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Research on Gastric Cancer’s Drug-resistant Gene Regulatory Network Model
Current Bioinformatics ( IF 4 ) Pub Date : 2020-02-29 , DOI: 10.2174/1574893614666190722102557
Zhi Li 1 , Tianyue Zhang 1 , Haojie Lei 1 , Liyan Wei 1 , Yuanning Liu 1 , Yadi Shi 2 , Shuyi Li 3 , Bowen Shen 1 , Hao Guo 4 , Zhangqian Chen 4 , Xiaorong Yi 4 , Hao Zhang 1
Affiliation  

Objective: Based on bioinformatics, differentially expressed gene data of drug-resistance in gastric cancer were analyzed, screened and mined through modeling and network modeling to find valuable data associated with multi-drug resistance of gastric cancer.

Methods: First, data sets were preprocessed from three aspects: data processing, data annotation and classification, and functional clustering. Secondly, based on the preprocessed data, each classified primary gene regulatory network was constructed by mining interactions among the genes. This paper computed the values of each node in each classified primary gene regulatory network and ranked these nodes according to their scores. On the basis of this, the appropriate core node was selected and the corresponding core network was developed.

Results and Conclusion: Finally, core network modules were analyzed, which were mined. After the correlation analysis, the result showed that the constructed network module had 20 core genes. This module contained valuable data associated with multi-drug resistance in gastric cancer.



中文翻译:

胃癌耐药基因调控网络模型的研究

目的:基于生物信息学,通过建模和网络建模分析,筛选和挖掘胃癌耐药基因的差异表达数据,以寻找与胃癌多药耐药相关的有价值的数据。

方法:首先,从三个方面对数据集进行预处理:数据处理,数据注释和分类以及功能聚类。其次,基于预处理数据,通过挖掘基因之间的相互作用来构建每个分类的一级基因调控网络。本文计算了每个分类的一级基因调控网络中每个节点的值,并根据它们的得分对其进行排名。在此基础上,选择了合适的核心节点并开发了相应的核心网络。

结果与结论:最后,对核心网络模块进行了分析和挖掘。经过相关分析,结果表明构建的网络模块具有20个核心基因。该模块包含与胃癌多药耐药性相关的有价值的数据。

更新日期:2020-02-29
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