our findings provides an alternative choice in the clinical pharmacy for treating glioma with TP-I.
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Zhao, H., Ding, H., Jin, G. (2014). De Novo Gene Expression Analysis to Assess the Therapeutic and Toxic Effect of Tachyplesin I on Human Glioblastoma Cell Lines. In: Wang, X., Pedrycz, W., Chan, P., He, Q. (eds) Machine Learning and Cybernetics. ICMLC 2014. Communications in Computer and Information Science, vol 481. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45652-1_44
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DOI: https://doi.org/10.1007/978-3-662-45652-1_44
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