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Possible Disease-Link Genetic Pathways Constructed by Hierarchical Clustering and Conditional Probabilities of Ovarian Carcinoma Microarray Data

机译:通过分层聚类和卵巢癌微阵列数据的条件概率构建可能的疾病关联遗传途径

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摘要

Different genes have different biological functions, these functions interactions between genes, moreover they play an important role in gene regulatory networks. In the recent cancer research field, a definite conclusion for the regulatory mechanisms of tumor genesis and metastasis has yet been found. Therefore we will apply oncogenes and suppressor genes from ovarian carcinoma micro array data analysis, using hierarchical clustering combined with Bayesian theorem to identify regulatory pathways. There are 19 regulatory paths identified by this scheme which include Wnt signaling pathway, TGF-β singling pathway, Gap junction and Pathway in cancer. Moreover we can understand the inhibition or activation between genes as well as their directions with validation by referring to the databases. The purpose of analytical method is not only analyzing complex cancer pathways or mechanism, but also tries to discover a more effective treatment path or model for cancer research in the future.
机译:不同的基因具有不同的生物学功能,这些功能在基因之间相互作用,而且它们在基因调控网络中起着重要的作用。在最近的癌症研究领域中,尚未找到关于肿瘤发生和转移的调节机制的明确结论。因此,我们将应用卵巢癌微阵列数据分析中的癌基因和抑制基因,并使用层次聚类结合贝叶斯定理来确定调控途径。该方案确定了19条调控途径,包括Wnt信号传导途径,TGF-β单一途径,Gap连接和癌症途径。此外,通过参考数据库,我们可以通过验证了解基因之间的抑制或激活及其方向。分析方法的目的不仅是分析复杂的癌症途径或机制,而且还试图为将来的癌症研究发现更有效的治疗途径或模型。

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