首页> 外文会议>2010 IEEE International Conference on Bioinformatics and Biomedicine >Detection and application of CagA sequence markers for assessing risk factor of gastric cancer caused by Helicobacter pylori
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Detection and application of CagA sequence markers for assessing risk factor of gastric cancer caused by Helicobacter pylori

机译:CagA序列标记在幽门螺杆菌引起胃癌危险因素评估中的应用

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As a marker of Helicobacter pylori, Cytotoxin-associated gene A (CagA) has been revealed to be the major virulence factor to cause gastroduodenal diseases. However, the molecular mechanisms that underlie the development of different gastroduodenal diseases caused by cagA-positive H. pylori infection remain unknown. Current studies are mainly limited to the relationship between EPIYA motifs in the CagA strain and diseases, but such a relationship is insufficient to explain the diversity of diseases. We propose a new and systematic method to analyze the relationship between the whole CagA sequence patterns and diseases. For this purpose, we introduced entropy calculation to detect key residues of CagA as the gastric cancer biomarkers, and then employed a supervised learning procedure to classify the cancer and non-cancer related CagA strains by using the key residues. We achieved 76% and 71% classification accuracy for Western and East Asian subtypes, respectively. Our study may help establish H. pylori biomarkers for predicting gastroduodenal disease outcome.
机译:作为幽门螺杆菌的标志物,已揭示细胞毒素相关基因A(CAGA)是引起胃生成疾病的主要毒力因素。然而,利于Caga阳性H.幽门螺杆菌感染引起的不同胃泌素疾病发展的分子机制仍然未知。目前的研究主要限于CAGA菌株和疾病中的EPIYA基序之间的关系,但这种关系不足以解释疾病的多样性。我们提出了一种新的和系统的方法来分析整个传奇序列模式和疾病之间的关系。为此目的,我们介绍了熵计算以检测Caga作为胃癌生物标志物的关键残留物,然后采用监督学习程序通过使用关键残留物来分类癌症和非癌症相关的Caga菌株。我们分别为西方和东亚亚型进行了76%和71%的分类准确性。我们的研究可能有助于建立H. Pylori生物标志物以预测胃生成疾病结果。

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